1

The Ontology of Experiments+ PATO

Barry Smith

httpontologybuffaloedusmith

2

Plan

1 The Experiment Ontology

2 Upper Level Ontologies

3 The Ontology of Biomedical Investigations

4 Phenotype Ontology

3

EXPO

The Ontology of Experiments

L Soldatova R KingDepartment of Computer Science

The University of Wales Aberystwyth

4

EXPO

controlled vocabularymeta-modeltheory of contentknowledge management10487081048708 knowledge systematization10487081048708 knowledge sharing10487081048708 knowledge treatment10487081048708 knowledge reusabilitydata integration

5

EXPO Formalisation of Science

The goal of science is to increase our knowledge of the natural world through the performance of experiments

This knowledge should ideally be expressed in a formal logical language

Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning

6

7

8

9

Suggested Upper Merged Ontology

Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

2

Plan

1 The Experiment Ontology

2 Upper Level Ontologies

3 The Ontology of Biomedical Investigations

4 Phenotype Ontology

3

EXPO

The Ontology of Experiments

L Soldatova R KingDepartment of Computer Science

The University of Wales Aberystwyth

4

EXPO

controlled vocabularymeta-modeltheory of contentknowledge management10487081048708 knowledge systematization10487081048708 knowledge sharing10487081048708 knowledge treatment10487081048708 knowledge reusabilitydata integration

5

EXPO Formalisation of Science

The goal of science is to increase our knowledge of the natural world through the performance of experiments

This knowledge should ideally be expressed in a formal logical language

Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning

6

7

8

9

Suggested Upper Merged Ontology

Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

3

EXPO

The Ontology of Experiments

L Soldatova R KingDepartment of Computer Science

The University of Wales Aberystwyth

4

EXPO

controlled vocabularymeta-modeltheory of contentknowledge management10487081048708 knowledge systematization10487081048708 knowledge sharing10487081048708 knowledge treatment10487081048708 knowledge reusabilitydata integration

5

EXPO Formalisation of Science

The goal of science is to increase our knowledge of the natural world through the performance of experiments

This knowledge should ideally be expressed in a formal logical language

Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning

6

7

8

9

Suggested Upper Merged Ontology

Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

4

EXPO

controlled vocabularymeta-modeltheory of contentknowledge management10487081048708 knowledge systematization10487081048708 knowledge sharing10487081048708 knowledge treatment10487081048708 knowledge reusabilitydata integration

5

EXPO Formalisation of Science

The goal of science is to increase our knowledge of the natural world through the performance of experiments

This knowledge should ideally be expressed in a formal logical language

Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning

6

7

8

9

Suggested Upper Merged Ontology

Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

5

EXPO Formalisation of Science

The goal of science is to increase our knowledge of the natural world through the performance of experiments

This knowledge should ideally be expressed in a formal logical language

Formal languages promote semantic clarity which in turn supports the free exchange of scientific knowledge and simplifies scientific reasoning

6

7

8

9

Suggested Upper Merged Ontology

Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

6

7

8

9

Suggested Upper Merged Ontology

Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

7

8

9

Suggested Upper Merged Ontology

Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

8

9

Suggested Upper Merged Ontology

Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

9

Suggested Upper Merged Ontology

Adam Peaseapeasearticulatesoftwarecomhttpwwwarticulatesoftwarecom

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

10

SUMO top levelEntity

ndash Physical bull Object

ndash SelfConnectedObject raquo Substance raquo CorpuscularObject raquo Food

ndash Region ndash Collection ndash Agent

bull Process ndash Abstract

bull SetOrClass bull Relation bull Quantity

ndash Number ndash PhysicalQuantity

bull Attribute bull Proposition

11

Suggested Upper Merged Ontology

1000 terms 4000 axioms 750 rules

Associated domain ontologies totalling 20000 terms and 60000 axioms

[includes ontology of boundaries from BS]

12

SUMO Structure

Structural Ontology

Base Ontology

SetClass Theory Numeric Temporal Mereotopology

Graph Measure Processes Objects

Qualities

13

SUMO+Domain OntologyStructuralOntology

BaseOntology

SetClassTheory

Numeric Temporal Mereotopology

Graph Measure Processes Objects

Qualities

SUMO

Mid-Level

Military

Geography

Elements

Terrorist Attack Types

Communications

People

TransnationalIssues Financial

Ontology

TerroristEconomy

NAICSTerroristAttacks

hellip

FranceAfghanistan

UnitedStates

DistributedComputing

BiologicalViruses

WMD

ECommerceServices

Government

Transportation

WorldAirports

Total Terms Total Axioms Rules

20399 67108 2500

14

entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract

12

SUMO Structure

Structural Ontology

Base Ontology

SetClass Theory Numeric Temporal Mereotopology

Graph Measure Processes Objects

Qualities

13

SUMO+Domain OntologyStructuralOntology

BaseOntology

SetClassTheory

Numeric Temporal Mereotopology

Graph Measure Processes Objects

Qualities

SUMO

Mid-Level

Military

Geography

Elements

Terrorist Attack Types

Communications

People

TransnationalIssues Financial

Ontology

TerroristEconomy

NAICSTerroristAttacks

hellip

FranceAfghanistan

UnitedStates

DistributedComputing

BiologicalViruses

WMD

ECommerceServices

Government

Transportation

WorldAirports

Total Terms Total Axioms Rules

20399 67108 2500

14

entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract

13

SUMO+Domain OntologyStructuralOntology

BaseOntology

SetClassTheory

Numeric Temporal Mereotopology

Graph Measure Processes Objects

Qualities

SUMO

Mid-Level

Military

Geography

Elements

Terrorist Attack Types

Communications

People

TransnationalIssues Financial

Ontology

TerroristEconomy

NAICSTerroristAttacks

hellip

FranceAfghanistan

UnitedStates

DistributedComputing

BiologicalViruses

WMD

ECommerceServices

Government

Transportation

WorldAirports

Total Terms Total Axioms Rules

20399 67108 2500

14

entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract

14

entity physical object process dual object process intentional process intentional psychological process recreation or exercise organizational process guiding keeping maintaining repairing poking content development making constructing manufacture publication cooking searching social interaction maneuver motion internal change shape change abstract

15

corpuscular object =defA SelfConnectedObject whose parts have properties that are not shared by the whole

Subclass(es)organic object artifact

Coordinate term(s)content bearing object food substance

Axiom corpuscular object is disjoint from substance

substance =defAn Object in which every part is similar to every other in every relevant respect

16

advantages of SUMO

clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)

much more coherent than eg CYC upper level

much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)

FOL

17

problems with SUMO as Upper-Levelit contains its own tiny biology (protein

crustacean fruit-Or-vegetable )

it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )

no clear treatment of relations between instances vs relations between types

[all of these problems can be fixed]

18EXPO Experiment Ontology

19

representational style part_of experimental hypothesisexperimental actions part_of experimental design

20equipment part_of experimental design(confuses object with specification)

21

22

OBI

The Ontology of Biomedical Investigations

grew out of FuGE FuGO MGED PSI development activities

23

Overview of the Ontology of Biomedical Investigations

with thanks to Trish Whetzel (FuGO Working Group)

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

16

advantages of SUMO

clear logical infrastructure FOL (too expressive for decidability more intuitive (human friendly) than eg OWL)

much more coherent than eg CYC upper level

much more coherent than the upper level hard wired into OWL-DL (and a fortiori into OWL-FULL)

FOL

17

problems with SUMO as Upper-Levelit contains its own tiny biology (protein

crustacean fruit-Or-vegetable )

it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )

no clear treatment of relations between instances vs relations between types

[all of these problems can be fixed]

18EXPO Experiment Ontology

19

representational style part_of experimental hypothesisexperimental actions part_of experimental design

20equipment part_of experimental design(confuses object with specification)

21

22

OBI

The Ontology of Biomedical Investigations

grew out of FuGE FuGO MGED PSI development activities

23

Overview of the Ontology of Biomedical Investigations

with thanks to Trish Whetzel (FuGO Working Group)

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

17

problems with SUMO as Upper-Levelit contains its own tiny biology (protein

crustacean fruit-Or-vegetable )

it is overwhelmingly an ontology for abstract entities (sets functions in the mathematical sense )

no clear treatment of relations between instances vs relations between types

[all of these problems can be fixed]

18EXPO Experiment Ontology

19

representational style part_of experimental hypothesisexperimental actions part_of experimental design

20equipment part_of experimental design(confuses object with specification)

21

22

OBI

The Ontology of Biomedical Investigations

grew out of FuGE FuGO MGED PSI development activities

23

Overview of the Ontology of Biomedical Investigations

with thanks to Trish Whetzel (FuGO Working Group)

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

18EXPO Experiment Ontology

19

representational style part_of experimental hypothesisexperimental actions part_of experimental design

20equipment part_of experimental design(confuses object with specification)

21

22

OBI

The Ontology of Biomedical Investigations

grew out of FuGE FuGO MGED PSI development activities

23

Overview of the Ontology of Biomedical Investigations

with thanks to Trish Whetzel (FuGO Working Group)

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

19

representational style part_of experimental hypothesisexperimental actions part_of experimental design

20equipment part_of experimental design(confuses object with specification)

21

22

OBI

The Ontology of Biomedical Investigations

grew out of FuGE FuGO MGED PSI development activities

23

Overview of the Ontology of Biomedical Investigations

with thanks to Trish Whetzel (FuGO Working Group)

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

20equipment part_of experimental design(confuses object with specification)

21

22

OBI

The Ontology of Biomedical Investigations

grew out of FuGE FuGO MGED PSI development activities

23

Overview of the Ontology of Biomedical Investigations

with thanks to Trish Whetzel (FuGO Working Group)

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

21

22

OBI

The Ontology of Biomedical Investigations

grew out of FuGE FuGO MGED PSI development activities

23

Overview of the Ontology of Biomedical Investigations

with thanks to Trish Whetzel (FuGO Working Group)

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

22

OBI

The Ontology of Biomedical Investigations

grew out of FuGE FuGO MGED PSI development activities

23

Overview of the Ontology of Biomedical Investigations

with thanks to Trish Whetzel (FuGO Working Group)

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

23

Overview of the Ontology of Biomedical Investigations

with thanks to Trish Whetzel (FuGO Working Group)

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

24

OBI neacutee FuGOPurpose

Provide a resource for the unambiguous description of the components of biomedical investigations such as the design protocols and instrumentation material data and types of analysis and statistical tools applied to the data NOT designed to model biology

Enables consistent annotation of data across different

technological and biological domains powerful queries semantically-driven data integration

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

25

Motivation for OBI

Standardization efforts in biological and technological domains Standard syntax - Data exchange formats

To provide a mechanism for software interoperability eg FuGE Object Model

Standard semantics - Controlled vocabularies or ontology Centralize commonalities for annotation term

needs across domains to describe an investigationstudyexperiment eg FuGO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

26

Emerging FuGO Design Principles

OBO Foundry ontology utilize ontology best practices Inherit top level classes from an Upper Level ontology Use of the Relation Ontology Follow additional OBO Foundry principles Facilitates interoperability with other OBO Foundry

ontologiesOpen source approach

ProteacutegeacuteOWL Weekly conference calls Shared environment using Sourceforge (SF) and SF

mailing lists

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

27

OBI Collaborating CommunitiesCrop sciences Generation Challenge Programme (GCP)Environmental genomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiGenomic Standards Consortium (GSC)

wwwgenomicscehacukgenomecatalogueHUPO Proteomics Standards Initiative (PSI) psidevsourceforgenetImmunology Database and Analysis Portal wwwimmportorgImmune Epitope Database and Analysis Resource (IEDB)

httpwwwimmuneepitopeorghomedoInternational Society for Analytical Cytology httpwwwisac-netorgMetabolomics Standards Initiative (MSI) Neurogenetics Biomedical Informatics Research Network (BIRN)Nutrigenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiPolymorphismToxicogenomics MGED RSBI Group wwwmgedorgWorkgroupsrsbiTranscriptomics MGED Ontology Group

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

28

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

29

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

30

FuGO - Top Level Universals Continuant an entity that endureremains the same through time

bull Dependent Continuant depend on another entityEg Environment (depend on the set of ranges of conditions eg geographic location)

Eg Characteristics (entity that can be measured eg temperature unit)

- Realizable an entity that is realizable through a process (executedrun)Eg Software (a set of machine instructions)

Eg Design (the plan that can be realized in a process)

Eg Role (the part played by an entity within the context of a process)

bull Independent Continuant stands on its ownEg All physical entity (instrument technology platform document etc)

Eg Biological material (organism population etc)

Occurrent an entity that occursunfold in timebull Eg Temporal Regions Spatio-Temporal Regions (single actions or Event)

bull Process Eg Investigation (the entire lsquoexperimentalrsquo process)Eg Study (process of acquiring and treating the biological material)Eg Assay (process of performing some tests and recording the results)

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

31

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

32

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

33

Basic Formal Ontologya true upper level ontologyno interference with domain ontologiesno interference with physics cognitionno abstractano negative entitiesexplicit treatment of instances types and relations

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

34

Three dichotomies

instance vs type

continuant vs occurrent

dependent vs independent

everything in the ontology is a type

types exist in reality through their instances

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

35

instance vs type

experiments as instances

experiments as types

ontologies relate to types (kinds universals)

we need to keep track of instances in databases

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

36

BFO

ContinuantOccurrent(Process)

IndependentContinuant

DependentContinuant

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

37

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

DependentContinuant

(quality functiondisease)

Functioning Side-Effect Stochastic Process

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

38

BFO

ContinuantOccurrent(Process)

IndependentContinuant

(molecule cell organorganism)

PATO Functioning Side-Effect Stochastic Process

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

39

Unifying goal integration

Integrating datandash within and across these domainsndash across levels of granularityndash across different perspectives

Requiresndash Rigorous formal definitions in both ontologies

and annotation schemas

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

40

Some thoughts on the ontology itself

Outlinendash Definitions

bull how do we define PATO termsbull what exactly is it wersquore defining

ndash is_a hierarchybull what are the top-level distinctionsbull what are the finer grained distinctions

ndash shapes and colors

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

41

Itrsquos all about the definitions

OBO Foundry Principlendash Definitions should describe things in reality

not how terms are usedbull definitions should not use the word lsquodescribingrsquo

Scope of PATO = Phenotypic qualities

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

42

Old PATOEntity ndash Attribute ndash Value

Eye ndash Red ndash Dark

New PATOEntity ndash Quality

Eye ndash Red Eye ndash Dark Red

Dark Red is_a Red

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

43

What a quality is NOT

Qualities are not measurementsndash Instances of qualities exist independently of their

measurementsndash Qualities can have zero or more measurements

These are not the names of qualitiesndash percentagendash processndash abnormalndash high

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

44

Some examples of qualities

The particular redness of the left eye of a single individual flyndash An instance of a quality type

The color lsquoredrsquondash A quality type

Note the eye does not instantiate lsquoredrsquo

PATO represents quality types (universals)ndash PATO definitions can be used to classify quality

instances by the types they instantiate

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

45

the particular case ofredness (of a particularfly eye)

the type ldquoredrdquo

instantiates

an instance of an eye(in a particular fly)

the type ldquoeyerdquo

instantiates

inheresin (is aquality ofhas_bearer)

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

46

Qualities are dependent entities

Qualities require bearersndash Bearers can be physical objects or processes

Examplendash A shape requires a physical object to bear itndash If the physical object ceases to exist (eg it

decomposes) then the shape ceases to exist

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

48

Scale Bearer Quality Definition (proposed)

Physical Continuant Mass Equivalent to the sum of the mass of the parts of the bearer (mass at the particle level is primitiveoutwith PATO)

Physical Continuant Opacity An optical quality manifest by the capacity of the bearer to block light

PhysChem Liquid Concentration A compositional relational quality manifest by the relative quantity of some chemical type contained by the bearer

Molecular Gene splicing quality manifest by the splicing processes undergone by the bearer

Cellular Cell ploidy A cellular quality manifest by the number of genomes that are part of the bearer

Cellular Cell transformative potency

A cellular quality manifest by the capacity of the bearer cell to differentiate to different cell types

Organismal Tissue tone

Organismal Organism reproductive quality

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

49

How many types of shape are there

notched T-shaped Y-shaped branched unbranched antrose retrose curled curved wiggly squiggly round flat square oblong elliptical ovoid cuboid spherical egg-shaped rod-shaped heart-shaped hellip

How do we define them

How do we compare them

Shapes cannot be organized in a linear scale

Compare problem of classifying RNA structures

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

50

Standard case monadic qualitiesExamples

ndash E=kidney Q=hypertrophiedndash autodef a kidney which is hypertrophied

We assume that there is more contextual data (not shown)ndash eg genotype environment number of organisms

in study that showed phenotype

Interpretation (with the rest of the database record)ndash all fish in this experiment with a particular

genotype had a hypertrophied kidney at some point in time

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO

51

Who should use PATO

Originallyndash model organism mutant phenotypes

But alsondash ontology-based evolutionary systematicsndash neuroscience BIRNndash clinical uses

bull OMIMbull clinical records (clinical manifestations)bull drug effects chemical effects

ndash to define terms in other ontologiesbull eg diploid cell invasive tumor engineered gene

condensed chromosome

• The Ontology of Experiments + PATO
• Plan
• EXPO
• Slide 4
• EXPO Formalisation of Science
• Slide 6
• Slide 7
• Slide 8
• Suggested Upper Merged Ontology
• SUMO top level
• Suggested Upper Merged Ontology
• SUMO Structure
• SUMO+Domain Ontology
• Slide 14
• Slide 15
• advantages of SUMO
• problems with SUMO as Upper-Level
• Slide 18
• Slide 19
• Slide 20
• Slide 21
• OBI
• Overview of the Ontology of Biomedical Investigations
• OBI neacutee FuGO
• Motivation for OBI
• Emerging FuGO Design Principles
• OBI Collaborating Communities
• Slide 28
• Slide 29
• FuGO - Top Level Universals
• Slide 31
• Slide 32
• Basic Formal Ontology
• Three dichotomies
• instance vs type
• BFO
• Slide 37
• Slide 38
• Unifying goal integration
• Some thoughts on the ontology itself
• Itrsquos all about the definitions
• Old PATO Entity ndash Attribute ndash Value Eye ndash Red ndash Dark
• What a quality is NOT
• Some examples of qualities
• Slide 45
• Qualities are dependent entities
• Slide 48
• How many types of shape are there
• Standard case monadic qualities
• Who should use PATO