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Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University of Queensland 20 August, 2002

Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

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Page 1: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Formal versus Material Ontologies for Information

Systems Interoperation in the Semantic Web

Work in progress

R. Colomb

School of ITEE, The University of Queensland

20 August, 2002

Page 2: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Outline

• Ontologies, upper ontologies,and semantic heterogeneity

• Sample of upper ontology efforts

• Semantic heterogeneity

• The synthetic a priori of Kant

• Application to the ontologies

• So what?

Page 3: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Ontologies, upper ontologies,and semantic heterogeneity

• Application-specific - SIC, SNOMED

• Upper ontologies application-independent• …what we now refer to as philosophical ontology has

sought the definitive and exhaustive classification of entities in all spheres of being … including the types of relations by which entities are tied together

• Heterogeneity - enemy target example

Page 4: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Sample of upper ontology efforts

• Cyc

• SUMO

• OntoClean

• GOL

• Bunge-Wand-Weber (BWW)

• WordNet

Page 5: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Cyc

• Transaction - The collection of actions performed by two or more agents cooperating (willingly) under some agreement wherein each agent performs actions in exchange for the actions of the other(s). Note that a case of attack-and-counterattack in warfare is not a Transaction; nor is fortuitous cooperation without agreement (e.g. where a group of investors who, unknown to each other, all buy the same stock almost at once, thereby driving up its price). For transactions involving an exchange of user rights (to goods and/or money) between agents, see the specialization of ExchangeOfUserRights

• Subtype of PurposefulAction, CooperativeEvent

Page 6: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

SUMO

• Transaction - The subclass of ChangeOfPossession where something is exchanged for something else. subclass of ChangeOfPossession

• ChangeOfPossession - The Class of Processes where ownership of something is transferred from one Agent to another. subclass of SocialInteraction

• SocialInteraction - The subclass of IntentionalProcess that involves interactions between CognitiveAgents. subclass of IntentionalProcess

• IntentionalProcess- A Process that is deliberately set in motion by a CognitiveAgent. subclass of Process

Page 7: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

OntoClean

• Quality• Quality Region• Aggregate

– Amount of matter– Arbitrary Collection

• Object– Physical Object

• Body• Ordinary Object

– Mental Object

• Feature– Relevant Part

– Place

• Occurrence– State

– Process

– Accomplishment

Page 8: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

GOL

• Entity– Set

» Extension– Urelement

» Individual» Chronoid (temporal duration)» Topoid (spatial region)» Substance» Moment» Quality» Relational Moment» Universal» Relational Universal

Page 9: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Bunge-Wand-Weber (BWW)

• Thing

• Property and Attribute

• State of a Thing: at a point in time, the attributes of a thing have values.

• Event: change of state in a thing.

• History of a Thing: a sequence of events in a thing.

• Type/Class and Subtype/Subclass

• Composite thing: is composed of (made up of) things other than itself. Things in the composite are part-of the composite.

Page 10: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

WordNet

• Abstraction

• Act (human)

• Entity

• Event

• Group

• Phenomenon

• Possession

• Psychological Feature

• State

Page 11: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Semantic heterogeneity

• Structural– Can be overcome with more or less elaborate views

• vs Fundamental– The words mean something a little different in the two

systems

Page 12: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Transaction examples• the interaction with Amazon.com resulting in the placing of an

order and the supply of credit card details.• the subsequent packing and shipping of the order, its receipt

by the purchaser in good condition, and the acceptance of the credit card charge by Visa.

• the interaction with Medline resulting in the placing of a query and the return of a collection of abstracts

• the borrowing and ultimate return of a book by the University of Queensland library from the University of Sydney library (interlibrary loan), on behalf of an academic (who must also borrow and return the book from the University of Queensland library).

• the interaction between the 2002 Salt Lake City Winter Olympics results processing agent and the agents responsible for the maintenance of results on multiple web sites ultimately completing with the information that the medal results for ice hockey have been recorded on all sites.

Page 13: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Searle’s Institutional Facts

• Brute fact X counts as institutional fact Y in context C– Eg Marriage, naming, buying

• Result of speech act

• Information systems concerned mostly with institutional facts

• Institutional facts need background for interpretation

Page 14: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Background

– Searle: The literal meaning of any sentence can only determine its truth conditions or other conditions of satisfaction against a background of capacities, dispositions, know-how, etc., which are not themselves a part of the semantic content of the sentence.

• Eg our expectation of the behaviour of objects in our environment, and of how various kinds of situations are supposed to develop.

Page 15: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Institutional facts immanent

• Nature of institutions means new institutional facts easily created– eg UQITEE-funded travel

• Transcendent system (rules of chess) give global shape– Permit ontology of openings, end games, etc– Rule change part of game makes system

immanent, lose ontology.

Page 16: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Institutional Facts Immanent

• Only local warrant needed for creation of new institutional fact

• Institutional facts are in complex contexts, but ultimately immanent

• So no reason to expect an a priori ontology

Page 17: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Synthetic a priori

• We can know a priori only how we represent knowledge, not what we can know

Page 18: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Synthetic a priori

• Space is the form of all appearances of outer sense, i.e.. the subject condition of sensibility, under which alone outer intuition is possible for us– Includes identification of objects

Page 19: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Synthetic a priori

• Time is the form of inner sense, i.e., of the intuition of our self and our inner state– the possibility of either simultaneity or

succession in the perception of objects.

Page 20: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Synthetic a priori

• Quantity unity, plurality, and totality– Also number

• Quality reality, negation and limitation• Modality possibility – impossibility, existence –

non-existence, necessity – contingency• Relation inherence and subsistence, causality and

dependence, and community (reciprocity between agent and patient)

Page 21: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Elements of formal ontology

• From space – identity• From time – sequence• From quantity – representation structures, the

part/whole relationship, arithmetic• From quality – negation, unity, identity of complex

objects• From modality – formal logic• From community – entities and attributes,

dependence, causality, mutual exclusion and complex objects

Page 22: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Formal vs material ontology

• Formal– GOL– Ontoclean– BWW

• Material– WordNet

• Mixed– Cyc– SUMO

Page 23: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

formal ontologies <- knowledge representation

• Programs = algorithms + data structures• KR systems follow the categories• Not so well as humans• Formal ontologies add richness• But are not qualitatively different• A tsunami is not a partial differential equation

Page 24: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

So what?

• Material ontologies fail due to semantic heterogeneity

• Formal ontologies are neutral wrt content– More limited aim

• Provide rich abstract data types

• Do not resolve semantic heterogeneity

Page 25: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Final thought

• Same entity can be represented differently for different purposes. Eg, aircraft might be– Part/whole to manufacturer (bill of materials)

– Set/instance to airline (seats)

– Process/accomplishments to production scheduling

– Physical object/ qualities to inspection system

• But one view might incorporate elements of all of these

Page 26: Formal versus Material Ontologies for Information Systems Interoperation in the Semantic Web Work in progress R. Colomb School of ITEE, The University

Final thought

• Formal ontologies not content– Formal concepts should not be at top of

subsumption structures• A tsunami is not a partial differential equation

• A bill of materials is not a part-whole system

– But using schemas/ variable instantiation– Separate formal and material as facets