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RoleofNISTinRealizingOKN
RamD.Sriram,Ph.D.Chief,SoftwareandSystemsDivisionInformationTechnologyLaboratory
Outline
• NISTBackground• OKNRelatedProjects• Expectations
2
NIST - Bird’s eye view
CourtesyHDRArchitecture,Inc./SteveHall©Hedrich Blessing
TheNationalInstituteofStandardsandTechnology(NIST)iswhereNobelPrize-winningsciencemeetsreal-worldengineering.
Withanextremelybroadresearchportfolio,world-classfacilities,nationalnetworks,andaninternationalreach,NISTworkstosupportindustryinnovation– ourcentralmission.
NIST’sMission
•TopromoteU.S.
innovationandindustrial
competitivenessby
advancingmeasurement
science,standards,
andtechnologyinwaysthat
enhanceeconomicsecurity
andimproveourqualityoflife.
U.S.EconomyDepends onNISTMeasurements
• Majorassets– ~3,000employees– ~2,800associatesandfacilitiesusers– ~1,300fieldstaffinpartnerorganizations– Twomainlocations:Gaithersburg,Md.,andBoulder,Colo.
– Fourexternalcollaborativeinstitutes:basicphysics,biotech,quantum,andmarinescience
– NobelPrizeWinners:1997,2001,2005,2007
NIST:BasicStatsandFacts
FY2016Appropriations$971.3M
©R.Rathe
MEP($155M)
Construction($119M)
NISTLabs($690M)
Others($7.3M)
RamD.Sriram
NationalInstituteofStandardsandTechnology(NIST)
RESEARCHCOMPONENTS
InteractingwithNIST
• GuestResearchers/FacultyAssociates• GrantsandContracts• IPA• SummerStudents• NRCPostDoctoralProgram• CollaborativeProposals
Outline
• NISTBackground• OKNRelatedProjects• Expectations
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OKNRelatedProjects
• CoreProductModel&Beyond(EL&ITL)• Ontologies&CategoryTheory(ITL&EL)• ExtractingDomainSpecificTermsFromDocuments(ITL&MML)
• TREC(ITL)
10
GenericInformationModelingRequirements
• Modelconstruction• Representationacrossscales• Broadaccommodationformultipleformalisms• Separationofdomain-specificconcerns• Integrationandaggregationacrossmodels• Modelevolution• Flexibilityandmodularity• Scalability
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CoreProductModel(1994-2010)• Objective:base-levelproductmodelthatis:
– generic– extensible– independentofanyoneproductdevelopment
process– capableofcapturingfullengineeringcontext
• Keyfeature:explicitrepresentationofFunction– Form- Behavior
(incontrasttoSTEPAP203thatessentiallyrepresentsonlyform)
KnowledgeRepresentation
Form Function
Behavior
Relationships Information
Geometry
Material
A product is represented by a hierarchy of entities of the class Artifact, which is an aggregation of Function, Form and Behavior. Function represents what the artifact is supposed to do; Form represents the proposed design solution for the design problem specified by the Function; and Behavior represents the evaluation of how the artifact implements its function.
FormRuptureDisc
DigitalPicture DetailedDesign3DModel
Function
SimplifiedFunctionFlow
DetailedFunctionFlow
FunctionLinks
LinksbetweenFunctionandArtifact
DesignObjectsFunctiontypes FunctionTaxonomy
Function Conveyance-function Usage-function Advance Sink Channel Absorb Conduct Consume Convey Destroy Direct Dissipate Divert Eliminate Guide Empty Generic-move Export Rotate Remove Transfer Source Translate Add Transmit Create Transport Emit Signal/Control- Extract function Generate Actuate Import Adjust Supply Close Storage Decrease Accumulate Delay Collect Detect Store Display Combination/ Equalize distribution-function Enhance Branch Generic-control Combine Identify Connect Increase Couple Indicate Distribute Inhibit Divide-flow Limit . . . . . .
CPM:FourCategoriesofClasses1. Classesthatprovidesupportinginformationfor
theobjects(abstractclasses)forstoringcommoninformation– CoreProductModel,CommonCoreObject,
CommonCoreRelationship– CoreEntity,CoreProperty
2. Classesofphysicalorconceptualobjects– Artifact,Feature,Port,Specification,Requirement– Function,TransferFunction,Flow,Behavior– From,Geometry,Material
3. Classesthatdescriberelationshipsamongobjects,theyarederivedfromCommonCoreRelationship– Constraint,Usage,Trace,EntityAssociation
4. Classesthatarecommonlyusedbyotherclasses.– Information,ProcessInformation,Rational
CPM:ThreeKindsofAssociationsAllobjectclasseshavetheirownseparate,independentdecompositionhierarchiesbyattributessuchassubArtifacts/subArtifactOffortheArtifactclass.
Thereareassociationsbetween:– aSpecificationandtheArtifactthatresultsfromit– aFlowanditssourceanddestinationArtifactsanditsinputand
outputFunctions– anArtifactanditsFeatures.
FouraggregationsarefundamentaltotheCPM:– Function,FormandBehavioraggregateintoArtifact– FunctionandFormaggregateintoFeature– GeometryandMaterialaggregateintoForm– RequirementaggregatesintoSpecification.
OpenAssemblyModel• Objectives:
– standardrepresentationforassemblyandsystem-leveltoleranceinformation
– extensible• Keyfeatures:
– emphasizesinformationrequirementsforpartfeaturesandassemblyrelationships
– assemblyasaconceptandassemblyasadatastructure
CPM&OPMleads:Fenves &Sudarsan
ExtensiontoCPM:OpenAssemblyModel
ProductRepresentation:Summary
PropertySpecificationBehavior
Form Geometry Material
Object
Function
Strength view Kinematics viewShape view
Idealization
Mapping
Master Model
Functional Model
DirectUndirect
SetRel. ConstraintAssemblyRel Reference
Relationship
Requirement
Family Designation
PFEM_Artifact
ConfigurationProduct series
Component series
Evaluation
Design Evaluation
Family Derivation
Series Derivation
Version Derivation
Family
Product Family
Component Family
Series
Product Version
Component Version
Version
Entity
FeatureArtifact
Part
Artifact Association
Ass’y Association
Composite Feature
Ass’y Feature
Assembly
Ass’y feature association
Ass’y feature association rep.
Position orientation
Relative motion
Connection
Intermittent
Movable
Fix
OAMFeature
Tolerance
Kinematic Pair Kinematic Path Parametric Ass’y Constraint
Evolution Rationale
Rationale
Design Rationale
Design Justification Evolution.
Family Derivation Rat.
Develop. Spec. Evolution
Develop. Spec.
Regulation
Technology
Design Justification
Optimal Suf.
PrincipleCase Rule Catalog
Authority Trade Off
Design Evolution Rat.
1
2
3
4
5
6
ImpactsofNIST’s ProductModelingWork• MajorportionsofCPM/OAMwasincludedinSTEPPart109• CPM/OAMisbeingusedbyseveralorganizations• PortionsofCPM/OAMwasusedinCADvendorsoftware(EU)• OntoSTEP releasedasopensourcesoftware• ExtensionstoCPM/OAM
– GeorgiaInst.ofTech:Design/Analysisintegration§ Createscomplexanalysismodelsfaster§ BeingintegratedintoworkwithLockheedMartin
– UniversityofWisconsinMadison:Heterogeneousmaterialmodeling§ Supportsanewapproachtomesh-freeanalysis
– ArizonaStateUniversity:Extendedfeatures§ BeingusedinaprojectforUSArmy
– SyracuseUniversity:Tolerance,kinematics,andassemblyanalysis§ Providesgreatersupportforintegratingproductspecificationswithmanufacturingand
inspection.– UniversityofMaryland,CollegePark:Assembly-basedsearch
§ Allowsorganizationstouseexistingdesigns§ Currentlyinnegotiationswithanindustrialpartner
TheNextSteps
• EngineeringLaboratoryiscurrentlyinvolvedintheIndustryOntologiesFoundry
24
OKNRelatedProjects
• CoreProductModel&Beyond(EL&ITL)• Ontologies&CategoryTheory(ITL&EL)• ExtractingDomainSpecificTermsFromDocuments(ITL&MML)
• TREC(ITL)
25
26
OntologySpectrum
weak semantics
strong semantics
IsDisjointSubclassofwithtransitivityproperty
ModalLogic
LogicalTheory
Thesaurus HasNarrowerMeaningThan
Taxonomy IsSub-Classificationof
Conceptual Model IsSubclassof
DBSchemas,XMLSchema
UML
FirstOrderLogic
XML
ER
ExtendedER
DescriptionLogicDAML+OIL,OWL
RDF/SXTM
SyntacticInteroperability
StructuralInteroperability
SemanticInteroperability
Courtesy:LeoObrst,MITRE
problem normal normal
Image segmentation
Feature Vectors Computation
Mapping calculated featurevectors into disease ontology
Highlighting regions withdeviation from normal conditions
Input Image
Output:Suggestion of the potential diagnosis Sugessted diagnosis: Ulcer...
Methodology for Image to Diagnosis Through Disease Ontology
27
Fragment of Disease Ontology in Protege’-Ontoviz
28
UMLRepresentationofInflammatoryBowelDisease
+endoscopic feature1 : <unspecified> = ulcers+location : string(idl) =distal small interstine / proximal colon/ distal colon/ rectum
Idiopathic inflammatory bowel disease
-endoscopic feature 2 : <unspecified> = strictures-endoscopic 3 : <unspecified> = cobblestonning
Crohns disease-endoscopic feature 2 : <unspecified> = pseudopolyps
Ulcerative colitis
29
FormoreaboutOntologies:SeeOntologySummitWebPages
• TheOntologySummitisanannualseriesofeventsthatstartedin2006withthejointsponsorshipofOntolog andNIST
• Thesummitislargelyaself-organizing,bottom-up,volunteerdriveneffort,thatsolicitscontributionsfromparticipantsaroundtheworldinbothindustryandacademia
• Eachyear'sSummit(differentthemeeveryyear)consistsofaserieseventsandcontinueddiscoursespanningthreemonths,culminatinginafree,two-dayface-to-faceworkshopandsymposium
• URL:http://ontologforum.org/index.php/OntologySummit
30
• Mostsemanticmodels(e.g.,OWL)arebasedonformallogicandsettheory.Thisisusuallysufficientforenablinginformationinteroperabilitybetweensystems.
• Logicalmodelsareusuallylessrelevantinsystemanalysisandbehavior.
• Otherrelevantclassesofsemanticsincludestochastic,dynamicalsystems,geometricandcomputationalmodels.
• Weareexploringtheuseofcategorytheory(CT)asaflexiblefoundationforrepresenting,analyzingandinterlinkingthisbroaderclassofsemanticmodels.
TowardCategoryTheory
Inmechanicalengineering,Newton’scalculusprovides:
● Alanguageforrepresentingmechanicalstates,processesandbehavior.
● Acollectionofstandardtechniquesandalgorithmsforanalyzingmechanicalsystemsexpressedinthislanguage.
Thepredicatecalculusplayssimilarrolesforlogic,andtheλ-calculusforcomputation.
CTisacalculusofabstractprocesseswhichgeneralizesallthreeofthesecontexts.
FormalrepresentationinCTprovides“hygiene”,helpingtoguideourthinkingandtoavoiderrorsandmisrepresentation.
ACalculus ofInformationInmechanicalengineering,Newton’scalculusprovides:
• Alanguageforrepresentingmechanicalstates,processesandbehavior.
• Acollectionofstandardtechniquesandalgorithmsforanalyzingmechanicalsystemsexpressedinthislanguage.
Thepredicatecalculusplayssimilarrolesforlogic,andtheλ-calculusforcomputation.
CTisacalculusofabstractprocesseswhichgeneralizesallthreeofthesecontexts.
FormalrepresentationinCTprovides“hygiene”,helpingtoguideourthinkingandtoavoiderrorsandmisrepresentation.
33
OntologySpectrum
weak semantics
strong semantics
IsDisjointSubclassofwithtransitivityproperty
ModalLogic
LogicalTheory
Thesaurus HasNarrowerMeaningThan
Taxonomy IsSub-Classificationof
Conceptual Model IsSubclassof
DBSchemas,XMLSchema
UML
FirstOrderLogic
RelationalModel,XML
ER
ExtendedER
DescriptionLogicDAML+OIL,OWL
RDF/SXTM
SyntacticInteroperability
StructuralInteroperability
SemanticInteroperability
Courtesy:LeoObrst,MITRE
IntegratingSupplyChainDatabases:CTApproach
Wisnesky R,Breiner S,JonesA,Spivak DI,Subrahmanian E.UsingCategoryTheorytoFacilitateMultipleManufacturingServiceDatabaseIntegration.ASME.J.Comput.Inf.Sci.Eng.2017;17(2):021011-021011-11.doi:10.1115/1.4034268.
OKNRelatedProjects
• CoreProductModel&Beyond(EL&ITL)• Ontologies&CategoryTheory(ITL&EL)• ExtractingDomainSpecificTermsFromDocuments(ITL&MML)
• TREC(ITL)
35
DisciplinaryInformationSystems
SearchwindowDocumentWindow.…….…..
.…….…..
.…….…..
.…….…...…….…...…….…...…….…...…….…...…….…...…….…..
OCR
.…….…...…….…...…….…...…….…...…….…...…….…...…….…..
ProcessedText
Parsers
Root&RulebasedCo-wordAnalysis
Word2Vec
Compoundnouns
Linguisticmapandtaxonomy
Tools
SearchTermMap
RootandRulebasedmethodallowsfor- Autocompletebasedusageinthe
domainforsearch- Facilitatescreationoftaxonomy- Couldbeconnectedtoontologytools- ExperimentswithIUCR,APS,others- Itenhancesperformanceofothertools
suchasWord2vecfortopicmodeling
OKNRelatedProjects
• CoreProductModel&Beyond(EL&ITL)• Ontologies&CategoryTheory(ITL&EL)• ExtractingDomainSpecificTermsFromDocuments(ITL&MML)
• TREC(ITL)
37
TREC
• Aworkshopseriesthatprovidestheinfrastructureforlarge-scaleevaluationof(text)retrievaltechnology– realistictestcollections– uniform,appropriatescoringprocedures– aforumfortheexchangeofresearchideasandforthediscussionofresearchmethodology
TREC is an annual benchmarking exercise that has become a de facto standard in Information Retrieval evaluation.
Stephen RobertsonMicrosoft
SIGIR 2007
Establishes the research methodology
TREC has proven to be a valuable forum in which IBM Research has contributed to an improved understanding of search, while at the same time the insights obtained by participating in TREC have helped to improve IBM’s products and services.
Alan Marwick, et al.IBM chapter of the TREC book
2005
Facilitates technology
transfer
In other words, for every $1 NIST and its partners invested in TREC, at least $3.35 to $5.07 in benefits accrued to IR researchers…These responses suggest that the benefits of TREC to both private and academic organizations go well beyond those quantified by this study’s economic benefits.
RTI InternationalEconomic Impact Assessment
of NIST’s TREC ProgramDecember 2010
Amortizes the costs of
infrastructure
This project [the TREC Legal track] can be expected to identify both cost effective and reliable search and information retrieval methodologies and best practice recommendations, which, if adhered to, certainly would support an argument that the party employing them performed a reasonable ESI search, whether for privilege review or other purposes.
Magistrate Judge Paul Grimm Victor Stanley v. Creative Pipe
Forms/solidifies a research community
The TREC data revitalized research on information retrieval. Having a standard, widely available, and carefully constructed set of data laid the groundwork for further innovation in the field. The yearly TREC conference fostered collaboration, innovation, and a measured dose of competition (and bragging rights) that led to better information retrieval.
Hal VarianGoogle Chief Economist
March 4, 2008
Improves the state of the
art
Outline
• NISTBackground• OKNRelatedProjects• Expectations
40
Expectations
• Provideagenerictemplateforstructuringknowledge
• Developevaluationandtestmethodologies• ExploreTRECtrackforevaluatingOKNinvariousdomains
• Leveragefunding
41