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Horizontal Integration of WarfighterIntelligence DataA Shared Semantic Resource for theIntelligence CommunityBarry Smith, ...
Horizontal Integration of Intelligence2
Horizontal Integration• “Horizontally integrating warfighter intelligencedata … requires access (including discovery,searc...
Challenges to the horizontalintegration of Intelligence Data• Quantity and variety– Need to do justice to radical heteroge...
Horizontal integration=def. multiple heterogeneous data resourcesbecome aligned in such a way that search andanalysis proc...
This 6
7will not yield horizontal integration
Strategy• Strategy to avoid stovepipes requires a solution that is– Stable– Incrementally growing– Flexible in addressing ...
Distributed Common Ground System–Army (DCGS-A)SemanticEnhancement ofthe Dataspaceon the CloudDr. Tatiana MalyutaNew York C...
Dataspace on the CloudSalmen, et al,. Integration of Intelligence Datathrough Semantic Enhancement, STIDS 2011• strategy f...
Dataspace on the Cloud• Cloud (Bigtable-like) store of heterogeneous data anddata semantics– Unified representation of str...
Dataspace on the Cloud• Cloud (Bigtable-like) store of heterogeneous data anddata semantics– Unified representation of str...
Basis of the SE ApproachSE ontology labels• Focusing on the terms (labels, acronyms, codes) used in the sourcedata.• Where...
SE Requirements to achieve HorizontalIntegration• The ontologies must be linked together throughlogical definitions to for...
Creating the SE Suite of Ontology Modules• Incremental distributed ontology development– based on Doctrine;– involves SMEs...
Intelligence Ontology SuiteNo. Ontology Prefix Ontology Full Name List of Terms1 AO Agent Ontology2 ARTO Artifact Ontology...
Ontology Development Principles• Reference ontologies – capture generic contentand are designed for aggressive reuse inmul...
Illustrationvehicle =def: an object used fortransporting people or goodstractor =def: a vehicle that is used fortowingcran...
IllustrationVehicleTractorWheeledTractorArtilleryTractorWheeledArtilleryTractorArtilleryVehicleBlack –referenceontologiesR...
Role of Reference Ontologies• Normalized (compare Ontoclean)– Allows us to maintain a set of consistent ontologies– Elimin...
Examples of Principles• All terms in all ontologies should be singularnouns• Same relations between terms should be reused...
SE Architecture• The Upper Level Ontology (ULO) in the SEhierarchy must be maximally general (no overlapwith domain ontolo...
Architecture Illustration
Intelligence Ontology SuiteNo. Ontology Prefix Ontology Full Name List of Terms1 AO Agent Ontology2 ARTO Artifact Ontology...
Anatomy Ontology(FMA*, CARO)EnvironmentOntology(EnvO)InfectiousDiseaseOntology(IDO*)BiologicalProcessOntology (GO*)CellOnt...
Shared Semantic Resource• Growing collection of shared ontologiesasserted and application• Pilot program to coordinate a s...
• Given the principles of building the SE (governance, distributedincremental development, common architecture) the next s...
28
29MI L I TARY OPERAT I ONS ONTOLOGY SUI T E
Anatomy Ontology(FMA*, CARO)EnvironmentOntology(EnvO)InfectiousDiseaseOntology(IDO*)BiologicalProcessOntology (GO*)CellOnt...
continuantindependentcontinuantportion ofmaterialobjectfiat objectpartobjectaggregateobjectboundarysitedependentcontinuant...
occurrentprocessualentityprocessfiat processpartprocessaggregateprocessboundaryprocessualcontextspatiotemporalregionscatte...
Conclusion
Acknowledgements
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Horizontal integration of warfighter intelligence data

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Transcript of "Horizontal integration of warfighter intelligence data"

  1. 1. Horizontal Integration of WarfighterIntelligence DataA Shared Semantic Resource for theIntelligence CommunityBarry Smith, University at Buffalo, NY, USATatiana Malyuta, New York City College of Technology, NYWilliam S. Mandrick, Data Tactics Corp., VA, USAChia Fu, Data Tactics Corp., VA, USAKesny Parent, Intelligence and Information Warfare Directorate, CERDEC, MD, USAMilan Patel, Intelligence and Information Warfare Directorate, CERDEC, MD, USA
  2. 2. Horizontal Integration of Intelligence2
  3. 3. Horizontal Integration• “Horizontally integrating warfighter intelligencedata … requires access (including discovery,search, retrieval, and display) to intelligence dataamong the warfighters and other producers andconsumers via standardized services andarchitectures. These consumers include, but arenot limited to, the combatant commands,Services, Defense agencies, and the IntelligenceCommunity.”Chairman of the Joint Chiefs of StaffInstruction J2 CJCSI 3340.02A1 August 2011
  4. 4. Challenges to the horizontalintegration of Intelligence Data• Quantity and variety– Need to do justice to radical heterogeneity in therepresentation of data and semantics Dynamicenvironments– Need agile support for retrieval, integration andenrichment of data• Emergence of new data resources– Need in agile, flexible, and incremental integrationapproach
  5. 5. Horizontal integration=def. multiple heterogeneous data resourcesbecome aligned in such a way that search andanalysis procedures can be applied to theircombined content as if they formed a singleresource
  6. 6. This 6
  7. 7. 7will not yield horizontal integration
  8. 8. Strategy• Strategy to avoid stovepipes requires a solution that is– Stable– Incrementally growing– Flexible in addressing new needs– Independent of source data syntax and semanticsThe answer: Semantic Enhancement (SE), astrategy of external (arm’s length) alignment
  9. 9. Distributed Common Ground System–Army (DCGS-A)SemanticEnhancement ofthe Dataspaceon the CloudDr. Tatiana MalyutaNew York City College of Technologyof the City University of New York
  10. 10. Dataspace on the CloudSalmen, et al,. Integration of Intelligence Datathrough Semantic Enhancement, STIDS 2011• strategy for developing an SE suite of orthogonalreference ontology modulesSmith, et al. Ontology for the Intelligence Analyst,CrossTalk: The Journal of Defense SoftwareEngineering November/December 2012,18-25.• Shows how SE approach provides immediatebenefits to the intelligence analyst
  11. 11. Dataspace on the Cloud• Cloud (Bigtable-like) store of heterogeneous data anddata semantics– Unified representation of structured and unstructureddata– Without loss and or distortion of data or data semantics• Homogeneous standardized presentation ofheterogeneous content via a suite of SE ontologiesHeterogeneous ContentsSE ontologiesUser
  12. 12. Dataspace on the Cloud• Cloud (Bigtable-like) store of heterogeneous data anddata semantics– Unified representation of structured and unstructureddata– Without loss and or distortion of data or data semantics• Homogeneous standardized presentation ofheterogeneous content via a suite of SE ontologiesHeterogeneous ContentsSE ontologiesUserIndex
  13. 13. Basis of the SE ApproachSE ontology labels• Focusing on the terms (labels, acronyms, codes) used in the sourcedata.• Where multiple distinct terms {t1, …, tn} are used in separate datasources with one and the same meaning, they are associated with asingle preferred label drawn from a standard set of such labels• All the separate data items associated with the {t1, … tn} therebylinked together through the corresponding preferred labels.• Preferred labels form basis for the ontologies we buildHeterogeneous ContentsABC KLMXYZ
  14. 14. SE Requirements to achieve HorizontalIntegration• The ontologies must be linked together throughlogical definitions to form a single, non-redundant and consistently evolving integratednetwork• The ontologies must be capable of evolving in anagile fashion in response to new sorts of dataand new analytical and warfighter needs  ourfocus here
  15. 15. Creating the SE Suite of Ontology Modules• Incremental distributed ontology development– based on Doctrine;– involves SMEs in label selection and definition• Ontology development rules and principles– A shared governance and change management process– A common ontology architecture incorporating a common,domain-neutral, upper-level ontology (BFO)• An ontology registry• A simple, repeatable process for ontology development• A process of intelligence data capture through‘annotation’ or ‘tagging’ of source data artifacts• Feedback between ontology authors and users
  16. 16. Intelligence Ontology SuiteNo. Ontology Prefix Ontology Full Name List of Terms1 AO Agent Ontology2 ARTO Artifact Ontology3 BFO Basic Formal Ontology4 EVO Event Ontology5 GEO Geospatial Feature Ontology6 IIAO Intelligence Information Artifact Ontology7 LOCO Location Reference Ontology8 TARGO Target OntologyHome Introduction PMESII-PT ASCOPE References LinksWelcome to the I2WD Ontology Suite!I2WD Ontology Suite: A web server aimed to facilitate ontology visualization, query, and development for the IntelligenceCommunity. I2WD Ontology Suite provides a user-friendly web interface for displaying the details and hierarchy of a specificontology term.16
  17. 17. Ontology Development Principles• Reference ontologies – capture generic contentand are designed for aggressive reuse inmultiple different types of context– Single inheritance– Single reference ontology for each domain ofinterest• Application ontologies – created by combininglocal content with generic content taken fromrelevant reference ontologies
  18. 18. Illustrationvehicle =def: an object used fortransporting people or goodstractor =def: a vehicle that is used fortowingcrane =def: a vehicle that is used forlifting and moving heavy objectsvehicle platform=def: means of providingmobility to a vehiclewheeled platform=def: a vehicleplatform that provides mobility throughthe use of wheelstracked platform=def: a vehicleplatform that provides mobility throughthe use of continuous tracksartillery vehicle = def. vehicle designed forthe transport of one or more artilleryweaponswheeled tractor = def. a tractor that has awheeled platformRussian wheeled tractor type T33 =def. a wheeled tractor of type T33manufactured in RussiaUkrainian wheeled tractor type T33= def. a wheeled tractor of type T33manufactured in UkraineReference Ontology Application Definitions
  19. 19. IllustrationVehicleTractorWheeledTractorArtilleryTractorWheeledArtilleryTractorArtilleryVehicleBlack –referenceontologiesRed –applicationontologies
  20. 20. Role of Reference Ontologies• Normalized (compare Ontoclean)– Allows us to maintain a set of consistent ontologies– Eliminates redundancy• Modular– A set of plug-and-play ontology modules– Enables distributed development• Surveyable– Common principles used, common training andgovernance
  21. 21. Examples of Principles• All terms in all ontologies should be singularnouns• Same relations between terms should be reusedin every ontology• Reference ontologies should be based on singleinheritance• All definitions should be of the forman S = Def. a G which Dswhere ‘G’ (for: species) is the parent term of S inthe corresponding reference ontology
  22. 22. SE Architecture• The Upper Level Ontology (ULO) in the SEhierarchy must be maximally general (no overlapwith domain ontologies)• The Mid-Level Ontologies (MLOs) introducesuccessively less general and more detailedrepresentations of types which arise insuccessively narrower domains until we reach theLowest Level Ontologies (LLOs).• The LLOs are maximally specific representation ofthe entities in a particular one-dimensionaldomain
  23. 23. Architecture Illustration
  24. 24. Intelligence Ontology SuiteNo. Ontology Prefix Ontology Full Name List of Terms1 AO Agent Ontology2 ARTO Artifact Ontology3 BFO Basic Formal Ontology4 EVO Event Ontology5 GEO Geospatial Feature Ontology6 IIAO Intelligence Information Artifact Ontology7 LOCO Location Reference Ontology8 TARGO Target OntologyHome Introduction PMESII-PT ASCOPE References LinksWelcome to the I2WD Ontology Suite!I2WD Ontology Suite: A web server aimed to facilitate ontology visualization, query, and development for the IntelligenceCommunity. I2WD Ontology Suite provides a user-friendly web interface for displaying the details and hierarchy of a specificontology term.24
  25. 25. Anatomy Ontology(FMA*, CARO)EnvironmentOntology(EnvO)InfectiousDiseaseOntology(IDO*)BiologicalProcessOntology (GO*)CellOntology(CL)CellularComponentOntology(FMA*, GO*) PhenotypicQualityOntology(PaTO)Subcellular Anatomy Ontology (SAO)Sequence Ontology(SO*) MolecularFunction(GO*)Protein Ontology(PRO*)Extension Strategy + Modular Organization 25top levelmid-leveldomainlevelInformation ArtifactOntology(IAO)Ontology forBiomedicalInvestigations(OBI)Spatial Ontology(BSPO)Basic Formal Ontology (BFO)
  26. 26. Shared Semantic Resource• Growing collection of shared ontologiesasserted and application• Pilot program to coordinate a small number ofdevelopment communities including both DSC(internal) and external groups to produce theirontologies according to the best practiceguidelines of the SE methodology
  27. 27. • Given the principles of building the SE (governance, distributedincremental development, common architecture) the next step is tocreate a semantic resource that can be shared by a larger community,and used for inter- and intra-integration on numerous systemsHeterogeneous ContentsShared Semantic ResourceDataspaceArmyNavyAirForce
  28. 28. 28
  29. 29. 29MI L I TARY OPERAT I ONS ONTOLOGY SUI T E
  30. 30. Anatomy Ontology(FMA*, CARO)EnvironmentOntology(EnvO)InfectiousDiseaseOntology(IDO*)BiologicalProcessOntology (GO*)CellOntology(CL)CellularComponentOntology(FMA*, GO*) PhenotypicQualityOntology(PaTO)Subcellular Anatomy Ontology (SAO)Sequence Ontology(SO*) MolecularFunction(GO*)Protein Ontology(PRO*)Extension Strategy + Modular Organization 30top levelmid-leveldomainlevelInformation ArtifactOntology(IAO)Ontology forBiomedicalInvestigations(OBI)Spatial Ontology(BSPO)Basic Formal Ontology (BFO)
  31. 31. continuantindependentcontinuantportion ofmaterialobjectfiat objectpartobjectaggregateobjectboundarysitedependentcontinuantgenericallydependentcontinuantinformationartifactspecificallydependentcontinuantqualityrealizableentityfunctionroledispositionspatialregion0D-region1D-region2D-region3D-regionBFO:continuant31
  32. 32. occurrentprocessualentityprocessfiat processpartprocessaggregateprocessboundaryprocessualcontextspatiotemporalregionscatteredspatiotemporalregionconnectedspatiotemporalregionspatiotemporalinstantspatiotemporalintervaltemporalregionscatteredtemporalregionconnectedtemporalregiontemporalinstanttemporalintervalBFO:occurrent32
  33. 33. Conclusion
  34. 34. Acknowledgements
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