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Towards Joint Doctrine for Military Informatics Towards Joint Doctrine for Military Informatics Presentation Transcript

  • Dr. Barry SmithDirectorNational Center for Ontological Researchhttp://x.co/qtYqTowards Joint Doctrine for MilitaryInformatics1
  • Barry Smith – who am I?Ontology work forNextGen (Next Generation) Air Transportation SystemNational Nuclear Security Administration, DoEJoint-Forces Command Joint Warfighting CenterArmy Net-Centric Data Strategy Center of ExcellenceArmy Intelligence and Information Warfare Directorate(I2WD)and for many national and international biomedicalresearch and healthcare agencies2
  • The problem of Big Data in biomedicine:Multiple kinds of data in multiple kinds of silosLab / pathology dataElectronic Health Record dataClinical trial dataPatient historiesMedical imagingMicroarray dataProtein chip dataFlow cytometryMass specGenotype / SNP dataeach lab, each hospital, each agency has its ownterminology for describing this data 3
  • How to find your data?How to reason with data when you find it?How to understand the significance of the datayou collected 3 years earlier?How to integrate with other people’s data?Part of the solution must involve consensus-based, standardized terminologies and codingschemes4
  • In the olden dayspeople measured lengths using inches, ulnas,perches, king’s feet, Swiss feet, leagues of Paris,etc., etc.5
  • On June 22, 1799, in Paris,everything changed6
  • International System of Units7
  • Making data (re-)usable throughstandard terminologies• Standards provide– common structure and terminology– single data source for review (less redundantdata)• Standards allow– use of common tools and techniques– common training– single validation of data8
  • Unifying goal: integration of biologicaland clinical data– within and across domains– across different species– across levels of granularity (organ,organism, cell, molecule)– across different perspectives (physical,biological, clinical)9
  • One successful part of the solution tothis problem = Ontologiescontrolled vocabularies (nomenclatures)plus definitions of terms in a logical language10
  • 11
  • 12types vs. instances
  • 13names of instances
  • 14names of types
  • Ontologies• are computer-tractable representations oftypes in specific areas of reality• are more and less general (upper and lowerontologies)– upper = organizing ontologies– lower = domain ontologies15
  • FMAPleuralCavityInterlobarrecessMesotheliumof PleuraPleura(Wallof Sac)VisceralPleuraPleural SacParietalPleuraAnatomical SpaceOrganCavitySerous SacCavityAnatomicalStructureOrganSerous SacMediastinalPleuraTissueOrgan PartOrganSubdivisionOrganComponentOrgan CavitySubdivisionSerous SacCavitySubdivisionFoundational Model of Anatomy16
  • 17ontologies = standardized labelsdesigned for use in annotationsto make the data cognitivelyaccessible to human beingsand algorithmically accessibleto computers
  • by allowing grouping of annotationsbrain 20hindbrain 15rhombomere 10Query brain without ontology 20Query brain with ontology 4518Ontologies facilitate retrieval of data
  • 19ontologies = high quality controlledstructured vocabularies used for theannotation (description, tagging) ofdata, images, emails, documents, …
  • The problem of retrieval, integrationand analysis of siloed data• is not confined to biomedicine• affects every domain due to massive legacy ofnon-interoperable data models and datasystems• and as new systems are created along thesame lines, the situation is constantly gettingworse.20
  • The problem: many, many silos• DoD spends more than $6B annually developing aportfolio of more than 2,000 business systemsand Web services• these systems are poorly integrated• deliver redundant capabilities,• make data hard to access, foster error and waste• prevent secondary uses of datahttps://ditpr.dod.mil/ Based on FY11 Defense Information TechnologyRepository (DITPR) data21
  • Some questions• How to find data?• How to understand data when you find it?• How to use data when you find it?• How to compare and integrate with other data?• How to avoid data silos?22
  • Favored solution: Über-model (NIEM,JC3IEDM …)– must be built en bloc beforehand– inflexible, unresponsive to warfighter needs– heavy-duty manual effort for both constructionand ingestion, with loss and/or distortion ofsource data and data-semantics– might help with data retrieval and integration– but offers limited analytic capability– has a limited lifespan because it rests on one pointof view23
  • NIEM National Information ExchangeModel24nc:VehicleBrandnc:VehicleBrandCodenc:VehicleBrandDatenc:VehicleBrandDesignationnc:VehicleInspectionJurisdictionAuthoritync:VehicleInspectionJurisdictionAuthorityTextnc:VehicleInspectionSafetyPassIndicatornc:VehicleInspectionSmogCertificateCodenc:VehicleInspectionStationIdentificationnc:VehicleInspectionTestCategoryTextnc:VehicleMotorCarrierIdentificationnc:VehicleOdometerReadingMeasurenc:VehicleOdometerReadingUnitCode
  • Über-Model Labels• Region.water.distanceBetweenLatrinesAndWaterSource• Region.water.fecalOrOralTransmittedDiseases– How are these labels used?– No way to standardize or horizontally integrate– Trying to pack too much into each label– Contain elements from several asserted ontologies– Need to be Decomposed into elements– Relating elements from different asserted ontologies– Common events and objects in an Area of Operations25
  • A better solution, begins with the Web(net-centricity)• You build a site• Others discover the site and they link to it• The more they link, the more well known thepage becomes (Google …)• Your data becomes discoverable26
  • 1. Each group creates a controlled vocabulary ofthe terms commonly used in its domain, andcreates an ontology out of these terms usingOWL syntax4. Binds this ontology to its data and makes thesedata available on the Web5. The ontologies are linked e.g. through their useof some common terms6. These links create links among all the datasets,thereby creating a „web of data‟7. We can all share the same tags – they arecalled internet addressesThe roots of Semantic Technology
  • Where we stand today• increasing availability of semantically enhanceddata and semantic software• increasing use of OWL (Web Ontology Language)in attempts to create useful integration of on-linedata and information• “Linked Open Data” the New Big Thing28
  • as of September 2010 29
  • The problem: the more SemanticTechnology is successful, they more it failsThe original idea was to break down silos viacommon controlled vocabularies for the taggingof dataThe very success of the approach leads to thecreation of ever new controlled vocabularies –semantic silos – as ever more ontologies arecreated in ad hoc waysEvery organization and sub-organization nowwants to have its own “ontology”The Semantic Web framework as currentlyconceived and governed by the W3C yieldsminimal standardization30
  • Divided we fail31
  • United we also fail32
  • 33The problem of joint / coalition operationsFireSupportLogisticsAir OperationsIntelligenceCivil-MilitaryOperationsTargetingManeuver&BlueForceTracking
  • Towards ontology coordination34
  • An alternative solution:Semantic EnhancementA distributed incremental strategy of coordinatedannotation– data remain in their original state (is treated at ‘arms length’)– ‘tagged’ using interoperable ontologies created in tandem– allows flexible response to new needs, adjustable in realtime– can be as complete as needed, lossless, long-lasting becauseflexible and responsive– big bang for buck – measurable benefit even from first smallinvestmentsThe strategy works only to the degree that it rests onshared governance and training35
  • compare: legends for mapscompare: legends for maps36
  • compare: legends for mapscommon legends allow (cross-border) integration37
  • The Gene OntologyMouseEcotope GlyProtDiabetInGeneGluChemsphingolipidtransporteractivity38
  • The Gene OntologyMouseEcotope GlyProtDiabetInGeneGluChemHolliday junctionhelicase complex39
  • The Gene OntologyMouseEcotope GlyProtDiabetInGeneGluChemsphingolipidtransporteractivity40
  • Common legends• help human beings use and understand complexrepresentations of reality• help human beings create useful complexrepresentations of reality• help computers process complexrepresentations of reality• help glue data togetherBut common legends serve these purposesonly if the legends are developed in acoordinated, non-redundant fashion41
  • International System of Units42
  • RELATIONTO TIMEGRANULARITYCONTINUANT OCCURRENTINDEPENDENT DEPENDENTORGAN ANDORGANISMOrganism(NCBITaxonomy)AnatomicalEntity(FMA,CARO)OrganFunction(FMP, CPRO) PhenotypicQuality(PaTO)BiologicalProcess(GO)CELL ANDCELLULARCOMPONENTCell(CL)CellularComponent(FMA, GO)CellularFunction(GO)MOLECULEMolecule(ChEBI, SO,RnaO, PrO)Molecular Function(GO)Molecular Process(GO)The Open Biomedical Ontologies (OBO) Foundry43
  • CONTINUANT OCCURRENTINDEPENDENT DEPENDENTORGAN ANDORGANISMOrganism(NCBITaxonomy)AnatomicalEntity(FMA,CARO)OrganFunction(FMP, CPRO) PhenotypicQuality(PaTO)Organism-LevelProcess(GO)CELL ANDCELLULARCOMPONENTCell(CL)CellularComponent(FMA, GO)CellularFunction(GO)Cellular Process(GO)MOLECULEMolecule(ChEBI, SO,RNAO, PRO)Molecular Function(GO)MolecularProcess(GO)rationale of OBO Foundry coverageGRANULARITYRELATION TOTIME44
  • RELATIONTO TIMEGRANULARITYCONTINUANT OCCURRENTINDEPENDENT DEPENDENTCOMPLEX OFORGANISMSFamily, Community,Deme, PopulationOrganFunction(FMP, CPRO)PopulationPhenotypePopulationProcessORGAN ANDORGANISMOrganism(NCBITaxonomy)AnatomicalEntity(FMA,CARO) PhenotypicQuality(PaTO)BiologicalProcess(GO)CELL ANDCELLULARCOMPONENTCell(CL)CellularComponent(FMA, GO)CellularFunction(GO)MOLECULEMolecule(ChEBI, SO,RnaO, PrO)Molecular Function(GO)Molecular Process(GO)Population-level ontologies 45
  • RELATIONTO TIMEGRANULARITYCONTINUANT OCCURRENTINDEPENDENT DEPENDENTORGAN ANDORGANISMOrganism(NCBITaxonomy)AnatomicalEntity(FMA,CARO)OrganFunction(FMP, CPRO)PhenotypicQuality(PaTO)BiologicalProcess(GO)CELL ANDCELLULARCOMPONENTCell(CL)CellularComponent(FMA, GO)CellularFunction(GO)MOLECULEMolecule(ChEBI, SO,RnaO, PrO)Molecular Function(GO)Molecular Process(GO)Environment Ontologyenvironments46
  • What can semantic technology dofor you?• software, hardware, business processes, target domainsof interest change rapidly• but meanings of common words change only slowly• semantic technology allows these meanings to beencoded separately from data files and from applicationcode – decoupling of semantics from data andapplications• ontologies (controlled, logically structured, vocabularies),which are used to enhance legacy and source content− to make these contents retrievable even by those notinvolved in their creation− to support integration of data deriving from heterogeneoussources47
  • Creation of new ontology consortia,modeled on the OBO Foundry48NIF Standard Neuroscience InformationFrameworkeagle-IOntologiesused by VIVO and CTSAconnect for publications,patents, credentials, data andsample collectionsIDO Consortium Infectious Disease OntologycROP Common ReferenceOntologies for Plants
  • RELATIONTO TIMEGRANULARITYCONTINUANT OCCURRENTINDEPENDENT DEPENDENTORGAN ANDORGANISMOrganism(NCBITaxonomy)AnatomicalEntity(FMA,CARO)OrganFunction(FMP, CPRO) PhenotypicQuality(PaTO)BiologicalProcess(GO)CELL ANDCELLULARCOMPONENTCell(CL)CellularComponent(FMA, GO)CellularFunction(GO)MOLECULEMolecule(ChEBI, SO,RnaO, PrO)Molecular Function(GO)Molecular Process(GO)what is the analogue of this in the military domain?49
  • 50
  • The SE solution: Ontology (only) at the I2WD center• Establish common ontology content, which we andour collaborators (and our software) control• Keep this content consistent and non-redundant as itevolves.• Seek semantic sharing only in the SE environment.– so what SE brings is semantic interoperability plusconstrained syntax– it brings a kind of substitute for semanticinteroperability of source data models, throughthe use by annotators of ontologies from thesingle evolving SE suite51
  • Distributed Common Ground System – Army(DCGS-A)Semantic Enhancementof the Dataspaceon the CloudDr. Tatiana MalyutaNew York City College of Technologyof the City University of New York
  • Integrated Store of Intelligence Data• Lossless integration without heavy pre-processing• Ability to:– Incorporate multiple integration models / approaches /points of view of data and data-semantics– Perform continuous semantic enrichment of the integratedstore• Scalability53
  • Solution Components• Cloud implementation– Cloudbase (Accumulo)• Data Representation and Integration Framework– Comprehensive unified representation of data, datasemantics, and metadata• This work funded by US Army CERDECIntelligence and Information Warfare Directorate(I2WD)• Current pilot project to extend experimentally toother services/agencies54
  • Dealing with Semantic HeterogeneityÜber-Model =Physical Integration.A separate data storehomogenizingsemantics in aparticular data-model– works only forspecial cases, entailsloss and distortion ofdata and semantics,creates a new datasilo.Virtual integration.A projection onto ahomogeneous data-model exposed tousers – is moreflexible, but may havethe problem of dataavailability (e.g.military, intelligence).Also, a particularhomogeneous modelhas limited usage,does not expose allcontent, and does notsupport enrichment55
  • Ontology vs. Data Model• Each ontology provides a comprehensive synoptic view of adomain as opposed to the flat and partial representationprovided by a data modelComputerSkillSingle Ontology Multiple Data modelsPersonPersonPersonNameFirstNameLastNamePersonSkillPersonName NetworkSkill ProgrammingSkillIs-a Bearer-ofSkillLast Name First Name SkillPerson Name Computer SkillProgrammingSkillNetworkSkillSkill56
  • Sources• Source database Db1, with tables Person and Skill, containingperson data and data pertaining to skills of different kinds,respectively.• Source database Db2, with the table Person, containing dataabout IT personnel and their skills:• Source database Db3, with the table ProgrSkill, containing dataabout programmers’ skills:PersonID SkillID111 222SkillID Name Description222 Java ProgrammingID SkillDescr333 SQLEmplID SkillName444 Java57
  • Benefits of the approach• We can see how much manual effort the analystneeds to apply in performing search without SE– and even then the information he will gain willbe meager in comparison with what is madeavailable through the Index with SE.–For example, if an analyst is familiar with the labelsused in Db1 and is thus in a position to enter Name= Java, his query will still return only: person 111.Directly salient Db4 information will thus be missed.58
  • Towards Globalization and Sharing• Using the SE approachto create a SharedSemantic Resource forthe IntelligenceCommunity to enableinteroperability acrosssystems• Applying it directly to orprojecting its contentson a particularintegration solution59
  • Building the Shared Semantic Resource• Methodology of distributed incrementaldevelopment• Training• Governance• Common Architecture of Ontologies to supportconsistency, non-redundancy, modularity– Upper Level Ontology (BFO)– Mid-Level Ontologies– Low Level Ontologies60
  • Governance• Common governance– coordinating editors, one from each ontology, responsiblefor managing changes and ensuring use of common bestpractices– small high-level board to manage interoperability• How much can we embed governance into software?• How much can we embed governance into training?– analogy with military doctrine• Question: Can military doctrine help to bring about theneeded ontology coordination61
  • Governance principles1. All ontologies are expressed in a common shared syntax (initially OWL2.0; perhaps later supplemented by CLIF) (Syntax for annotationsneeds to be fixed later; potentially RDF.)2. Each ontology possesses a unique identifier space (namespace) andeach term has a unique ID ending with an alphanumeric string of theform GO:00001234563. Each ontology has a unique responsible authority (a human being)4. If ontologies import segments from other ontologies then importedterms should preserve the original term ID (URI).5. Versioning: The ontology uses procedures for identifying distinctsuccessive versions (via URIs).6. Each ontology must be created through a process of downwardpopulation from existing higher-level ontologies to ensure a commonarchitecture62
  • Governance principles7. Each ontology extends from BFO 2.08. Each lower-level ontology is orthogonal to the other ontologies atthe same level within the ontology hierarchy9. The ontologies include textual (human readable) and logicaldefinitions for all terms.10. The ontology uses relations which are unambiguously definedfollowing the pattern of definitions laid down in the RelationOntology that is incorporated into BFO 2.011. Each ontology is developed collaboratively, so that in areas ofoverlap between neighboring ontologies authors will settle on adivision of terms.12. Ontologies are divided between asserted and inferred – the formerare stable reference ontologies; the latter are combinations ofontology fragments designed for specific local needs.63
  • Orthogonality• For each domain, ensure convergence upon a singleontology recommended for use by those who wish tobecome involved with the initiative• Thereby: avoid the need for mappings – which are in tooexpensive, too fragile, too difficult to keep up-to-date asmapped ontologies change• Orthogonality means:– everyone knows where to look to find out how toannotate each kind of data– everyone knows where to look to find content forapplication ontologies64
  • Ontology traffic rule for Definitions all definitions should be of the genus-speciesformA =def. a B which Cswhere B is the parent term of A in the ontologyhierarchy65
  • Ontologies are built as orthogonalmodules which form an incrementallyevolving network• scientists are motivated to commit todeveloping ontologies because they will need intheir own work ontologies that fit into thisnetwork• users are motivated by the assurance that theontologies they turn to are maintained byexperts66
  • More benefits of orthogonality• helps those new to ontology to find what theyneed• to find models of good practice• ensures mutual consistency of ontologies(trivially)• and thereby ensures additivity of annotations67
  • More benefits of orthogonality• No need to reinvent the wheel for each newdomain• Can profit from storehouse of lessons learned• Can more easily reuse what is made by others• Can more easily reuse training• Can more easily inspect and criticize results ofothers’ work• Leads to innovations (e.g. Mireot, Ontofox) instrategies for combining ontologies68
  • Continuant OccurrentIndependentContinuantDependentContinuantcell componentbiological processmolecular functionBasic Formal Ontology69
  • 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 70top levelmid-leveldomainlevelInformation ArtifactOntology(IAO)Ontology forBiomedicalInvestigations(OBI)Spatial Ontology(BSPO)Basic Formal Ontology (BFO)
  • continuantindependentcontinuantportion ofmaterialobjectfiat objectpartobjectaggregateobjectboundarysitedependentcontinuantgenericallydependentcontinuantinformationartifactspecificallydependentcontinuantqualityrealizableentityfunctionroledispositionspatialregion0D-region1D-region2D-region3D-regionBFO:continuant71
  • occurrentprocessualentityprocessfiat processpartprocessaggregateprocessboundaryprocessualcontextspatiotemporalregionscatteredspatiotemporalregionconnectedspatiotemporalregionspatiotemporalinstantspatiotemporalintervaltemporalregionscatteredtemporalregionconnectedtemporalregiontemporalinstanttemporalintervalBFO:occurrent72
  • More than 100 Ontologyprojects using BFOhttp://www.ifomis.org/bfo/users
  • Basic Formal OntologyContinuant Occurrentprocess, eventIndependentContinuantthingDependentContinuantquality.... ..... .......typesinstances
  • Blinding Flash of the ObviousContinuant Occurrentprocess, eventIndependentContinuantthingDependentContinuantquality.... ..... .......quality dependson bearer
  • Blinding Flash of the ObviousContinuant Occurrentprocess, eventIndependentContinuantthingDependentContinuantquality, ….... ..... .......event dependson participant
  • Occurrents depend on participantsinstances15 May bombing5 April insurgency attackoccurrent typesbombingattackparticipant typesexplosive deviceterrorist group
  • Roles pertain not to what a thing enduringly is,but to the part it plays, e.g. in some operationContinuantOccurrentprocess, eventIndependentContinuantthingDependentContinuantrole.... ..... .......process is changein quality
  • General lessons for ontology successincorporated into BFOCommon traffic lawsLessons learned and disseminated ascommon guidelines – all developers aredoing it the same wayOntologies built by domain experts
  • Universality (low hanging fruit)Start with simple assertions which youknow to be universally truehand part_of bodycell death is_a deathpneumococcal bacterium is_a bacterium(Computers need to be led by the hand)
  • Need to manage ontologychange• how to ensure that resources invested inan ontology now do not lose their valuewhen the ontology changes• through explicit versioning, and agovernance structure for changemanagement to ensure evolution intandem of ontologies within the networkedontology structure)
  • Experience with BFO inbuilding ontologies providesa community of skilled ontology developers andusersassociated logical toolsdocumentation for different types of usersa methodology for building conformantontologies by starting with BFO and populatingdownwards
  • ConclusionOntologists have established bestpractices– for building ontologies– for linking ontologies– for evaluating ontologies– for applying ontologieswhich have been thoroughly tested in useand which conform precisely to the extensionstrategy from a single upper level
  • with thanks to LCL Dr. Bill MandrickSenior OntologistData Tacticshttp://militaryontology.orgA Strategy for Military Ontology84
  • Agenda• Introductory Remarks• Previous Information Revolution• Ontology & Military Symbology• Asserted Ontologies• Inferencing• Realizing the strategy85
  • 86Orders of Reality1st order. Reality as it is. In the actionin the upper image to the right, realityis what is, not what we think ishappening2nd Order. Participant Perceptions.What we believe is happening as wepeer through the fog of war.3rd Order. Reality as we record it. Inreports, databases, ontologies. …The gaps between the orders of reality introduce risk. These gaps are not the onlyform of risk but reducing these gaps contributes to reducing risk.86
  • 87Examples of Conflation of the 3 Orders
  • 88Warfighters’ Information Sharing EnvironmentFireSupportLogisticsAir OperationsIntelligenceCivil-MilitaryOperationsTargetingManeuver&BlueForceTracking
  • Merriam-Webster’s CollegiateDictionaryJoint Publication 1-02 DoD Dictionaryof Military and Related TermsJoint Publication 3-0 Joint OperationsJoint Publication 3-13 Joint Commandand ControlJoint Publication 3-24CounterinsurgencyJoint Publication 3-57 Civil-MilitaryOperationsJP 3-10, Joint Security Operations inTheaterJoint Publication 3-16 MultinationalOperationsJoint Publication 5-0 Joint OperationsPlanningAuthoritative Referenceshttp://www.dtic.mil/doctrine/Warfighter LexiconControlled VocabularyStableHorizontally IntegratedCommon Operational Picture89
  • 90Ontology(ies) that enables interoperability among members of an Operations Centerand other warfighters.
  • 91JP 3-0OperationsJP 2-0IntelligenceJP 6-0CommSupportJP 4-0LogisticsJP 3-16MultinationalOperationsJP 3-33JTFHeadquartersJP 1-02DoD DictionaryCivil-Military OperationsArea of Operations XXX XArea of Responsibility XXXXXC2 Systems XXX XDoctrinal PublicationsConsistent Terminology (Data Elements, Names and Definitions)Area of Interest X XXKey: word for word
  • Previous Information Revolution92
  • Previous Information Revolution• 1800 Cartographic Revolution• Explosion of production, dissemination and useof cartography• Revolutionary and Napoleonic wars• Several individual armies in the extended terrain• New spatial order of warfare• Urgent need for new methods of spatialmanagement…**SOURCE: PAPER EMPIRES: MILITARY CARTOGRAPHY AND THE MANAGEMENT OF SPACE93
  • Standardizing Geospatial InformationTriangulationMilitary Grid Reference SystemLatitude Longitude 94
  • Interoperable Semantics(example: Anatomy & Physiology)• Standardized Labels• Anatomical Continuants• Physiological Occurrents• Teachable• Inferencing• Horizontally Integrated• Sharing of Observations• Accumulated Knowledge95
  • Standardized Symbols96GroundResistorCapacitor
  • Ontology & Military Symbology• Elements of Military Ontology• Represent Entities and Events found in militarydomains• Used to develop the Common OperationalPicture• Used to develop Situational Awareness• Used to develop Situational Understanding• Used for Operational Design• Used to Task Organize Forces• Used to Design/Create Information Networks• Enhance the Military Decision Making Process97
  • Military SymbologySample of Military Standard 2525 Military Symbology98
  • Map Overlays99
  • Task OrganizingOntological methods are used in the process ofTask-OrganizingA Task-Organization is the Output (Product) ofTask OrganizingA Task-Organization is a Plan or part of a PlanA Plan is an Information Content EntityTask-Organizing — The act of designing an operatingforce, support staff, or logistic package of specific sizeand composition to meet a unique task or mission.Characteristics to examine when task-organizing theforce include, but are not limited to: training,experience, equipage, sustainability, operatingenvironment, enemy threat, and mobility. (JP 3-05)100
  • Operational DesignSource: FM 3-0 OperationsMilitary Ontologies help planners and operators “see” andunderstand the relations between Entities and Events in thearea of operations.Military Ontologies are prerequisites of military innovationssuch as Airborne Operations, Combined Fires and JointOperations.Military Ontologies are prerequisites for the creation of effectiveinformation systems.Operational Design — The conception and construction of theframework that underpins a campaign or major operation planand its subsequent execution. See also campaign; majoroperation. (JP 3-0)101
  • Asserted (Reference) Ontologies• Generic Content• Aggressive Reuse• Multiple Different Types of Context• Better Definitions• Prerequisite for InferencingTarget ListTargetNominationListCandidateTarget ListHigh-PayoffTarget ListProtectedTarget ListIntelligenceProductGeospatialIntelligenceProductTargetIntelligenceProductSignalsIntelligenceProductHumanIntelligenceProduct 102
  • 103
  • Grids &Coordinates104
  • Information Artifacts105
  • Information Artifacts106
  • Geospatial Feature Descriptions107
  • Geographic Features& Geospatial Regions108
  • Geospatial Regions*CombineGeographic/Geospatialcontent from otherontology (see next slide)109
  • Artifacts110
  • Facilities111
  • Facility by Role112
  • continuantindependentcontinuantportion ofmaterialobjectfiat objectpartobjectaggregateobjectboundarysitedependentcontinuantgenericallydependentcontinuantinformationartifactspecificallydependentcontinuantqualityrealizableentityfunctionroledispositionspatialregion0D-region1D-region2D-region3D-regionBFO:continuant113
  • occurrentprocessualentityprocessfiat processpartprocessaggregateprocessboundaryprocessualcontextspatiotemporalregionscatteredspatiotemporalregionconnectedspatiotemporalregionspatiotemporalinstantspatiotemporalintervaltemporalregionscatteredtemporalregionconnectedtemporalregiontemporalinstanttemporalintervalBFO:occurrent114
  • Vehicles115
  • Weapons116
  • Human Ontologies117
  • Organizations118
  • Processes119
  • Infantry Company is part_of a Battalion (Continuant to Continuant)Civil Affairs Team participates_in a Civil Reconnaissance(Continuant to Occurrent)Military Engagement is part_of a Battle Event (Occurrent toOccurrent)House is a Building (Universal to Universal)3rd Platoon, Alpha Company participates_in Combat Operations(Instance to Universal)3rd Platoon, Alpha Company is located_at Forward Operating BaseWarhorse (Instance to Instance)Relations: How Data becomes Information120
  • Standardized Relations121
  • Über-Model Labels• Region.water.distanceBetweenLatrinesAndWaterSource• Region.water.fecalOrOralTransmittedDiseases– How are these labels used?– No way to standardize or horizontally integrate– Trying to pack too much into each label– Contain elements from several asserted ontologies– Need to be Decomposed into elements– Relating elements from different asserted ontologies– Common events and objects in an Area of Operations122
  • Asserted OntologiesRegion.water.distanceBetweenLatrinesAndWaterSourceTribalRegionArea OfOperationsGeospatialRegionVillageWater SourceLatrineWellPondCesspoolAct OfMeasurementAct OfAnalysisAct OfObservationActMeasurement ResultDepthMeasurementResultHeightMeasurement ResultDistanceMeasurement ResultGeographicCoordinatesLatitudeLongitudeCoordinatesMilitary GridReference SystemCoordinatesUniversalTransverseMercatorCoordinates123
  • locatedinhasroleRegion.water.fecalOrOralTransmittedDiseasesWellVillageAssessmentBacterialPathogenRoleParticularBacterialPathogenRoleCollectionofBacteriumCholeraEpidemicCholeracause_ofcause_ofinstance_ofinstance_of instance_ofReportDate TimeGroup150029OCT2010stampsinstance_ofdescribesinstance_of
  • Relating Asserted OntologiesRegion.water.fecalOrOralTransmittedDiseasesVirusProtozoanMicroorganismBacteriumWater SourceLatrineWellPondCesspoolPathogenRoleConsumableRoleMedicinalRoleRoleDiseaseHepatitis AShigellosisCholeraEventContaminationEventEpidemic EventDiseaseTransmissionEventhas_rolehas_locationpart_ofcause_of125
  • locatednearUnpacking: Region.water.distanceBetweenLatrinesAndWaterSourceLatrineWell‘VT 334 569’DistanceMeasurementResultVillageName‘KhanabadVillage’Villageis_ainstance_ofGeopoliticalEntitySpatialRegionGeographicCoordinatesSetdesignatesinstance_oflocatedininstance_ofhaslocation designateshaslocationinstance_ofinstance_of’16 meters’instance_ofmeasurement_of
  • 127
  • Conclusions• Situational Understanding• Shared Lexicon• Horizontal Integration of Preferred Labels• Need Training & Governance128
  • Barry Smith&Bill MandrickRealizing the Strategy:A Practical Introduction toOntology Building129
  • Agenda• Standardized Processes• Scoping the Domain• Creating Initial Lexicon• Initial Ontology• Feedback and Iteration• Publish and Share130
  • 131
  • Guide to aRepeatable ProcessforOntology Creation (v 0.1)132
  • Scope the Domain• 1.1 Subject Matter Expert (SME) Interaction• 1.2 Identify Authoritative References• 1.3 Survey Authoritative References• 1.4 Define the Domain• 1.5 Describe the Domain• 1.6 Devise Metrics133
  • Merriam-Webster’s CollegiateDictionaryJoint Publication 1-02 DoD Dictionaryof Military and Related TermsJoint Publication 3-0 Joint OperationsJoint Publication 3-13 Joint Commandand ControlJoint Publication 3-24CounterinsurgencyJoint Publication 3-57 Civil-MilitaryOperationsJP 3-10, Joint Security Operations inTheaterJoint Publication 3-16 MultinationalOperationsJoint Publication 5-0 Joint OperationsPlanningAuthoritative Referenceshttp://www.dtic.mil/doctrine/ 134
  • 135
  • DefinitionsAttack Geography:A description of the geography surrounding the IEDincident, such as road segment, buildings, foliage,etc. Understanding the geography indicates enemyuse of landscape to channel tactical response, slowfriendly movement, and prevent pursuit of enemyforces.IED Attack Geography:A Geospatial Region where some IED Incident takesplace.IED Attack Geography Description:A Description of the physical features of someGeospatial Region where an IED Incident takesplace.Original “Definition” Improved Definition(s)136
  • Method of Emplacement:A description of where the device was delivered, used, oremployed. (original definition)Original “Definition” Improved Definition(s)Method of IED Emplacement:A systematic procedure used in the positioning of anImprovised Explosive Device.Method of IED Emplacement Description:A description of the systematic procedure used in thepositioning of an Improvised Explosive Device.Example 2: Method of Emplacement137
  • Example 3: Method of EmploymentMethod of Employment:A description of where the device was delivered, used, oremployed. (original definition)Original “Definition” Improved Definition(s)Method of IED Employment:A systematic procedure used in the delivery of anImprovised Explosive Device.Method of IED Employment Description:A description of the systematic procedure used in thedelivery of an Improvised Explosive Device.138
  • Doctrinal Definitionsintelligence estimate — The appraisal, expressed inwriting or orally, of available intelligence relating to aspecific situation or condition with a view to determiningthe courses of action open to the enemy or adversaryand the order of probability of their adoption. (JP 2-0)139
  • 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.140
  • I2WD Ontology Suite141
  • A simple example of how ontologiescan help142
  • 143Logically Inconsistent Terms in CJCSI4410.01E, “Standardized Terminology forAircraft Inventory Management”Peter Morosoff e-MapsDecember 12, 2012Ontology-100 Aircraft Inventory Terms.ppt
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  • 146Diagram of Terms Extracted from CJCSI 4410.01ENote that the diagram shows two major child or sub categories: total activeinventory (TAI) and total inactive inventory (TII). Note also that TII has eightsubcategories, of which foreign military sales is represented as one among equals.
  • 147Foreign military sales aircraft. Aircraft and UA instorage, bailment, used as government-furnished property,on loan or lease outside the Defense establishment, orotherwise not available to the Military Services; includesaircraft for the purpose of sale to foreign governments.(Source: DOD 5105.36-M.)Bailment aircraft.Aircraft and UAfurnished to andunder the physicalcustody of anongovernmentalorganizationpursuant to therequirements of agovernment contract.Lease aircraft.Military aircraftand UA providedto agencies andorganizationsoutside thefederalgovernment on atemporary basis.Loan aircraft.Military aircraftand UAprovided toother federalgovernmentdepartmentsand agencieson atemporarybasis.Storageaircraft.Aircraft and UAremoved fromthe activeinventory andheld for parts,disposal, or in apreservedcondition.“Aircraftfor thepurpose ofsale toforeigngovern-ments”Terms Extracted from CJCSI 4410.01EThe category foreign military sales aircraft is defined, however, as having six subcategories.Three of the six categories in the lower boxes (i.e., bailment, lease, and loan aircraft) arealso represented in the chart on the previous slide as being mutually exclusive from foreignmilitary sales. Such categorization impedes machine inference and creates a situation whichwill record some bailment aircraft under “foreign military sales aircraft.”“Aircraftnototherwiseavailable”
  • 148Thoughts Prompted by Ontological Concepts1. Someone who understands logic needs to work with theoversight office for CJCI 4410.01E to develop a betterstructure of categories..2. How should we represent that a UH-1 helicopter isowned by the Navy and being used for training so thatwe facilitate machine inference about the helicopter?3. The essential characteristics of UH-1 helicopter is amember of that category is (a) a vehicle intended to flythat (b) is kept aloft by rotating blades. Their accidentalroles include the Service that owns them, their use intraining, and them membership in the “primary trainingaircraft inventory.”
  • 149Bottom Line1. The people who drafted and approved CJCSI4410.01E probably did the best they could withthe categorization concepts and methodsavailable to them. Clearly, however, theirproduct, while suitable for use by people, doesnot support development of IT that maximizesthe potential of IT to share data and informationand to inference.2. DoD needs to exploit the concepts andmethods of ontology if its informationtechnology (IT) is to maximize efficiency andoperational effectiveness.
  • 150Do we need joint doctrine formilitary informatics?1. To support joint operations2. To do justice to the increasing role ofinformatics systems in militaryoperations3. To ensure consistent procurement4. To promote utility of software to thewarfighter
  • Examples of military innovations151Artillery massing fires in WWINote that at the beginning of the 20th Century the US Army hadthe technical means and capabilities to employe indirect fieldartillery fires on the battlefield. It was, however, not until 1939that the field manual on the employment of indirect field artilleryfires was published. I have attached some quotes on the Armysslow start of effective indirect field artillery fires.Dowding in WWIIRadar stations were, in isolation, sitting ducks for Luftwaffe.Through a C2 terrain model and common lexicon he created anetwork to watch over all of them, and over the airbases andequipment they helped to defendPatraeus in IRAQPetreaus FM 3-24 "Counterinsurgency" Doctrine turned thingsaround in Iraq
  • Question (From P. Morosoff)152Should we wait before commiting militaryinformatics into Doctrine?The massing artillery fires example shows thatcreating a first-class military capability fromtechnology often waits decades until thedoctrinal publications are produced.Capability created in Ft Sill around 1906Capability committed to Doctrine in 1939
  • The capability for massing timely andaccurate artillery fires by dispersedbatteries upon single targets required• real-time communications of a sort that could– create a common operational picture that could take accountof new developments in the field– thereby transforming dispersed batteries into a single systemof interoperable modules.• this was achieved through– a new type of information support (better maps, timekeeping)– a new type of governance and training– new artillery doctrine153/24
  • The capability for massing timely andaccurate intelligence “fires”will similarly require real-time pooling of information of asort that can– create a common operational picture able to be constantlyupdated in light of new developments in the field– thereby transforming dispersed data artifacts within theCloud into a single system of interoperable modulesThis will require in turn– a new type of support (for semantic enhancement of data)– a new type of governance and training– new intelligence doctrine to include applied semantics154/24
  • Why is doctrine needed• WIKI• DOTLMPF• http://en.wikipedia.org/wiki/DOTMLPF155
  • DOTLMPF156The Joint Capabilities Integration Development System providesa solution space that considers solutions involving anycombination ofDoctrineOrganizationTrainingMaterielLeadershipPersonnelFacilitiesDOTLMPF also serves as a mnemonic for staff planners toconsider certain issues prior to undertaking a new effort.
  • How is DOTMLPF interpreted?157Doctrine: the way we fight, e.g., emphasizing maneuver warfarecombined air-ground campaigns.Organization: how we organize to fight; divisions, air wings, Marine-AirGround Task Forces (MAGTFs), etc.Training: how we prepare to fight tactically; basic training to advancedindividual training, various types of unit training, joint exercises, etc.Materiel: all the “stuff” necessary to equip our forces, that is, weapons,spares, etc. so they can operate effectively.Leadership and education: how we prepare our leaders to lead the fightfrom squad leader to 4-star general/admiral; professional development.Personnel: availability of qualified people for peacetime, wartime, andvarious contingency operationsFacilities: real property; installations and industrial facilities (e.g.government owned ammunition production facilities) that support ourforces.
  • How can DOTMLPF be applied tomilitary informatics?158Doctrine: how does software contribute to the way we fight, e.g., incombined air-ground campaigns.Organization: how are informatics personnel organized in relation tomilitary units?Training: how are informatics personnel trained?Materiel: all the “stuff” necessary to equip our forces, that is, weapons,spares, etc. so they can operate effectively.Leadership and education: how we prepare our leaders to lead the fightfrom squad leader to 4-star general/admiral; professional development.Personnel: availability of qualified people for peacetime, wartime, andvarious contingency operationsFacilities: real property; installations and industrial facilities (e.g.government owned ammunition production facilities) that support ourforces.
  • Ideas towards Joint Doctrine forMilitary Informatics159Joint Doctrine contains the controlled vocabulary,lexicon, and nomenclature for• Equipment (Vehicles, Weapons, Target Roles, etc...)• Events (Operations, Planning Events, TargetingEvents, Intelligence Events – e.g. IntelligencePreparation of the Battlespace –, etc.• Military Units/OrganizationsWhat is needed is the same type of standardization forInformation Artifacts (Reports, Assessments, Estimates,Target Lists, Matrices, Templates, Images, Maps, etc.)
  • Doctrine for informatics (from P. Morosoff)160• Doctrine is one of DoDs primary tools for creating a militarycapability from equipment – including software, computernetworks, and servers.• To what extent were Navy capabilities created from newequipment?• The development of new equipment does not guarantee a newcapability.• From my Marine Corps experience, I am familiar with the role ofdoctrine in creating amphibious warfare, naval gunfire for groupforces, Navy close air support to ground troops, and CWC (I believeCWC now stands for composite warfare commander).• In each case, a doctrinal publication provided a conceptual andprocedural framework that included characteristics of equipment indescriptions formulated generally so that new models of particulartypes of equipment can be introduced without requiring amodification of the doctrinal manual
  • Doctrine creates an image of the waywe fight (from P. Morosoff)161Doctrine facilitates warfighters’ creating or revising their mental images ofhow to use the equipment to create a capability: a good doctrinalpublication explains a general problem (e.g., how to get a gun on a ship tohit a small target on the land) and then explains how to solve it towarfighters who may feel the problem is impossible.General Petreaus FM 3-24, "Counterinsurgency," is a classic example. Inhis case, the writing of FM 3-24 came about 3 years after the problemarose. Equipped with that manual and encouragement from Petreaus thecommander in Iraq, the forces in Iraq turned things around.
  • 162Coordinated Warfighter Ontologies areprerequisite for:–Situational Awareness–Situational Understanding–Common Operational Picture–Operational Design–Task Organizing–Systems Analysis–Military Decision Making Process
  • Conclusions & Recommendations• Ontology process is part of all Operations• War-Fighters, doctrine writers, and IT developersneed to collaboratively develop and then work off ofshared models ontologies• Essential to Sense-Making and Understanding• Essential to Decision Making• Essential to proper domain representation• Currently no Repeatable Process (RP) across DoD• Should Adopt and Refine RP across DoD• Benefits to Operations, Doctrine, Training, and ITDevelopment
  • Coda: Practical Introduction toOntology Building (Toy Example)Werner Ceusters164
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T UA simple battlefield ontology (from W. Ceusters)building personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-intoOntology
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T UOntology used for annotating a situationbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-intoOntologySituation
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T UReferent Tracking (RT) used for representing a situation#1 #2 #3 #4 #10OntologySituationalmodelSituation#5 #6 #8#7usesusesusesusesusesbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-inbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-in
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T Uuse the same weaponuse the sametype ofweaponReferent Tracking preserves identity#2 #3 #4 #10OntologySituationalmodelSituation#6 #8#7usesusesusesusesbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-inbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-in
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T UfaithfulSpecific relations versus generic relations#1 #2 #3 #4 #10OntologySituationalmodelSituation#5 #6 #8#7usesusesusesusesusesbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-inbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-in
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T USpecific relations versus generic relationsOntologySituationalmodelSituationNOT faithfulusesbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-inbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-in
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T URepresentation of times when relations hold#3OntologySituationalmodelSituationsoldierprivate sergeant sergeant-majorat t1at t2at t3
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T U#1 #2OntologySituationalmodelSituation#5 #6usesat t1usesat t1building personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-inbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-in
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T U#1 #2OntologySituationalmodelSituation#5usesat t2after the death of #1 at t2building personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-inbuilding personvehicletank soldierPOWweaponmortarsubmachinegun carobjectcorpseSpatial regionlocated-intransforms-in
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T URT deals with conflicting representations bykeeping track of sources#1 #2SituationalmodelSituation#5 #6usesat t1usesat t1usesat t2at t3Ontology corpseasserts at t2
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T U#1 #2SituationalmodelSituation#5 #6usesat t1usesat t1usesat t2at t3Ontology corpseasserts at t4RT deals with conflicting representations bykeeping track of sources
  • New York StateCenter of Excellence inBioinformatics & Life SciencesR T UAdvantages of Referent Tracking• Preserves identity• Allows to assert relationships amongst entities thatare not generically true• Appropriate representation of the time whenrelationships hold• Deals with conflicting representations by keepingtrack of sources• Mimics the structure of reality