Horizontal Integration of Warfighter Intelligence Data A Shared - - PowerPoint PPT Presentation

Horizontal Integration of Warfighter Intelligence Data

A Shared Semantic Resource for the Intelligence Community

Barry Smith, University at Buffalo, NY, USA Tatiana Malyuta, New York City College of Technology, NY William S. Mandrick, Data Tactics Corp., VA, USA Chia Fu, Data Tactics Corp., VA, USA Kesny Parent, Intelligence and Information Warfare Directorate, CERDEC, MD, USA Milan Patel, Intelligence and Information Warfare Directorate, CERDEC, MD, USA

Horizontal Integration of Intelligence

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Horizontal Integration

• “Horizontally integrating warfighter intelligence

data … requires access (including discovery, search, retrieval, and display) to intelligence data among the warfighters and other producers and consumers via standardized services and

• architectures. These consumers include, but are

not limited to, the combatant commands, Services, Defense agencies, and the Intelligence Community.” Chairman of the Joint Chiefs of Staff Instruction J2 CJCSI 3340.02A 1 August 2011

Challenges to the horizontal integration of Intelligence Data

• Quantity and variety

– Need to do justice to radical heterogeneity in the representation of data and semantics Dynamic environments – Need agile support for retrieval, integration and enrichment of data

• Emergence of new data resources

– Need in agile, flexible, and incremental integration approach

Horizontal integration

=def. multiple heterogeneous data resources become aligned in such a way that search and analysis procedures can be applied to their combined content as if they formed a single resource

This

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will not yield horizontal integration

Strategy

• Strategy to avoid stovepipes requires a solution that is

– Stable – Incrementally growing – Flexible in addressing new needs – Independent of source data syntax and semantics

The answer: Semantic Enhancement (SE), a strategy of external (arm’s length) alignment

Distri Distribu bute ted d Commo Common n Gro Groun und d System System–Army Army (DCGS-A)

Semantic Enhancement of the Dataspace

• n the Cloud
• Dr. Tatiana Malyuta

New York City College of Technology

• f the City University of New York

Dataspace on the Cloud

Salmen, et al,. Integration of Intelligence Data through Semantic Enhancement, STIDS 2011

• strategy for developing an SE suite of orthogonal

reference ontology modules Smith, et al. Ontology for the Intelligence Analyst, CrossTalk: The Journal of Defense Software Engineering November/December 2012,18-25.

• Shows how SE approach provides immediate

benefits to the intelligence analyst

Dataspace on the Cloud

• Cloud (Bigtable-like) store of heterogeneous data and

data semantics

– Unified representation of structured and unstructured data – Without loss and or distortion of data or data semantics

• Homogeneous standardized presentation of

heterogeneous content via a suite of SE ontologies

Heterogeneous Contents SE ontologies

User

Dataspace on the Cloud

• Cloud (Bigtable-like) store of heterogeneous data and

data semantics

– Unified representation of structured and unstructured data – Without loss and or distortion of data or data semantics

• Homogeneous standardized presentation of

heterogeneous content via a suite of SE ontologies

Heterogeneous Contents SE ontologies

User Index

Basis of the SE Approach

SE ontology labels

• Focusing on the terms (labels, acronyms, codes) used in the source

data.

• Where multiple distinct terms {t1, …, tn} are used in separate data

sources with one and the same meaning, they are associated with a single preferred label drawn from a standard set of such labels

• All the separate data items associated with the {t1, … tn} thereby

linked together through the corresponding preferred labels.

• Preferred labels form basis for the ontologies we build

Heterogeneous Contents ABC KLM XYZ

SE Requirements to achieve Horizontal Integration

• The ontologies must be linked together through

logical definitions to form a single, non- redundant and consistently evolving integrated network

• The ontologies must be capable of evolving in an

agile fashion in response to new sorts of data and new analytical and warfighter needs  our focus here

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

Intelligence Ontology Suite

No. Ontology Prefix Ontology Full Name List of Terms

1 AO Agent Ontology 2 ARTO Artifact Ontology 3 BFO Basic Formal Ontology 4 EVO Event Ontology 5 GEO Geospatial Feature Ontology 6 IIAO Intelligence Information Artifact Ontology 7 LOCO Location Reference Ontology 8 TARGO Target Ontology

Home Introduction PMESII-PT ASCOPE References Links Welcome to the I2WD Ontology Suite!

I2WD Ontology Suite: A web server aimed to facilitate ontology visualization, query, and development for the Intelligence

• Community. I2WD Ontology Suite provides a user-friendly web interface for displaying the details and hierarchy of a specific
• ntology term.

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Ontology Development Principles

• Reference ontologies – capture generic content

and are designed for aggressive reuse in multiple different types of context

– Single inheritance – Single reference ontology for each domain of interest

• Application ontologies – created by combining

local content with generic content taken from relevant reference ontologies

Illustration

vehicle =def: an object used for transporting people or goods tractor =def: a vehicle that is used for towing crane =def: a vehicle that is used for lifting and moving heavy objects vehicle platform=def: means of providing mobility to a vehicle wheeled platform=def: a vehicle platform that provides mobility through the use of wheels tracked platform=def: a vehicle platform that provides mobility through the use of continuous tracks artillery vehicle = def. vehicle designed for the transport of one or more artillery weapons wheeled tractor = def. a tractor that has a wheeled platform Russian wheeled tractor type T33 =

• def. a wheeled tractor of type T33

manufactured in Russia Ukrainian wheeled tractor type T33 = def. a wheeled tractor of type T33 manufactured in Ukraine

Reference Ontology Application Definitions

Illustration

Vehicle Tractor Wheeled Tractor Artillery Tractor Wheeled Artillery Tractor Artillery Vehicle Black – reference

• ntologies

Red – application

• ntologies

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 and governance

Examples of Principles

• All terms in all ontologies should be singular

nouns

• Same relations between terms should be reused

in every ontology

• Reference ontologies should be based on single

inheritance

• All definitions should be of the form

an S = Def. a G which Ds where ‘G’ (for: species) is the parent term of S in the corresponding reference ontology

SE Architecture

• The Upper Level Ontology (ULO) in the SE

hierarchy must be maximally general (no overlap with domain ontologies)

• The Mid-Level Ontologies (MLOs) introduce

successively less general and more detailed representations of types which arise in successively narrower domains until we reach the Lowest Level Ontologies (LLOs).

• The LLOs are maximally specific representation of

the entities in a particular one-dimensional domain

Architecture Illustration

Intelligence Ontology Suite

No. Ontology Prefix Ontology Full Name List of Terms

1 AO Agent Ontology 2 ARTO Artifact Ontology 3 BFO Basic Formal Ontology 4 EVO Event Ontology 5 GEO Geospatial Feature Ontology 6 IIAO Intelligence Information Artifact Ontology 7 LOCO Location Reference Ontology 8 TARGO Target Ontology

Home Introduction PMESII-PT ASCOPE References Links Welcome to the I2WD Ontology Suite!

I2WD Ontology Suite: A web server aimed to facilitate ontology visualization, query, and development for the Intelligence

• Community. I2WD Ontology Suite provides a user-friendly web interface for displaying the details and hierarchy of a specific
• ntology term.

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Anatomy Ontology (FMA*, CARO) Environment Ontology (EnvO) Infectious Disease Ontology (IDO*) Biological Process Ontology (GO*) Cell Ontology (CL) Cellular Component Ontology (FMA*, GO*) Phenotypic Quality Ontology (PaTO) Subcellular Anatomy Ontology (SAO) Sequence Ontology (SO*) Molecular Function (GO*) Protein Ontology (PRO*)

Extension Strategy + Modular Organization 25

top level mid-level domain level

Information Artifact Ontology (IAO) Ontology for Biomedical Investigations (OBI) Spatial Ontology (BSPO)

Basic Formal Ontology (BFO)

Shared Semantic Resource

• Growing collection of shared ontologies

asserted and application

• Pilot program to coordinate a small number of

development communities including both DSC (internal) and external groups to produce their

• ntologies according to the best practice

guidelines of the SE methodology

• Given the principles of building the SE (governance, distributed

incremental development, common architecture) the next step is to create a semantic resource that can be shared by a larger community, and used for inter- and intra-integration on numerous systems Heterogeneous Contents

Shared Semantic Resource

Dataspace Army Navy Air Force

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MI L I TARY OPERAT I ONS ONTOLOGY SUI T E

Anatomy Ontology (FMA*, CARO) Environment Ontology (EnvO) Infectious Disease Ontology (IDO*) Biological Process Ontology (GO*) Cell Ontology (CL) Cellular Component Ontology (FMA*, GO*) Phenotypic Quality Ontology (PaTO) Subcellular Anatomy Ontology (SAO) Sequence Ontology (SO*) Molecular Function (GO*) Protein Ontology (PRO*)

Extension Strategy + Modular Organization 30

top level mid-level domain level

Information Artifact Ontology (IAO) Ontology for Biomedical Investigations (OBI) Spatial Ontology (BSPO)

Basic Formal Ontology (BFO)

continuant independent continuant portion of material

• bject

fiat object part

• bject

aggregate

• bject

boundary site dependent continuant generically dependent continuant

information artifact

specifically dependent continuant quality realizable entity function role disposition spatial region

0D-region 1D-region 2D-region 3D-region

BFO:continuant

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• ccurrent

processual entity process fiat process part process aggregate process boundary processual context spatiotemporal region

scattered spatiotemporal region connected spatiotemporal region

spatiotemporal instant spatiotemporal interval temporal region

scattered temporal region connected temporal region

temporal instant temporal interval

BFO:occurrent

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Conclusion

Acknowledgements