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

2

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 6

7 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

Distributed Common Ground System–Army (DCGS-A)

Semantic

Enhancement of

the Dataspace

on the Cloud

Dr. Tatiana Malyuta New York City College of Technology

of 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 ontology 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 ontologies Red – application ontologies

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 ontology 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 ontologies 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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M I L I TA R Y O P E R AT I O N S O N T O L O G Y S U I 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

object

fiat object part

object aggregate

object 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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occurrent

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