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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.
16
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.
24
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
28
29
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
31
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
32
Conclusion
Acknowledgements