1. 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

2. Horizontal Integration of Intelligence
2

3. 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

4. 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

5. 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

6. This 6

7. will not yield horizontal integration 7

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

9. 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

10. 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

11. 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
User SE ontologies
Heterogeneous Contents

12. 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
User SE ontologies
Index Heterogeneous Contents

13. Basis of the SE Approach
• 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
SE ontology labels XYZ
ABC Heterogeneous Contents KLM

14. 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

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. Intelligence Ontology Suite
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.
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
16
8 TARGO Target Ontology

17. 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

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

19. Illustration
Vehicle Black –
reference
ontologies
Artillery Red –
Tractor Vehicle application
ontologies
Wheeled Artillery
Tractor Tractor
Wheeled
Artillery
Tractor

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 and
governance

21. 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

22. 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

23. Architecture Illustration

24. Intelligence Ontology Suite
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.
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
24
8 TARGO Target Ontology

25. top level Basic Formal Ontology (BFO)
Ontology for
Information Artifact
Biomedical Spatial Ontology
mid-level Ontology
Investigations (BSPO)
(IAO)
(OBI)
Anatomy Ontology Infectious
(FMA*, CARO) Disease
Environment
Cellular Ontology
Cell Ontology
Component (IDO*)
Ontology (EnvO)
Ontology
(CL) Phenotypic Biological
domain (FMA*, GO*)
Quality Process
level Subcellular Anatomy Ontology (SAO)
Ontology Ontology (GO*)
(PaTO)
Sequence Ontology
(SO*) Molecular
Function
Protein Ontology (GO*)
(PRO*)
Extension Strategy + Modular Organization 25

26. 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

27. • 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
Army
Shared Semantic Resource
Navy
Dataspace
Air
Force Heterogeneous Contents

28. 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
29

30. top level Basic Formal Ontology (BFO)
Ontology for
Information Artifact
Biomedical Spatial Ontology
mid-level Ontology
Investigations (BSPO)
(IAO)
(OBI)
Anatomy Ontology Infectious
(FMA*, CARO) Disease
Environment
Cellular Ontology
Cell Ontology
Component (IDO*)
Ontology (EnvO)
Ontology
(CL) Phenotypic Biological
domain (FMA*, GO*)
Quality Process
level Subcellular Anatomy Ontology (SAO)
Ontology Ontology (GO*)
(PaTO)
Sequence Ontology
(SO*) Molecular
Function
Protein Ontology (GO*)
(PRO*)
Extension Strategy + Modular Organization 30

31. BFO:continuant
continuant
independent dependent spatial
continuant continuant region
portion of object generically specifically 0D-region
site dependent dependent
material boundary
continuant continuant
object 1D-region
information realizable
quality
artifact entity
fiat object 2D-region
part function
object 3D-region
aggregate role
disposition
31

32. BFO:occurrent
occurrent
processual spatiotemporal temporal
entity region region
scattered connected scattered connected
process spatiotemporal spatiotemporal temporal temporal
region region region region
fiat process spatiotemporal temporal
part instant instant
process spatiotemporal temporal
aggregate interval interval
process
boundary
processual
context
32

33. Conclusion

34. Acknowledgements