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. 7will not yield horizontal integration

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
Heterogeneous Contents
SE ontologiesUser

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
Heterogeneous Contents
SE ontologiesUser
Index

13. 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 ContentsABC KLM
XYZ

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
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

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
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

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

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
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

25. 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)

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
Heterogeneous Contents
Shared Semantic Resource
Dataspace
Army
Navy
Air
Force

28. 28

29. 29
MI L I TARY OPERAT I ONS ONTOLOGY SUI T E

30. 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)

31. 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

32. 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

33. Conclusion

34. Acknowledgements