Distributed Development of a Shared Semantic Resource

Working Papers

Methodology for Building a Shared Semantic Resource (03-21-13)

Ontologies and Data Models (03-20-13)

Collaborative Development of a Shared Semantic Resource (01-29-2013)

---

The General Structure: Data Models and Ontologies (from T. Malyuta)

A data model is an efficient means to store data that is needed for some given application. It is not the role of the data model to serve as any sort of bigger picture. The data model provides no larger context.

Suppose, for example, we are dealing with a small domain that includes Id, DOB, Name (First Name [FN] and Last Name [LN]) of a Person. Depending on the needs of my application I can have different models, representing:

Person (ID, DOB, FN, LN) -- I need to store one version of person's names

Person (ID, DOB) and Names (NameID, ID, FN, LN) -- I need to store all available names (e.g. we have a situation when we collect personal data from different reports)

Person (ID, Name) -- we benefit in our processing from having one field for the Name

The role of an ontology is to provide the bigger picture that provides a context for these and other related models. It achieves this by describe not how we store data about reality, but rather by describing this reality itself. This is important because this is what gives us hope of achieving interoperability of data sources via mappings to ontology. Even though we have different ways of representing data about reality in our stores (for example because we are using different labels), we can nonetheless agree on what this reality is, on the labels we use to represent the entities we identify within it, and on the logic of the relations between these entities. Thus in ontology we will have a single representation of a person, a person's id, his full name, first and last name, date of birth, as well as of the relations between these entities.

When we map models, we map semantics but not the structure. We map ID, DOB, FN, LN, and Name to the ontology using relevant logical expressions. But we do not map the structure of data as it is in our model. NameID in the second model has no meaning in the life (it is a specific structuring tool, created by our application), therefore we do not map it to the ontology which serves as benchmark for integration.

---

Publications

David Salmen, Tatiana Malyuta, Alan Hansen, Shaun Cronen, Barry Smith, “Integration of Intelligence Data through Semantic Enhancement”, Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS), George Mason University, Fairfax, VA, November 16-17, 2011, CEUR 808, 6-13.

Barry Smith, Tatiana Malyuta, William S. Mandrick, Chia Fu, Kesny Parent, Milan Patel, “Horizontal Integration of Warfighter Intelligence Data. A Shared Semantic Resource for the Intelligence Community”, Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS), George Mason University, Fairfax, VA, October 23-25, 2012, CEUR 996, 112-119.

Barry Smith, Tatiana Malyuta, David Salmen, William Mandrick, Kesny Parent, Shouvik Bardhan, Jamie Johnson, “Ontology for the Intelligence Analyst”, CrossTalk: The Journal of Defense Software Engineering, November/December 2012,18-25.

Barry Smith, Tatiana Malyuta, Ron Rudnicki, William Mandrick, David Salmen, Peter Morosoff, Danielle K. Duff, James Schoening, Kesny Parent, “IAO-Intel: An Ontology of Information Artifacts in the Intelligence Domain”, Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS), George Mason University, Fairfax, VA, Nov. 11-13, 2013), CEUR, vol. 1097, 33-40.

Erik Thomsen, William Duncan, Tatanya Malyuta and Barry Smith, “A Computational Framework for Living Plan Specification, Execution and Evaluation”, Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS), George Mason University, Fairfax, VA, November 18-20, 2014.

Neil Otte, Brian Donohue and Barry Smith. “An Ontological Approach to Territorial Disputes”, Proceedings of the Conference on Semantic Technology in Intelligence, Defense and Security (STIDS), George Mason University, Fairfax, VA, November 18-20, 2014.

James R. Schoening, Danielle K. Duff, Dorothy A. Hines, Keith M. Riser, Tien Pham, Gary H. Stolovy, Jeff Houser, Ronald Rudnicki, Robert Ganger, Alex James, Eric Nagler, “PED fusion via enterprise ontology," Proceedings of SPIE 9464, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI, 2015

Peter Morosoff, Ron Rudnicki, Jason Bryant, Robert Farrell, Barry Smith, “Peter Morosoff, Ron Rudnicki, Jason Bryant, Robert Farrell, Barry Smith, “Joint Doctrine Ontology: A Benchmark for Military Information Systems Interoperability”, Semantic Technology for Intelligence, Defense and Security (STIDS), 2015, CEUR vol. 1523, 2-9.

---

Basic Formal Ontology

Building Ontologies with Basic Formal Ontology (MIT Press, 2015)

http://www.ifomis.uni-saarland.de/bfo/

Draft Specification and User Guide for BFO 2.0: http://purl.obolibrary.org/obo/bfo/Reference.

Current version of the draft BFO 2.0 OWL file: http://purl.obolibrary.org/obo/bfo.owl

Release notes: http://purl.obolibrary.org/obo/bfo/2012-07-20/ReleaseNotes

Further information concerning the draft BFO 2.0: http://code.google.com/p/bfo/

Collaborating projects

AIRS Project Ontologies

Military Ontology