View The Document

Accession Number:

AD1132214

Title:

Ontology Engineering: An Application Perspective

Author(s):

• Semy, Salim K.
• Hetherington-Young, Kevin N.
• Frey, Steven E.

Author Organization(s):

• MITRE CORP MCLEAN VA

Report Date:

2004-01-01

Abstract:

Enterprise Integration is a key challenge faced by many organizations, including those of the U.S. Government. An important enabler of enterprise integration is data integration. There is promise in applying Semantic Web technologies to enable data integration of disparate data sources based on the semantics (meaning) of the data. As we start to build ontologies within United States (U.S.) government domains for this purpose, we consider how Semantic Web technologies may operate within existing operational infrastructures and how best to build ontologies to facilitate usability. This paper explores the ontology engineering and adoption challenges based on current state of the art in Semantic Web technology. We consider alternative approaches to engineer ontologies, discuss current and emerging standards in this area, look at approaches to integrate data through ontology mapping, and outline a set of skills necessary to develop and apply ontologies. We then propose an architecture to insert Semantic Web technologies into an existing infrastructure to enable data and application interoperability, based on experimentation within the Intelligence Community. The paper concludes with recommendations on a way ahead, and highlights some potential pitfalls for future ontology developers.

Document Type:

Conference:

Journal:

Pages:

14

File Size:

1.25MB

Contracts:

Grants:

Descriptors:

• relational database management systems
• department of state
• graphical user interface
• computer programming
• databases
• engineering
• language
• law enforcement
• computers
• data integration
• data sets
• database management systems
• governments
• inference engines
• intelligence community
• relational databases
• standards
• best practices
• law enforcement officers
• lessons learned

Identifiers:

• architecture to insert Semantic Web technologies
• existing infrastructure to enable data
• application interoperability
• experimentation within the Intelligence Community
• potential pitfalls
• future ontology developers

SubjectCategory:

• Mathematical and Computer Sciences
• Mathematical and Computer Sciences

Communities of Interest:

• Materials and Manufacturing Processes

Distribution Statement:

Approved For Public Release

View The Document