2010•Unpublished venueRequires access

Ontologies for Rapid Integration of Heterogeneous Data for Command, Control, & Intelligence

Leo Obrst, Suzette Stoutenburg, Dru McCandless, Deborah L. Nichols, Paul Franklin, Mike Prausa, Richard Sward

Open publisher page 7 citations

Abstract

Ontologies enable explicit expression of collective concepts and support Machine-to-Machine (M2M) interactions at the semantic level. Ontologies expressed in a standard language, such as the Web Ontology Language (OWL) and exposed on a network offer the potential for unprecedented interoperability solutions since they are semantically rich, computer interpretable and inherently extensible. In this chapter, we describe how we applied ontologies in OWL for rapid enterprise integration of heterogeneous data sources to track objects in a battlespace. We found that once a robust foundational domain ontology is established, it is easy and quick to integrate new data sources and therefore rapidly provide new system capabilities. In particular, we demonstrate how moving tracks can be quickly integrated with intelligence and space events to provide enhanced situational awareness using ontologies. This chapter also describes the overall SEER and SWORIER systems we developed, the latter of which translated OWL ontologies (and RDF instances) and Semantic Web Rule Language (SWRL) rules into Prolog, applied knowledge compilation techniques, and then at runtime, utilized a combined OWL/logic programming reasoned for efficient automated reasoning. We also briefly describe a more recent extension to the prototype and to the ontologies that we made to address more rigorous geospatial rules for unmanned autonomous vehicle (UAV) avoidance. Finally, we consider some issues raised by our work and future lines of research to address these.

About this research paper

What this paper is about

Ontologies enable explicit expression of collective concepts and support Machine-to-Machine (M2M) interactions at the semantic level. Ontologies expressed in a standard language, such as the Web Ontology Language (OWL) and exposed on a network offer the potential for unprecedented interoperability solutions since they are semantically rich, computer interpretable and inherently extensible. In this chapter, we describe how we applied ontologies in OWL for rapid enterprise integration of heterogeneous data sources to track objects in a battlespace. We found that once a robust foundational domain ontology is established, it is easy and quick to integrate new data sources and therefore rapidly provide new system capabilities. In particular, we demonstrate how moving tracks can be quickly integrated with intelligence and space events to provide enhanced situational awareness using ontologies. This chapter also describes the overall SEER and SWORIER systems we developed, the latter of which translated OWL ontologies (and RDF instances) and Semantic Web Rule Language (SWRL) rules into Prolog, applied knowledge compilation techniques, and then at runtime, utilized a combined OWL/logic programming reasoned for efficient automated reasoning. We also briefly describe a more recent extension to the prototype and to the ontologies that we made to address more rigorous geospatial rules for unmanned autonomous vehicle (UAV) avoidance. Finally, we consider some issues raised by our work and future lines of research to address these.

Why it matters

OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Ontologies enable explicit expression of collective concepts and support Machine-to-Machine (M2M) interactions at the semantic level. Ontologies expressed in a standard language, such as the Web Ontology Language (OWL) and exposed on a network offer the potential for unprecedented interoperability solutions since they are semantically rich, computer interpretable and inherently extensible. In this chapter, we describe how we applied ontologies in OWL for rapid enterprise integration of heterogeneous data sources to track objects in a battlespace. We found that once a robust foundational domain ontology is established, it is easy and quick to integrate new data sources and therefore rapidly provide new system capabilities. In particular, we demonstrate how moving tracks can be quickly integrated with intelligence and space events to provide enhanced situational awareness using ontologies. This chapter also describes the overall SEER and SWORIER systems we developed, the latter of which translated OWL ontologies (and RDF instances) and Semantic Web Rule Language (SWRL) rules into Prolog, applied knowledge compilation techniques, and then at runtime, utilized a combined OWL/logic programming reasoned for efficient automated reasoning. We also briefly describe a more recent extension to the prototype and to the ontologies that we made to address more rigorous geospatial rules for unmanned autonomous vehicle (UAV) avoidance. Finally, we consider some issues raised by our work and future lines of research to address these.

Key concepts: Computer science, Ontology, Web Ontology Language, Semantic Web, RDF, Ontology language, Semantic Web Rule Language, Automated reasoning

Related papers

Back to paper searchBrowse research topicsOriginal source
Ontologies for Rapid Integration of Heterogeneous Data for Command, Control, & Intelligence — Research Paper | ScholarLens