A Case Study in Applying Semantic Web Technologies to the XML-Based Tactical Assessment Markup Language (TAML)

Candace Childers, Don Brutzman, Curis Blais, Paul Young

The ability to analyze data quickly and transform it into actionable information is vital for information superiority. However, the amount of available data is increasing and the time to make decisions is decreasing. There is too much data for humans to sift through and filter for decision making, so computer automation is necessary. The Extensible Markup Language (XML) offers a partial solution by providing a syntactic standard for data exchange. The Tactical Assessment Markup Language (TAML) is an XML vocabulary for exchanging undersea warfare tactical data. However, the meaning or semantics of the data is unknown to the machine processing the data. The Semantic Web is a set of technologies designed to add semantic information to data for machine processing. The technologies consist of several components, including a common syntax for data exchange, common semantic representation, and a common ontology language. Reasoning engines also apply algorithms to the data to infer useful information and present it to decision makers. Sophisticated Semantic Web tools and techniques are rapidly emerging. This paper provides a case study in adding stronger semantic content through application of Semantic Web technologies to XML-based languages such as TAML. The lessons learned will help enable systems to extract useful, actionable information from a number of distributed, autonomous, heterogeneous information sources and bring the armed forces closer to a knowledge-aware Global Information Grid (GIG).

Subjects: 11.2 Ontologies; 1.10 Information Retrieval


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