Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. The outcome of the analytical process in these applications often hinges on uncovering and analyzing complex relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful in these applications. However, these analysis mechanisms are primarily intended for thematic relationships. We describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between named entities and describe an efficient implementation in Oracle DBMS. Additionally, we demonstrate the scalability of our approach with a performance study using a synthetic dataset from the national security domain.
Sheth, A. P.,
& Jain, P.
(2007). What, Where and When: Supporting Semantic, Spatial and Temporal Queries in a DBMS. .