Supporting Complex Thematic, Spatial and Temporal Queries over Semantic Web Data

Abstract

Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. Often, the analytical process requires uncovering and analyzing complex thematic 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 for this purpose. However, these analysis mechanisms are primarily intended for thematic relationships. In this paper, we describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between named entities. We discuss modeling issues and present a set of semantic query operators. We also describe an efficient implementation in Oracle DBMS and demonstrate the scalability of our approach with a performance study using a large synthetic dataset from the national security domain.

Temporally Annotated Extended Logic Programs

“…Work in [10] provides a framework to support spatial and temporal analysis over semantic web data. With respect to the temporal component [10] is similar to [9], as it also computes the maximal validity temporal intervals of derived RDF triples, using the RDFS entailment rules.…”

“…With respect to the temporal component [10] is similar to [9], as it also computes the maximal validity temporal intervals of derived RDF triples, using the RDFS entailment rules. Yet, [10] does not consider strong and weak negation and validity intervals on logic rules.…”

A Survey on Models and Query Languages for Temporally Annotated RDF

“…In [20], [21], [22], the authors consider an extension of RDFS with spatial and temporal information. Here, we consider only the extension with temporal information.…”

Provenance and Temporally Annotated Logic Programming

“…Work in [11] provides a framework to support spatial and temporal analysis over RDFS data. With respect to the temporal component, [11] is similar to [10], as it also computes the maximal validity temporal intervals of derived RDF triples, using the RDFS entailment rules.…”

“…With respect to the temporal component, [11] is similar to [10], as it also computes the maximal validity temporal intervals of derived RDF triples, using the RDFS entailment rules. Yet, [11] does not consider the provenance domain.…”