Representing Contextualized Data using Semantic Web Tools

RDF-based tools promise to provide a base for reasoning about metadata and about situ- ated data—data describing entities situated in time and space—that is superior to alternatives such as relational databases or object-oriented databases. However, essential representational machinery is missing from the current generation of Semantic Web tools and languages. When that machinery is added, the resulting capabilities offer a combination of novelty and flexibility that may usher in a wave of commercial Semantic Web tool-based applications that precedes the true arrival of the Semantic Web. We have constructed a system, the Semantic Engineering Workbench (SEW), that is proficient at managing situated data. Achieving a practical implementation necessitated extending the basic RDF tools (Hewlett-Packard's Jena and Stanford's Protege) to support contexts. In the SEW, a context references a set of statements having common spatial, temporal (and other metadata) attributes. We investigated multiple possible implementations of contexts, and found significant drawbacks in the most common approaches. The clear winners are quads (adding a fourth field of type 'context' to each triple results in a quadruple, or quad), and object-oriented contexts (a context mechanism that references individuals instead of statements). Most existing Semantic Web tools (e.g., Jena and Protege) do not understand contextualized data. For these tools, object-oriented contexts provide an elegant solution. We invented a new semantic primitive, called 'theRealThing', that is a generalization of the 'owl:sameIndividualAs' property. If and hold, then e1 and e2 are distinct resources (having different sets of attributes) that denote the same real-world entity. The SEW uses the 'theRealThing' property to automatically generate abstractions of related sets of resources. Our CHIME visualization tool utilizes the SEW to generate a continuous stream of abstracted entities representing summarizations of spatio-temporally situated entities. CHIME offers a preview of novel capabilities enabled by Semantic Web technol-