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Contribution Details
| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Applied temporal RDF: efficient temporal querying of RDF data with SPARQL |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Event Title | 6th European Semantic Web Conference (ESWC) |
| Event Type | conference |
| Event Location | Crete, Greece |
| Event Start Date | June 1 - 2009 |
| Event End Date | June 1 - 2009 |
| Abstract Text | Many applications operate on time-sensitive data. Some of these data are only valid for certain intervals (e.g., job-assignments, versions of software code), others describe temporal events that happened at certain points in time (e.g., a persons birthday). Until recently, the only way to incorporate time into Semantic Web models was as a data type property. Temporal RDF, however, considers time as an additional dimension in data preserving the semantics of time. In this paper we present a syntax and storage format based on named graphs to express temporal RDF. Given the restriction to preexisting RDF-syntax, our approach can perform any temporal query using standard SPARQL syntax only. For convenience, we introduce a shorthand format called t-SPARQL for temporal queries and show how t-SPARQL queries can be translated to standard SPARQL. Additionally, we show that, depending on the underlying data’s nature, the temporal RDF approach vastly reduces the number of triples by eliminating redundancies resulting in an increased performance for processing and querying. Last but not least, we introduce a new indexing approach method that can significantly reduce the time needed to execute time point queries (e.g., what happened on January 1st). |
| Digital Object Identifier | 10.1007/978-3-642-02121-3_25 |
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