Abstract
The paper contributes to the recent efforts on temporalizing and streamifiying ontology based data access (OBDA) by discussing aspects of rewritability, i.e., compilability of the TBox into ontology-level queries, and unfoldability, i.e., transformability of ontology-level queries to queries on datasource level, for the new query-language framework STARQL. The distinguishing feature of STARQL is its general stream windowing and ABox sequencing strategy which allows it to plugin well-known query languages such as unions of conjunctive queries (UCQs) in combination with TBox languages such as DL-Lite and do temporal reasoning with a sorted first-order logic on top of them. The paper discusses safety aspects under which STARQL queries that embed UCQs over DL-Lite ontologies can be rewritten and unfolded to back-end relational stream query languages such as CQL. With these results, the adoption of description logic technology in industrially relevant application areas such as industrial monitoring is crucially fostered.
| Originalsprache | Englisch |
|---|---|
| Titel | KI 2014: Advances in Artificial Intelligence |
| Redakteure/-innen | Carsten Lutz, Michael Thielscher |
| Seitenumfang | 12 |
| Band | 8736 |
| Erscheinungsort | Cham |
| Herausgeber (Verlag) | Springer International Publishing |
| Erscheinungsdatum | 01.10.2014 |
| Seiten | 183-194 |
| ISBN (Print) | 978-3-319-11205-3 |
| ISBN (elektronisch) | 978-3-319-11206-0 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 01.10.2014 |
| Veranstaltung | 37th Annual German Conference on Artificial Intelligence - Stuttgart, Deutschland Dauer: 22.09.2014 → 26.09.2014 |
UN SDGs
Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung
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SDG 3 – Gesundheit und Wohlergehen
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SDG 9 – Industrie, Innovation und Infrastruktur
DFG-Fachsystematik
- 4.43-01 Theoretische Informatik
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