Stream-Query Compilation with Ontologies

Özgür Lütfü Özçep, Ralf Möller, Christian Neuenstadt


Rational agents perceiving data from a dynamic environment and acting in it have to be equipped with capabilities such as decision making, planning etc. We assume that these capabilities are based on query answering with respect to (high-level) streams of symbolic descriptions, which are grounded in (low-level) data streams. Queries need to be answered w.r.t. an ontology. The central idea is to compile ontology-based stream queries (continuous or historical) to relational data processing technology, for which efficient implementations are available. We motivate our query language STARQL (Streaming and Temporal ontology Access with a Reasoning-Based Query Language) with a sensor data processing scenario, and compare the approach realized in the STARQL framework with related approaches regarding expressivity.

Original languageEnglish
Title of host publicationAI 2015: Advances in Artificial Intelligence
EditorsBernhard Pfahringer, Jochen Renz
Number of pages7
Place of PublicationCham
PublisherSpringer International Publishing
Publication date22.11.2015
ISBN (Print)978-3-319-26349-6
ISBN (Electronic)978-3-319-26350-2
Publication statusPublished - 22.11.2015
Event28th Australasian Joint Conference on Artificial Intelligence - Canberra, Australia
Duration: 30.11.201504.12.2015
Conference number: 157849

DFG Research Classification Scheme

  • 409-01 Theoretical Computer Science


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