Ontology Based Data Access on Temporal and Streaming Data

Abstract

Though processing time-dependent data has been investigated for a long time, the research on temporal and especially stream reasoning over linked open data and ontologies is reaching its high point these days. In this tutorial, we give an overview of state-of-the art query languages and engines for temporal and stream reasoning. On a more detailed level, we discuss the new language STARQL (Reasoning-based Query Language for Streaming and Temporal ontology Access). STARQL is designed as an expressive and flexible stream query framework that offers the possibility to embed different (temporal) description logics as filter query languages over ontologies, and hence it can be used within the OBDA paradigm (Ontology Based Data Access in the classical sense) and within the ABDEO paradigm (Accessing Big Data over Expressive Ontologies).
Original languageEnglish
Title of host publicationReasoning Web. Reasoning on the Web in the Big Data Era: 10th International Summer School 2014, Athens, Greece, September 8-13, 2014. Proceedings
EditorsManolis Koubarakis, Giorgos Stamou, Giorgos Stoilos, Ian Horrocks, Phokion Kolaitis, Georg Lausen, Gerhard Weikum
Number of pages34
Volume8714
Place of PublicationCham
PublisherSpringer International Publishing
Publication date01.09.2014
Pages279-312
ISBN (Print)978-3-319-10586-4
ISBN (Electronic)978-3-319-10587-1
DOIs
Publication statusPublished - 01.09.2014
Event10th International Summer School 2014 in Reasoning Web: Reasoning on the Web in the Big Data Era - Athens, Greece
Duration: 08.09.201413.09.2014

DFG Research Classification Scheme

  • 409-06 Information Systems, Process and Knowledge Management

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