License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
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DOI: 10.4230/DagSemProc.10042.4
URN: urn:nbn:de:0030-drops-25555
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Stuckenschmidt, Heiner ; Ceri, Stefano ; Della Valle, Emanuele ; van Harmelen, Frank

Towards Expressive Stream Reasoning

10042.StuckenschmidtHeiner.Paper.2555.pdf (0.3 MB)


Stream Data processing has become a popular topic in database research addressing the challenge of efficiently answering queries over continuous data streams. Meanwhile data streams have become more and more important as a basis for higher level decision processes that require complex reasoning over data streams and rich background knowledge. In previous work the foundation for complex reasoning over streams and background knowledge was laid by introducing technologies for wrapping and querying streams in the RDF data format and by supporting simple forms of reasoning in terms of incremental view maintenance. In this paper, we discuss how this existing technologies should be extended toward richer forms of reasoning using Sensor Networks as a motivating example.

BibTeX - Entry

  author =	{Stuckenschmidt, Heiner and Ceri, Stefano and Della Valle, Emanuele and van Harmelen, Frank},
  title =	{{Towards Expressive Stream Reasoning}},
  booktitle =	{Semantic Challenges in Sensor Networks},
  pages =	{1--14},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10042},
  editor =	{Karl Aberer and Avigdor Gal and Manfred Hauswirth and Kai-Uwe Sattler and Amit P. Sheth},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-25555},
  doi =		{10.4230/DagSemProc.10042.4},
  annote =	{Keywords: Streaming Data, Reasoning, C-SPARQL, Sensor Networks}

Keywords: Streaming Data, Reasoning, C-SPARQL, Sensor Networks
Collection: 10042 - Semantic Challenges in Sensor Networks
Issue Date: 2010
Date of publication: 18.05.2010

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