License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.TIME.2019.7
URN: urn:nbn:de:0030-drops-113658
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2019/11365/
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Brandt, Sebastian ; Calvanese, Diego ; Kalayci, Elem Güzel ; Kontchakov, Roman ; Mörzinger, Benjamin ; Ryzhikov, Vladislav ; Xiao, Guohui ; Zakharyaschev, Michael

Two-Dimensional Rule Language for Querying Sensor Log Data: A Framework and Use Cases

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LIPIcs-TIME-2019-7.pdf (1 MB)

Abstract

Motivated by two industrial use cases that involve detecting events of interest in (asynchronous) time series from sensors in manufacturing rigs and gas turbines, we design an expressive rule language DslD equipped with interval aggregate functions (such as weighted average over a time interval), Allen's interval relations and various metric constructs. We demonstrate how to model events in the uses cases in terms of DslD programs. We show that answering DslD queries in our use cases can be reduced to evaluating SQL queries. Our experiments with the use cases, carried out on the Apache Spark system, show that such SQL queries scale well on large real-world datasets.

BibTeX - Entry

@InProceedings{brandt_et_al:LIPIcs:2019:11365,
  author =	{Sebastian Brandt and Diego Calvanese and Elem G{\"u}zel Kalayci and Roman Kontchakov and Benjamin M{\"o}rzinger and Vladislav Ryzhikov and Guohui Xiao and Michael Zakharyaschev},
  title =	{{Two-Dimensional Rule Language for Querying Sensor Log Data: A Framework and Use Cases}},
  booktitle =	{26th International Symposium on Temporal Representation and Reasoning (TIME 2019)},
  pages =	{7:1--7:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-127-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{147},
  editor =	{Johann Gamper and Sophie Pinchinat and Guido Sciavicco},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2019/11365},
  URN =		{urn:nbn:de:0030-drops-113658},
  doi =		{10.4230/LIPIcs.TIME.2019.7},
  annote =	{Keywords: Ontology-based data access, temporal logic, sensor log data}
}

Keywords: Ontology-based data access, temporal logic, sensor log data
Collection: 26th International Symposium on Temporal Representation and Reasoning (TIME 2019)
Issue Date: 2019
Date of publication: 07.10.2019

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