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

Authors Sebastian Brandt, Diego Calvanese, Elem Güzel Kalaycı, Roman Kontchakov, Benjamin Mörzinger, Vladislav Ryzhikov, Guohui Xiao, Michael Zakharyaschev



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Author Details

Sebastian Brandt
  • Siemens CT, München, Germany
Diego Calvanese
  • KRDB Research Centre, Faculty of Computer Science, Free University of Bozen-Bolzano, Italy
Elem Güzel Kalaycı
  • KRDB Research Centre, Faculty of Computer Science, Free University of Bozen-Bolzano, Italy
Roman Kontchakov
  • Department of Computer Science and Information Systems, Birkbeck, University of London, UK
Benjamin Mörzinger
  • Technische Universität Wien, Austria
Vladislav Ryzhikov
  • Department of Computer Science and Information Systems, Birkbeck, University of London, UK
Guohui Xiao
  • KRDB Research Centre, Faculty of Computer Science, Free University of Bozen-Bolzano, Italy
Michael Zakharyaschev
  • Department of Computer Science and Information Systems, Birkbeck, University of London, UK
  • Faculty of Computer Science, National Research University Higher School of Economics, Moscow, Russia

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Sebastian Brandt, Diego Calvanese, Elem Güzel Kalaycı, Roman Kontchakov, Benjamin Mörzinger, Vladislav Ryzhikov, Guohui Xiao, and Michael Zakharyaschev. Two-Dimensional Rule Language for Querying Sensor Log Data: A Framework and Use Cases. In 26th International Symposium on Temporal Representation and Reasoning (TIME 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 147, pp. 7:1-7:15, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.TIME.2019.7

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.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Ontology engineering
  • Computing methodologies → Temporal reasoning
  • Theory of computation → Modal and temporal logics
Keywords
  • Ontology-based data access
  • temporal logic
  • sensor log data

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