Database Technology for Processing Temporal Data

Michael Hanspeter Böhlen, Anton Dignös, Johann Gamper, Christian Søndergaard Jensen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Abstract

Despite the ubiquity of temporal data and considerable research on processing such data, database systems largely remain designed for processing the current state of some modeled reality. More recently, we have seen an increasing interest in processing historical or temporal data. The SQL:2011 standard introduced some temporal features, and commercial database management systems have started to offer temporal functionalities in a step-by-step manner. There has also been a proposal for a more fundamental and comprehensive solution for sequenced temporal queries, which allows a tight integration into relational database systems, thereby taking advantage of existing query optimization and evaluation technologies. New challenges for processing temporal data arise with multiple dimensions of time and the increasing amounts of data, including time series data that represent a special kind of temporal data.
Original languageEnglish
Title of host publication25th International Symposium on Temporal Representation and Reasoning, TIME 2018
EditorsKjetil Norvag, Wojciech Penczek, Natasha Alechina
Number of pages7
Volume120
PublisherSchloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH
Publication date1 Oct 2018
Article number2
ISBN (Electronic)978-3-95977-089-7
DOIs
Publication statusPublished - 1 Oct 2018
SeriesLeibniz International Proceedings in Informatics
Volume120
ISSN1868-8969

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Processing
Relational database systems
Time series

Keywords

  • SQL
  • Sequenced semantics
  • Temporal databases
  • Temporal query processing

Cite this

Böhlen, M. H., Dignös, A., Gamper, J., & Jensen, C. S. (2018). Database Technology for Processing Temporal Data. In K. Norvag, W. Penczek, & N. Alechina (Eds.), 25th International Symposium on Temporal Representation and Reasoning, TIME 2018 (Vol. 120). [2] Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH. Leibniz International Proceedings in Informatics, Vol.. 120 https://doi.org/10.4230/LIPIcs.TIME.2018.2
Böhlen, Michael Hanspeter ; Dignös, Anton ; Gamper, Johann ; Jensen, Christian Søndergaard. / Database Technology for Processing Temporal Data. 25th International Symposium on Temporal Representation and Reasoning, TIME 2018. editor / Kjetil Norvag ; Wojciech Penczek ; Natasha Alechina. Vol. 120 Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, 2018. (Leibniz International Proceedings in Informatics, Vol. 120).
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Böhlen, MH, Dignös, A, Gamper, J & Jensen, CS 2018, Database Technology for Processing Temporal Data. in K Norvag, W Penczek & N Alechina (eds), 25th International Symposium on Temporal Representation and Reasoning, TIME 2018. vol. 120, 2, Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Leibniz International Proceedings in Informatics, vol. 120. https://doi.org/10.4230/LIPIcs.TIME.2018.2

Database Technology for Processing Temporal Data. / Böhlen, Michael Hanspeter; Dignös, Anton; Gamper, Johann; Jensen, Christian Søndergaard.

25th International Symposium on Temporal Representation and Reasoning, TIME 2018. ed. / Kjetil Norvag; Wojciech Penczek; Natasha Alechina. Vol. 120 Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, 2018. 2 (Leibniz International Proceedings in Informatics, Vol. 120).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Böhlen MH, Dignös A, Gamper J, Jensen CS. Database Technology for Processing Temporal Data. In Norvag K, Penczek W, Alechina N, editors, 25th International Symposium on Temporal Representation and Reasoning, TIME 2018. Vol. 120. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH. 2018. 2. (Leibniz International Proceedings in Informatics, Vol. 120). https://doi.org/10.4230/LIPIcs.TIME.2018.2