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Database Technology for Processing Temporal Data (Invited Paper)

Authors Michael H. Böhlen , Anton Dignös , Johann Gamper , Christian S. Jensen

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Author Details

Michael H. Böhlen
  • University of Zurich, Switzerland
Anton Dignös
  • Free University of Bozen-Bolzano, Italy
Johann Gamper
  • Free University of Bozen-Bolzano, Italy
Christian S. Jensen
  • Aalborg University, Denmark

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Michael H. Böhlen, Anton Dignös, Johann Gamper, and Christian S. Jensen. Database Technology for Processing Temporal Data (Invited Paper). In 25th International Symposium on Temporal Representation and Reasoning (TIME 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 120, pp. 2:1-2:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.TIME.2018.2

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.

Subject Classification

ACM Subject Classification
  • Information systems → Data management systems
  • Information systems → Temporal data
Keywords
  • Temporal databases
  • temporal query processing
  • sequenced semantics
  • SQL

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