Abstract
Temporal data is ubiquitous, and its importance has been witnessed by the research efforts for several decades as well as by the increased interest in the last years from both academia and industry. Two prominent research directions in this context are the field of temporal databases and the field of time series data. This extended abstract aims at providing a concise overview about the state of the art in processing temporal and time series data as well as to discuss open research problems and challenges.
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CITATION STYLE
Gamper, J., & Dignös, A. (2020). Processing Temporal and Time Series Data: Present State and Future Challenges. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12245 LNCS, pp. 8–14). Springer. https://doi.org/10.1007/978-3-030-54832-2_2
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