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The SPADES Framework for Scalable Management of Spatio-textual Data

Published: 04 March 2021 Publication History

Abstract

This paper presents the research activities in the context of the SPADES project for scalable indexing and processing of big spatial and spatio-textual data. Management of spatio-textual data raises challenges due to the high dimensional nature of text, in combination with the problem of preserving data locality for spatial data. In this paper, we provide an overview of our contributions in this field, both for centralized and parallel processing. We present an indexing layer that supports spatio-textual data, as well as other data types: spatio-temporal, multidimensional as well as semantic data represented in RDF. This is coupled with a processing layer that encompasses algorithms both for centralized and parallel processing.

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cover image ACM Other conferences
PCI '20: Proceedings of the 24th Pan-Hellenic Conference on Informatics
November 2020
433 pages
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Published: 04 March 2021

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Author Tags

  1. Spatio-textual data
  2. big data
  3. indexing
  4. processing

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PCI 2020
PCI 2020: 24th Pan-Hellenic Conference on Informatics
November 20 - 22, 2020
Athens, Greece

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Overall Acceptance Rate 190 of 390 submissions, 49%

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