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Powering Soft Querying in J-CO-QL with JavaScript Functions

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16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021) (SOCO 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1401))

Abstract

The availability of large data sets represented as JSON documents is demanding for powerful tools able to integrate and query them. The J-CO Framework is a research prototype under development at University of Bergamo (Italy), specifically devised to provide practical tools to manage possibly large JSON data sets. Its query language, named J-CO-QL, provides constructs to evaluate the belonging of documents to fuzzy sets, so as to perform soft queries on JSON documents. In this paper, we present a real case study that shows how a novel construct, which enables defining JavaScript functions within J-CO-QL queries, provides users with an even improved possibility to personalize soft operators used to evaluate membership degrees.

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Notes

  1. 1.

    Regione Lombardia Open Data Portal - https://www.dati.lombardia.it/.

  2. 2.

    Socrata platform - https://dev.socrata.com/.

  3. 3.

    Haversine formula to calculate distance between two geo-referenced points https://en.wikipedia.org/wiki/Haversine_formula.

  4. 4.

    Regione Lombardia Open Data Portal. Air-quality stations - https://www.dati.lombardia.it/Ambiente/Stazioni-qualit-dell-aria/ib47-atvt.

  5. 5.

    Github repository of the J-CO Framework - https://github.com/zunstraal/J-Co-Project.

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Author information

Authors and Affiliations

  1. University of Bergamo, Viale Marconi 5, 24044, Dalmine, BG, Italy

    Paolo Fosci & Giuseppe Psaila

Authors
  1. Paolo Fosci
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  2. Giuseppe Psaila
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Corresponding author

Correspondence to Giuseppe Psaila .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Hugo Sanjurjo González

  2. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Iker Pastor López

  3. Faculty of Engineering, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  4. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  5. BISITE Research Group, University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Fosci, P., Psaila, G. (2022). Powering Soft Querying in J-CO-QL with JavaScript Functions. In: Sanjurjo González, H., Pastor López, I., García Bringas, P., Quintián, H., Corchado, E. (eds) 16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021). SOCO 2021. Advances in Intelligent Systems and Computing, vol 1401. Springer, Cham. https://doi.org/10.1007/978-3-030-87869-6_20

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