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Mobility Data Analytics with KNOT: The KNime mObility Toolkit

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Web and Wireless Geographical Information Systems (W2GIS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13912))

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Abstract

Developments in Web and Wireless technologies have enabled the diffusion of large volumes of geospatial mobility data, and new challenges and opportunities have emerged for the GIScience research community, interested in extracting knowledge from these data.

In most data analytics scenarios, well-known analytics platforms, such as KNIME or RapidMiner, offer practical general-purpose tools to data analysts. However, when dealing with mobility data, these platforms provide only limited support to some peculiar geospatial data manipulation tasks, thus forcing researchers and practitioners to manually implement significant portions of their pipelines, hindering productivity and replicability of the results.

This paper presents a solution we are currently working on to support mobility data analysis. Our prototype, which we called KNOT (KNime mObility Toolkit), extends the KNIME Analytics Platform with a collection of new components specifically designed to support processing steps typical of mobility data, including map-matching, trajectory partitioning, and road network coverage analysis. To show the effectiveness of these components, we report also on how we applied them to perform a realistic analytical task on a real-world massive mobility dataset.

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Notes

  1. 1.

    https://www.knime.com/.

  2. 2.

    https://rapidminer.com/.

  3. 3.

    https://www.ibm.com/cloud/watson-studio.

  4. 4.

    https://github.com/luistar/knot.

  5. 5.

    https://github.com/luistar/knot.

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Authors and Affiliations

  1. Università degli Studi di Napoli Federico II, Dipartimento di Ingegneria Elettrica e Tecnologie dell’Informazione (DIETI), Via Claudio 21, Naples, 80125, Italy

    Sergio Di Martino, Nicola Mazzocca, Franca Rocco Di Torrepadula & Luigi Libero Lucio Starace

Authors
  1. Sergio Di Martino
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  2. Nicola Mazzocca
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  3. Franca Rocco Di Torrepadula
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  4. Luigi Libero Lucio Starace
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Corresponding author

Correspondence to Luigi Libero Lucio Starace .

Editor information

Editors and Affiliations

  1. Université Laval, Québec, QC, Canada

    Mir Abolfazl Mostafavi

  2. INSA, Saint Etienne du Rouvray Cedex, France

    Géraldine Del Mondo

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Di Martino, S., Mazzocca, N., Di Torrepadula, F.R., Starace, L.L.L. (2023). Mobility Data Analytics with KNOT: The KNime mObility Toolkit. In: Mostafavi, M.A., Del Mondo, G. (eds) Web and Wireless Geographical Information Systems. W2GIS 2023. Lecture Notes in Computer Science, vol 13912. Springer, Cham. https://doi.org/10.1007/978-3-031-34612-5_6

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  • DOI: https://doi.org/10.1007/978-3-031-34612-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34611-8

  • Online ISBN: 978-3-031-34612-5

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