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FAIRification of Citizen Science Data

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Web Engineering (ICWE 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13362))

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Abstract

Citizen Science (CS) initiatives encourage citizens to collect local data, contributing to knowledge creation and scientific development. However, these CS initiatives do not follow metadata nor data-sharing standards, which hampers their discoverability and reusability out of the scope of them. To improve this scenario in CS is crucial to consider Findable, Accessible, Interoperable and Reusable (FAIR) guidelines for research data sharing. This work proposes a FAIRification process (i.e. making CS initiatives more FAIR compliant), enhancing data sharing capacities in the CS context. It will be considered the adoption of Web standards, Web application programming interfaces (APIs) and Web augmentation. This approach contributes to the production of FAIR data in CS for data consumers. As preliminary results this paper explains the FAIRification process. The research objectives and plan are also presented.

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Notes

  1. 1.

    https://www.w3.org/TR/vocab-dcat-3/.

  2. 2.

    https://core.citizenscience.org/.

  3. 3.

    https://data.vlaanderen.be/shacl-validator/.

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Acknowledgements

This research work has been partially funded by the Proyecto Habana 2021.

Author information

Authors and Affiliations

  1. University of Informatics Sciences, Havana, Cuba

    Reynaldo Alvarez Luna & Hector Gonz

  2. Department of Languages and Computing Systems, University of Alicante, Alicante, Spain

    José Zubcoff & Irene Garrigós

Authors
  1. Reynaldo Alvarez Luna
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  2. José Zubcoff
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  3. Irene Garrigós
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  4. Hector Gonz
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Corresponding author

Correspondence to Reynaldo Alvarez Luna .

Editor information

Editors and Affiliations

  1. Polytechnic University of Bari, Bari, Italy

    Tommaso Di Noia

  2. Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

    In-Young Ko

  3. Johannes Kepler University Linz, Linz, Austria

    Markus Schedl

  4. Polytechnic University of Bari, Bari, Italy

    Carmelo Ardito

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Luna, R.A., Zubcoff, J., Garrigós, I., Gonz, H. (2022). FAIRification of Citizen Science Data. In: Di Noia, T., Ko, IY., Schedl, M., Ardito, C. (eds) Web Engineering. ICWE 2022. Lecture Notes in Computer Science, vol 13362. Springer, Cham. https://doi.org/10.1007/978-3-031-09917-5_34

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  • DOI: https://doi.org/10.1007/978-3-031-09917-5_34

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-09917-5

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