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International Conference on Web Engineering

ICWE 2022: Web Engineering pp 162–176Cite as

FAIRification of Citizen Science Data Through Metadata-Driven Web API Development

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

Abstract

Citizen Science (CS) implies a collaborative process to encourage citizens to collect data in CS projects and platforms. Unfortunately, these CS initiatives do not follow metadata nor data-sharing standards, which hampers their discoverability and reusability. To improve this scenario in CS is crucial to consider FAIR (Findability, Accessibility, Interoperability and Reusability) guidelines. Therefore, this paper defines a FAIRification process (i.e. make CS initiatives more FAIR compliant) which maps metadata of CS platforms’ catalogues to DCAT and generates Web Application Programming Interfaces (APIs) for improving CS data discoverability and reusability in an integrated approach. An experiment in a CS platform with different CS projects shows the performance and suitability of our FAIRification process. Specifically, the validation of the DCAT metadata generated by our FAIRification process was conducted through a SHACL standard validator, which emphasises how the process could boost CS projects to become more FAIR compliant.

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Notes

  1. 1.

    https://scistarter.org/.

  2. 2.

    https://www.zooniverse.org/.

  3. 3.

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

  4. 4.

    https://citizenscience.org/get-involved/working-groups/data-and-metadata-working-group/.

  5. 5.

    https://scistarter.org/.

  6. 6.

    https://scistarter.org/street-story-give-your-input-on-safe-streets.

  7. 7.

    https://data.europa.eu/.

  8. 8.

    https://github.com/ralvarezluna/csdatalab-apigen.

  9. 9.

    https://scistarter.org/api.

  10. 10.

    https://www.wikidata.org/wiki/Q1093434.

  11. 11.

    http://metadata.un.org/sdg.

  12. 12.

    https://github.com/Informasjonsforvaltning/datacatalogtordf.

  13. 13.

    https://www.w3.org/TR/vocab-dcat-2/#Class:Data_Service.

  14. 14.

    https://pypi.org/project/oastodcat/.

  15. 15.

    https://www.w3.org/TR/shacl/.

  16. 16.

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

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Acknowledgement

This research work has been partially funded by the Proyecto Habana 2021 and by project GVA-COVID19/2021/103 funded by Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital de la Generalitat Valenciana.

Author information

Authors and Affiliations

  1. University of Informatics Sciences, Havana, Cuba

    Reynaldo Alvarez & Hector Raúl González Diez

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

    César González-Mora, José Zubcoff, Irene Garrigós & Jose-Norberto Mazón

Authors
  1. Reynaldo Alvarez
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  2. César González-Mora
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  3. José Zubcoff
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  4. Irene Garrigós
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  5. Jose-Norberto Mazón
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  6. Hector Raúl González Diez
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Corresponding author

Correspondence to Reynaldo Alvarez .

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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Alvarez, R., González-Mora, C., Zubcoff, J., Garrigós, I., Mazón, JN., González Diez, H.R. (2022). FAIRification of Citizen Science Data Through Metadata-Driven Web API Development. 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_11

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  • DOI: https://doi.org/10.1007/978-3-031-09917-5_11

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  • Online ISBN: 978-3-031-09917-5

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