Data Quality in Citizen Science

Bálint Balázs; Peter Mooney; Eva Nováková; Lucy Bastin; Jamal Jokar Arsanjani

doi:10.1007/978-3-030-58278-4_8

Data Quality in Citizen Science

Bálint Balázs, Peter Mooney, Eva Nováková, Lucy Bastin, Jamal Jokar Arsanjani

Research output: Chapter in Book/Published conference output › Chapter (peer-reviewed) › peer-review

Abstract

This chapter discusses the broad and complex topic of data quality in citizen science – a contested arena because different projects and stakeholders aspire to different levels of data accuracy. In this chapter, we consider how we ensure the validity and reliability of data generated by citizen scientists and citizen science projects. We show that this is an essential methodological question that has emerged within a highly contested field in recent years. Data quality means different things to different stakeholders. This is no surprise as quality is always a broad spectrum, and nearly 200 terms are in use to describe it, regardless of the approach. We seek to deliver a high-level overview of the main themes and issues in data quality in citizen science, mechanisms to ensure and improve quality, and some conclusions on best practice and ways forwards. We encourage citizen science projects to share insights on their data practice failures. Finally, we show how data quality assurance gives credibility, reputation, and sustainability to citizen science projects.

Original language	English
Title of host publication	The Science of Citizen Science
Publisher	Springer
Pages	139–157
ISBN (Electronic)	978-3-030-58278-4
ISBN (Print)	978-3-030-58277-7
DOIs	https://doi.org/10.1007/978-3-030-58278-4_8
Publication status	Published - 12 Jan 2021

Publication series

Name	The Science of Citizen Science

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10.1007/978-3-030-58278-4_8Licence: CC BY 4.0

2021_Book_TheScienceOfCitizenScience
Licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Final published version, 8.51 MBLicence: CC BY 4.0

Cite this

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Data Quality in Citizen Science

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