0556712 - ÚGN 2023 RIV CH eng M - Část monografie knihy
Balázs, B. - Mooney, P. - Nováková, Eva - Bastin, L. - Arsanjani, J. J.
Data Quality in Citizen Science.
The Science of Citizen Science. 1. Cham: Springer, 2021 - (Vohland, K.; Land-Zandstra, A.; Ceccaroni, L.; Lemmens, R.; Perelló, J.; Ponti, M.; Samson, R.; Wagenknecht, K.), s. 139-157. ISBN 978-3-030-58277-7
Institucionální podpora: RVO:68145535
Klíčová slova: peer verification * expert verification * quality assessment
Obor OECD: Information science (social aspects)
https://link.springer.com/chapter/10.1007/978-3-030-58278-4_8

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.
Trvalý link: http://hdl.handle.net/11104/0330865