Provoking a Cultural Shift in Data Quality

Ecological studies require quality data to describe the nature of ecological processes and to advance understanding of ecosystem change. Increasing access to big data has magnified both the burden and the complexity of ensuring quality data. The costs of errors in ecology include low use of data, in...

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Bibliographic Details
Published in:Bioscience 2021-06, Vol.71 (6), p.647-657
Main Authors: MCCORD, SARAH E., WEBB, NICHOLAS P., VAN ZEE, JUSTIN W., BURNETT, SARAH H., CHRISTENSEN, ERICA M., COURTRIGHT, ERICHA M., LANEY, CHRISTINE M., LUNCH, CLAIRE, MAXWELL, CONNIE, KARL, JASON W., SLAUGHTER, AMALIA, STAUFFER, NELSON G., TWEEDIE, CRAIG
Format: Article
Language:English
Subjects:
Big Data
Ecological research
Ecological studies
Environmental changes
Professional Biologist
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Summary:Ecological studies require quality data to describe the nature of ecological processes and to advance understanding of ecosystem change. Increasing access to big data has magnified both the burden and the complexity of ensuring quality data. The costs of errors in ecology include low use of data, increased time spent cleaning data, and poor reproducibility that can result in a misunderstanding of ecosystem processes and dynamics, all of which can erode the efficacy of and trust in ecological research. Although conceptual and technological advances have improved ecological data access and management, a cultural shift is needed to embed data quality as a cultural practice. We present a comprehensive data quality framework to evoke this cultural shift. The data quality framework flexibly supports different collaboration models, supports all types of ecological data, and can be used to describe data quality within both short- and long-term ecological studies.
ISSN:0006-3568
1525-3244
DOI:10.1093/biosci/biab020