1. Provoking a Cultural Shift in Data Quality
- Author
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Sarah E. McCord, Christine Laney, Jason W. Karl, Craig E. Tweedie, Justin W. Van Zee, Nicholas P. Webb, Amalia Slaughter, Erica M. Christensen, Connie M. Maxwell, Sarah H. Burnett, Nelson G. Stauffer, Ericha M. Courtright, and Claire Lunch
- Subjects
0106 biological sciences ,010504 meteorology & atmospheric sciences ,AcademicSubjects/SCI00010 ,Computer science ,Ecology (disciplines) ,Big data ,quality assurance ,010603 evolutionary biology ,01 natural sciences ,ecoinformatics ,Professional Biologist ,big data ,Ecoinformatics ,data quality ,Cultural practice ,AcademicSubjects/SOC02100 ,quality control ,0105 earth and related environmental sciences ,business.industry ,Data science ,Cultural shift ,data ,Ecosystem change ,Data quality ,General Agricultural and Biological Sciences ,business ,Quality assurance - Abstract
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.
- Published
- 2021