Standard data management practices

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Abstract

Accomplishing data management in a standardized and practical way begins with an understanding of what data management is. The Data Management Association defines data management as “the development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles” (Earley 2017). In this chapter, we present the tenets of data management in the context of fisheries for our target audience: fisheries biologists who may have limited formal training in data science. Experienced data managers may also benefit from the contents of this chapter, but the authors’ goal is to enhance and improve those activities that produce data, from project planning to acquiring data through field sampling, to cataloging and analyzing data, to sharing and archiving data.

Suggested Citation

Krogman, R., Bayer, J.M., Cooper, A., Kopaska, J., Leonard, N., Pritt, J., Roe, C., Tracy, E., Venturelli, P.A., Wieferich, D.J., and Infante, D.M., 2024, Standard data management practices, chap. 15 of Standard methods for sampling North American freshwater fishes, second edition, p. 339-368, https://doi.org/10.47886/9781934874769.ch15.

Publication type Book chapter
Publication Subtype Book Chapter
Title Standard data management practices
Chapter 15
DOI 10.47886/9781934874769.ch15
Year Published 2024
Language English
Publisher American Fisheries Society
Contributing office(s) Core Science Analytics and Synthesis, Forest and Rangeland Ecosys Science Center
Description 30 p.
Larger Work Type Book
Larger Work Subtype Monograph
Larger Work Title Standard methods for sampling North American freshwater fishes, second edition
First page 339
Last page 368
Additional publication details