Standard Methods for Sampling North American Freshwater Fishes, second edition

Chapter 15: Standard Data Management Practices

Rebecca M. Krogman, Jennifer M. Bayer, Arthur R. Cooper, Jeff Kopaska, Nancy J. Leonard, Jeremy J. Pritt, Colleen Roe, Erin E. Tracy, Paul Venturelli, Daniel Wieferich, and Dana M. Infante

doi: https://doi.org/10.47886/9781934874769.ch15

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.