The Fisheries Information and Technology Section and the Organization of Fish and Wildlife Information Managers Guide to Swimming in the Ocean of Information

Kopaska, Jeff; Defilippi, Julie M.; Hurley, Keith L.; Krogman, Rebecca M.; Loftus, Andrew J.

doi:10.1080/03632415.2016.1199833

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2023

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Cited by 2 publications

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“…Furthermore, agency fi sheries managers may be unaware of data sets from completed historic projects, which may exist only on a single hard drive or on paper. Unfortunately, team recruitment may not solve these problems, because even recent university educations may not fully train students in data management skills (McMullin et al 2016 ) for the entire data life cycle (Kopaska et al 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Fisheries Volume 48 Number 10 October 2023

2023

Fisheries

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Fisheries Volume 48 Number 10 October 2023

2023

Fisheries

View full text Add to dashboard Cite

“…Furthermore, agency fisheries managers may be unaware of data sets from completed historic projects, which may exist only on a single hard drive or on paper. Unfortunately, team recruitment may not solve these problems, because even recent university educations may not fully train students in data management skills (McMullin et al 2016) for the entire data life cycle (Kopaska et al 2016).…”

Section: Introductionmentioning

confidence: 99%

{NCIFD} — An Internal R Package for a Fisheries Agency

2023

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We developed an R package for the Inland Fisheries Division of the North Carolina Wildlife Resources Commission to help team members share R functions and data sets. The {NCIFD} package stores several functions that were developed for agency research, including cleanBIODE(), which cleans query results from a database of standardized fish samples and imports the data into an R session. In addition, {NCIFD} stores a variety of data sets including observations from ongoing research projects, hatchery records, and administrative information. Stored in a package, data sets are instantly available for exploration and analysis in an R session, can share a common naming convention, and retain their metadata. Although developing an R package requires effort, we believe it is a useful tool that other fisheries agencies should encourage interested staff to explore. We share advice to help others get started while avoiding some missteps we encountered.

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The Fisheries Information and Technology Section and the Organization of Fish and Wildlife Information Managers Guide to Swimming in the Ocean of Information

Cited by 2 publications

References 7 publications

Fisheries Volume 48 Number 10 October 2023

Fisheries Volume 48 Number 10 October 2023

{NCIFD} — An Internal R Package for a Fisheries Agency

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