An open,efficient, and transparent spatial reproducible reporting tool for data discovery and science advice.
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Open and reproducible research practices offer a means to keep pace with rapidly expanding knowledge as science becomes increasingly data-intensive.The Science branch of Fisheries and Oceans Canada (DFO) encompasses a range of research topics yet approaches to data governance are often impeded by siloed groups and out dated workflows. Using R for coding and Git for version control,we developed a tool that generates automated reports to enable data-discovery of DFO and non-DFO information within the Maritimes region.We focus our framework on co-creation between report users,data providers,and experts to document and identify datasets along with their caveats,uncertainties,or other disclaimers.We also proactively use this as an opportunity to increase collaboration and transparency within DFO by highlighting how reproducible methods can increase efficiency and modernize workflows. Reports currently summarize over thirty datasources, with approximately twenty Reports generated thus far.Th.....
PublisherBedford Institute of Oceanography
Dartmouth, NS, Canada
Series;NrCanadian Technical Report of Fisheries and Aquatic Sciences;3495
Sustainable Development Goals (SDG)14.a
CitationStoyel, Q., Finnis, S., Gomez, C., Lazin, G., Daigle, R., Brager, L., Hamer, A., Smith, C., Beauchesne, D., Cazelles, K. and Butler, S. (2022) An open,efficient, and transparent spatial reproducible reporting tool for data discovery and science advice. Dartmouth, NS, Canada, Bedford Institute of Oceanography. 27pp. (Canadian Technical Report of Fisheries and Aquatic Sciences, 3495). DOI: http://dx.doi.org/10.25607/OBP-1869