Reproducibility literature analysis - a federal information professional perspective

Authors

  • Erin Antognoli U.S. Department of Agriculture, National Agricultural Library
  • Regina L. Avila U.S. National Institute of Standards and Technology
  • Jonathan Sears United States Department of Agriculture, National Agricultural Library
  • Leighton L. Christiansen U.S. Department of Transportation, National Transportation Library, Bureau of Transportation Statistics
  • Jessica Tieman U.S. Government Publishing Office
  • Jacquelyn Hart U.S. Library of Congress, Canada & Oceania Section

DOI:

https://doi.org/10.29173/iq967

Keywords:

reproducibility, reproducibility crisis, replicability, research data, landscape analysis, culture shift

Abstract

This article examines a cross-section of literature and other resources to reveal common reproducibility issues faced by stakeholders regardless of subject area or focus. We identify a variety of issues named as reproducibility barriers, the solutions to such barriers, and reflect on how researchers and information professionals can act to address the ‘reproducibility crisis.’ The finished products of this work include an annotated list of 122 published resources and a primer that identifies and defines key concepts from the resources that contribute to the crisis.

Author Biographies

Erin Antognoli, U.S. Department of Agriculture, National Agricultural Library

Regina L. Avila, U.S. National Institute of Standards and Technology

Jonathan Sears, United States Department of Agriculture, National Agricultural Library

Leighton L. Christiansen, U.S. Department of Transportation, National Transportation Library, Bureau of Transportation Statistics

Jessica Tieman, U.S. Government Publishing Office

Jacquelyn Hart, U.S. Library of Congress, Canada & Oceania Section

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Published

2020-06-29

How to Cite

Antognoli, E., Avila, R. L., Sears, J., Christiansen, L. L., Tieman, J., & Hart, J. (2020). Reproducibility literature analysis - a federal information professional perspective. IASSIST Quarterly, 44(1-2), 1–26. https://doi.org/10.29173/iq967