Data Science Journal (Jan 2015)

A Unified Framework for Measuring Stewardship Practices Applied to Digital Environmental Datasets

  • Ge Peng,
  • Jeffrey L Privette,
  • Edward J Kearns,
  • Nancy A Ritchey,
  • Steve Ansari

DOI
https://doi.org/10.2481/dsj.14-049
Journal volume & issue
Vol. 13
pp. 231 – 253

Abstract

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This paper presents a stewardship maturity assessment model in the form of a matrix for digital environmental datasets. Nine key components are identified based on requirements imposed on digital environmental data and information that are cared for and disseminated by U.S. Federal agencies by U.S. law, i.e., Information Quality Act of 2001, agencies’ guidance, expert bodies’ recommendations, and users. These components include: preservability, accessibility, usability, production sustainability, data quality assurance, data quality control/monitoring, data quality assessment, transparency/traceability, and data integrity. A five-level progressive maturity scale is then defined for each component associated with measurable practices applied to individual datasets, representing Ad Hoc, Minimal, Intermediate, Advanced, and Optimal stages. The rationale for each key component and its maturity levels is described. This maturity model, leveraging community best practices and standards, provides a unified framework for assessing scientific data stewardship. It can be used to create a stewardship maturity scoreboard of dataset(s) and a roadmap for scientific data stewardship improvement or to provide data quality and usability information to users, stakeholders, and decision makers.

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