Abstract
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.
Highlights
From commercial users in the private sector to researchers and educators in the public sector, digital environmental data users are asking for data to be dependable in terms of quality and production sustainability, to be from credible, secure, and authoritative sources, to be and publicly accessible online, and to be usable in a standardbased common data format with relevant documentation
This paper presents a stewardship maturity assessment model in the form of a matrix for digital environmental datasets
Modelers need to know and understand the upstream data quality management practices applied to their input datasets to help improve their model projections and better quantify the uncertainty associated with those projections, especially the uncertainty stemming from the quality of the observations (US CLIVAR Scientific Steering Committee, 2013)
Summary
From commercial users in the private sector to researchers and educators in the public sector, digital environmental data users are asking for data to be dependable in terms of quality and production sustainability, to be from credible, secure, and authoritative sources, to be and publicly accessible online, and to be usable in a standardbased common data format with relevant documentation. There is no systematic framework to assess the vigor of stewardship practices applied to individual environmental datasets or to provide consistent information on data quality, data integrity and usability to users and stakeholders (Peng & Privette, 2014). The product maturity assessment model described by Bates and Privette (2012) for individual climate data products is one of the few maturity models that explicitly address data quality It measures the readiness of long-term climate data records for the transition from research to operation over six categories: software, metadata, documentation, product validation, public access, and utility. This provides us with a more progressive and representative 5-level scale structure
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