Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets

Abstract

Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data and need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision- and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Community practical guidelines will allow for global access and harmonization of quality information at the level of individual Earth science datasets and support open science.

Stewardship Maturity Assessment Tools for Modernization of Climate Data Management

“…As the SMM-CD is domain specific, and has been developed for WMO Member countries, it tries to capture the current stewardship practices applied to individual datasets of Earth Science systems. Providing data stewardship maturity information utilizing the SMM-CD primarily supports the Transparency, Responsibility and User focus aspects of the TRUST principles for data repositories (Peng et al, 2020).…”