Abstract
Assessing the stewardship maturity of individual datasets is an essential part of ensuring and improving the way datasets are documented, preserved, and disseminated to users. It is a critical step towards meeting U.S. federal regulations, organizational requirements, and user needs. However, it is challenging to do so consistently and quantifiably. The Data Stewardship Maturity Matrix (DSMM), developed jointly by NOAA’s National Centers for Environmental Information (NCEI) and the Cooperative Institute for Climate and Satellites–North Carolina (CICS-NC), provides a uniform framework for consistently rating stewardship maturity of individual datasets in nine key components: preservability, accessibility, usability, production sustainability, data quality assurance, data quality control/monitoring, data quality assessment, transparency/traceability, and data integrity. So far, the DSMM has been applied to over 800 individual datasets that are archived and/or managed by NCEI, in support of the NOAA’s OneStop Data Discovery and Access Framework Project. As a part of the OneStop-ready process, tools, implementation guidance, workflows, and best practices are developed to assist the application of the DSMM and described in this paper. The DSMM ratings are also consistently captured in the ISO standard-based dataset-level quality metadata and citable quality descriptive information documents, which serve as interoperable quality information to both machine and human end-users. These DSMM implementation and integration workflows and best practices could be adopted by other data management and stewardship projects or adapted for applications of other maturity assessment models.
Highlights
The National Oceanic and Atmospheric Administration (NOAA) is responsible for providing environmental intelligence to American citizens, businesses, and governments to enable informed decisions
The data stewardship maturity matrix (DSMM) ratings were integrated into the metadata records through a script
It became quite clear early on that the scalability of assessing, representing, and integrating DSMM ratings needs to be improved and automation is a must in order to apply the DSMM to hundreds to thousands of NOAA datasets
Summary
The National Oceanic and Atmospheric Administration (NOAA) is responsible for providing environmental intelligence to American citizens, businesses, and governments to enable informed decisions. The data stewardship maturity matrix (DSMM), developed jointly by domain (data management, technology, and science) subject matter experts (SMEs) from NOAA’s National Centers for Environmental Information (NCEI) and the Cooperative Institute for Climate and Satellites–North Carolina (CICS-NC), provides such a consistent framework. Leveraging institutional knowledge and community best practices and standards, the Figure 1: A conceptual model of the scientific data stewardship maturity matrix (DSMM) of National Centers for Environmental Information (NCEI) and the Cooperative Institute for Climate and Satellites– North Carolina (CICS-NC). And systematically capturing and integrating this data maturity information for machine and human end-users is an important part of improving data and information accessibility, usability, and interoperability Both utilizing a maturity framework and consistently capturing dataset maturity information are fairly new for Earth Science data management and stewardship. Of the entire lifecycle of the DSMM application, namely, evaluating, capturing, representing, baselining, integrating, and visualizing DSMM ratings
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