Practical Application of a Data Stewardship Maturity Matrix for the NOAA OneStop Project

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 the paper that we are presenting you today.

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.

Peng, G., Milan, A., Ritchey, N.A., Partee II, R.P., Zinn, S., McQuinn, E., Casey, K.S., Lemieux III, P., Ionin, R., Jones, P., Jakositz, A. and Collins, D., 2019. Practical Application of a Data Stewardship Maturity Matrix for the NOAA OneStop Project. Data Science Journal, 18(1), p.41.

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