Use and Re-use of a Data Stewardship Maturity Assessment Model for Institutional Research Data Management Support
Creators: name: Peng, Ge
name: Ritchey, Nancy
name: Lief, Christina
name: Maggio, Iolanda
Publisher: name: Zenodo
Year: 2020
Subjects: Data Stewardship Maturity Matrix
FAIR
Scientific Data Management
Dataset Quality Information
Data Use and Reuse

description: The quality of a dataset is important in decision-making regarding data use. Associated quality information helps enable data use and re-use. Curating standards-based quality metadata and consistent quality descriptive information on the dataset level is fundamental for enabling data to be Findable, Accessible, Interoperable, and Reusable (FAIR) and helping establish the credibility and trustworthiness of individual data products. This effort, however, has been a difficult challenge for the data management community due to the lack of consistent assessment frameworks, processes, and workflows. Furthermore, developing and implementing assessment models requires multi-domain knowledge and close cross-disciplinary collaboration. A data maturity assessment model, in the form of a matrix, provides structure and tiered practices in producing, managing, and stewarding data products, helps better define the scope of the assessment, and allows for consistent quality ratings at a dataset level. In this presentation, we describe the progress made in use and re-use efforts of a Data Stewardship Maturity Matrix (DSMM) and demonstrate how they help organizations ensure and improve the stewardship maturity of their data.
description: IDCC2020 Poster
description: {"references": ["Peng, G., J.L. Privette, E.J. Kearns, N.A. Ritchey, and S. Ansari, 2015: A unified framework for measuring stewardship practices applied to digital environmental datasets. Data Science Journal, 13, 231 - 253. http://dx.doi.org/10.2481/dsj.14-049.", "Peng, G., A. Milan, N. Ritchey, R. P. Partee II, S. Zinn, PE. McQuinn, Lemieux III, R. Ionin, D. Collins, P. Jones, A. Jakositz, and K.S. Casey, 2019: Practical Application of a Stewardship Maturity Matrix for the NOAA OneStop Program. Data Science Journal, 18. doi:10.5334/dsj-2019-041.", "WGISS Data Stewardship Interest Group, 2017: WGISS Data stewardship maturity matrix. Document ID: CEOS.WGISS.DSIG.DSMM. Version: 1.0 26 September 2017. Available at: http://ceos.org/document_management/Working_Groups/WGISS/Interest_Groups/Data_Stewardship/White_Papers/WGISS%20Data%20M anagement%20and%20Stewardship%20Maturity%20Matrix.pdf", "WMO SMM-CD Working Group, 2019: The WMO-Wide Stewardship Maturity Matrix for Climate Data. Figshare. https://doi.org/10.6084/m9.figshare.7006028.", "WMO, 2019: Manual for High Quality Global Data Management Framework for Climate. Cg-18/Doc. 5.2(2), Annex, DRAFT 2. Available at: CEOS WGISS Data Management and Stewardship Maturity Matrix (DMSMM) The Working Group on Information Systems and Services (WGISS) of the Committee on Earth Observation Satellites (CEOS) supports the full life cycle of CEOS data management, access, and services. The DSMM has been adapted by the CEOS WGISS Data Stewardship Interest Group to help ensure that CEOS data products are compliant with the Data Management Principles Implementation Guidelines (DMP IG) for a Global Earth Observation System of Systems (GEOSS). The WGISS Data Management and Stewardship Maturity Matrix (DMSMM) has been recommended to the CEOS community for use (WGISS Data Stewardship Interest Group 2017). Data Stewardship Maturity Matrix (DSMM) DSMM Defines Measureable, Five-Level Progressive Practices in Nine Quasi-Independent Key Components NOAA OneStop Application A Data Stewardship Maturity Matrix (DSMM) has been developed by the National Centers for Environmental Information (NCEI) of the U.S. National Oceanic and Atmospheric Administration (NOAA) in collaboration with the Cooperative Institute for Climate and Satellites, North Carolina (CICS-NC), which is a partnership between NOAA and North Carolina State University (Peng et al. 2015). Leveraging institutional knowledge and community best practices and standards, the DSMM measures quantifiable stewardship practices applied to individual data products. The DSMM has been applied to over 800 datasets by the NOAA OneStop project. The tools and workflows are developed to streamline and automate the process for data stewardship maturity evaluation, ISO quality metadata curation, and DSMM ratings integration for search and discovery (Peng et al. 2019). The DSMM is now a part of the NOAA OneStop-ready process. WMO Stewardship Maturity Matrix for Climate Data (SMM-CD) (From WMO 2019) The World Meteorological Organization (WMO) is a United Nations agency specializing in weather, climate, and water with a membership of 193 member states and territories. To help WMO ensure and establish the trustworthiness of climate data, the DSMM has been integrated into the WMO Stewardship Maturity Matrix for Climate Data (SMM-CD) to provide a scored measure of the quality of the data stewardship and governance (WMO SMM-CD Working Group 2019). The SMM-CD is one of the three building blocks of the WMO High Quality Global Data Management Framework for Climate (HQ-GDMFC) which has recently been adopted by the Eighteenth World Meteorological Congress (Cg- 18) (June 2019). The HQ-GDMFC is a collaborative and inclusive framework for promoting modern standards and practices for the management of climate data and sharing assessed global climate datasets in an online WMO catalogue. http://www.wmo.int/pages/prog/wcp/wcdmp/hq-gdmfc/hq-gdmfc.php"]}