A Stewardship Maturity Matrix for Assessing the State of Environmental Data Quality and Usability Practices

Sustained environmental data products are used widely in research, modeling and decision support systems. For example, weather and seasonal-to-interannual climate prediction relies in part on accurate initial conditions that are usually provided via data assimilation systems utilizing model systems and available observation. Although many operational products are mature and well-validated, the archived records and their routine updates may – or may not -- be rigorously assessed for ongoing quality and usability. Data Stewardship refers to the quality and usability practices applied to data products. Stewardship practices, such as data quality assurance (DQA) and monitoring (DQM), can provide downstream users with information that can, e.g., inform data screening processes in assimilation systems or provide a basis for scientific defensibility of results and conclusions. Although many expert groups (e.g., National Academy of Sciences, Global Climate Observing System) and even U.S. Law advocate strong environmental data stewardship, there is no systematic framework for assessing stewardship practices, let alone for providing consistent information to users and stakeholders. In this presentation, we describe a new stewardship framework based on NOAA's maturity matrix concept (Bates and Privette, 2012). Based on published guidance from expert bodies, the stewardship matrix defines the principal components of data stewardship, as well as a graduated scale for each component with which to assess the rigor, quality or value of practices applied to a given data set or product. This tool should be helpful to modelers, decision support system users, and scientists seeking to better understand the upstream data management practices applied to their input data sets.