Good Data Can Be Better Data - How Data Management Maturity Can Help Repositories Improve Operations, Data Quality, And Usability, Helping Researchers

Abstract:

Much earth and space science data and metadata are managed and supported by an infrastructure of repositories, ranging from large agency or instrument facilities, to institutions, to smaller repositories including labs. Scientists face many challenges in this ecosystem both on storing their data and in accessing data from others for new research. Critical for all uses is ensuring the credibility and integrity of the data and conveying that and provenance information now and in the future. Accurate information is essential for future researchers to find (or discover) the data, evaluate the data for use (content, temporal, geolocation, precision) and finally select (or discard) that data as meeting a "fit-for-purpose" criteria. We also need to optimize the effort it takes in describing the data for these determinations, which means making it efficient for the researchers who collect the data.  At AGU we are developing a program aimed at helping repositories, and thereby researchers, improve data quality and data usability toward these goals. AGU has partnered with the CMMI Institute to develop their Data Management Maturity (DMM) framework within the Earth and space sciences. The CMMI DMM framework guides best practices in a range of data operations, and the application of the DMM, through an assessment, reveals how repositories and institutions can best optimize efforts to improve operations and functionality throughout the data lifecycle and elevate best practices across a variety of data management operations. Supporting processes like data operations, data governance, and data architecture are included.   An assessment involves identifying accomplishment, and weaknesses compared to leading practices for data management. Broad application of the DMM can help improve quality in data and operations, and consistency across the community that will facilitate interoperability, discovery, preservation, and reuse.
Good data can be better data. Consistency results in sustainability.