What is it about?

This paper describes the development of a capability maturity model (CMM) for RDM. The RDM CMM includes five sectins describing five key process areas for research data management: 1) data management in general; 2) data acquisition, processing, and quality assurance; 3) data description and representation; 4) data dissemination; and 5) repository services and preservation. In each section, key data management practices are organized into four groups according to the CMM’s generic processes: commitment to perform, ability to perform, tasks performed, and process assessment (combining the original measurement and verification). For each area of practice, the document provides a rubric to help projects or organizations assess their level of maturity in RDM.

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Why is it important?

There's growing awareness of the importance of managing research data and lots of advice about how to do it. This paper offers a framework that organizes that advice into different facets and also for plotting a path towards more reliable data management so that new projects do not have to invent processes from scratch.

Perspectives

This paper came out of a fruitful collaboration and brought home for me my own problems in managing data.

Kevin Crowston
Syracuse University

Read the Original

This page is a summary of: Pursuing Best Performance in Research Data Management by Using the Capability Maturity Model and Rubrics , Journal of eScience Librarianship, October 2017, University of Massachusetts Medical School,
DOI: 10.7191/jeslib.2017.1113.
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