@article {2014, title = {A Capability Maturity Model for Research Data Management}, year = {2014}, institution = {Syracuse University School of Information Studies}, address = {Syracuse, NY}, abstract = {

Objective: To support the assessment and improvement of research data management (RDM) practices to increase its reliability, this paper describes the development of a capability maturity model (CMM) for RDM. Improved RDM is now a critical need, but low awareness of {\textendash} or lack of {\textendash} data management is still common among research projects.

Methods: A CMM includes four key elements: key practices, key process areas, maturity levels, and generic processes. These elements were determined for RDM by a review and synthesis of the published literature on and best practices for RDM.

Results: The RDM CMM includes five chapters 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 chapter, key data management practices are organized into four groups according to the CMM{\textquoteright}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.

Conclusions: By helping organizations identify areas of strength and weakness, the RDM CMM provides guidance on where effort is needed to improve the practice of RDM.

}, url = {https://surface.syr.edu/istpub/184/}, author = {Jian Qin and Kevin Crowston and Arden Kirkland} }