Questionnaire and reporting framework for research data management
Using best practice statements from UVa sources (Information Technology Services’ Risk Management Program and SciDaC guidelines) and the Australian National Data Service’s (ANDS) long-term sustainability scoring model, the system compares the information collected during the data interview process with these data management best practice statements.
The model then further correlates the researcher’s data management practices with the eight data management practice components developed by the SciDaC group: File Formats and Data Types, Organizing Files, Security/Storage/Backups, Funding Guidelines, Copyright & Privacy/Confidentiality, Data Documentation & Metadata, Archiving & Sharing and Citing Data.
To provide a framework for comparing and improving departmental data management practices, we took the value resulting from the average of the data management best practice statements and compared them the Crowston and Qin Capability Maturity Model (CMM). Using this model as a basis, the data management maturity levels are defined as: Level 0: Initial (this includes current practices that can be seen as counter-productive or even “risky” from a security standpoint) Level 1: Managed (the researcher begins to uniformly apply some of the lower level/easier best practices, really starting to “manage” the situation) Level 2: Defined (the researcher is further “defining” their DM practices) Level 3: Quantitatively Manage (the researcher begins to use central and outside services to manage their data) Level 4: Optimizing (the researcher are continually improving their data management practices).
The strength of the DM Vitals tool is in generating tasks customized to each researcher. These tasks can then be easily grouped into phases, creating a data management implementation plan for each researcher based on their personal data interview and subsequent information gathering. The DM Vitals assessment tool differs from the Digital Curation Center’s (DCC) CARDIO in that its focus is not on consensus and collaboration by individuals responsible for the research data (PI, IT, Data manager, etc.).
Excerpt from abstract of IDCC11 poster (Lake and Borda): http://www.dcc.ac.uk/sites/default/files/documents/IDCC11/photos/posters/UVA-DMVitals_Poster.pdf