Findings
The DAF methodology was tested in four pilot audits by the development team partners. The online tool that was subsequently developed was tested by King's College London. The findings from these early audits and the tool test are provided below, along with the findings of pilot implementation projects and early adopters.
DAF Development project findings
Lessons learned from the intial four pilot audits
A scenario-based test report providing feedback on the usability of the online tool from the auditor's perspective
The DAF Development project final report
Findings from pilot implementations and early adopters
University of Edinburgh pilot implementation project final report
Imperial College pilot implementation project final report
University College London pilot implementation project final report
A University of Oxford case study on using the Data Audit Framework
The Southampton data survey - a report on using DAF as part of the DataShare project
Details for a preservation policy study undertaken at the University of Glasgow, prompted by DAF findings and emerging policy drivers.
Data Services for the Sciences: A Needs Assessment - an article by Brian Westra of the University of Oregon about using DAF and data curation profiles to scope user needs.
Use of DAF within the Sudamih project - a 2010 report on using DAF in the JISC Managing Research Data programme
A DAF investigation of research data management practices at the University of Northampton - a project in 2010 which investigated the types of data held at Northampton, researchers' existing data management practices and the risks associated with these practices.
Audits have provided useful insights into data managment practices and helped identify areas in which staff require support. The volume of data being created and held by HE instituions makes it impractical to complete comprehensive audits. As such, emphasis has mostly been placed on the assessment stage to survey staff working practices and identify risks and where inventories have been created, sampling methods have been used. The scope of each audit - i.e what consitutes a 'data asset' and level of granularity to adopt - as well as approaches used, varied significantly to suit the underlying aims. The methodology was designed to be non-prescriptive and flexible to ensure it could be applied in such different ways.
The main issues researchers were found to face centred on storage shortages, lack of data policies and procedures, and the responsibility of long-term curation when repository support, skilled staff and resourcing was not available. These findings have been summarised for a paper in the IJDC Useful suggestions and examples of how to implement the methodology have been collated in the implementation guide.
Some longer-term outcomes of the development project have emerged. The Universities of Glasgow and Edinburgh have both built on their early DAF work and are now undertaking projects in the JISC Managing Research Data programme to offer data management training options and support infrastructures in response to the needs identified.
Data Asset Framework
