Data Asset Framework

The Data Asset Framework (formerly the Data Audit Framework) provides organisations with the means to identify, locate, describe and assess how they are managing their research data assets.

DAF combines a set of methods with an online tool to enable data auditors to gather this information. DAF will help ensure that research data produced in UK Higher Education Institutions is preserved and remains accessible in the long term.

Background

Vast quantities of data are being created by researchers in UK higher education institutions, however few institutions have formal strategies in place for curating these research outputs. Moreover there appears in many institutions to be a lack of awareness as to what data are held and whether they are being managed. If institutions are to realise the full potential value of their data through its reuse they must be able to establish quickly and easily an overview of holdings and the policies and practices in place to manage them.

In response to these concerns the JISC issued a call for proposals to develop and implement a Data Audit Framework. We, the DCC, answered the call and a project was funded to produce an audit methodology, online tool and registry. Four implementation projects [external] were also funded to test the toolkit and promote its uptake. These are based at the University of Edinburgh, Imperial College, King's College and University College London.

Methodology

DAF recommends that audits of research data assets proceed as a four step process:

  • In the planning stage the purpose and scope of the audit is defined. Preliminary research is conducted and meetings scheduled to optimise time spent with the organisation's staff.
  • The purpose of the second stage, identifying research data, is to establish what data assets exist and classify them according to their anticipated value to the organisation. The classification step determines the scope of further audit activities, as only those data most important for your purposes will be assessed in greater detail in Stage 3, assessing management of data.
  • The information collected in Stage 3 will assist auditors to identify weaknesses in data policy and current data creation and curation procedures. This will provide the basis of recommendations in the final stage of the audit.
  • The knowledge gained from the audit will enable organisations to improve data management.

See the DAF Methodology document [external PDF] and diagram for further details.

An Implementation Guide [external PDF] collating the lessons of DAF pilot studies is also available. The Guide provides practical usage tips and example questionnaires and interviews frameworks used in data surveys.

The DAF online tool [external] may be useful for those who wish to construct a registry of data assets as part of an audit.