Data Asset Framework

Develop processes to manage research data produced in your higher education institution.

Product FeaturesApplicable DisciplinesTerms & Conditions

Assess how well your institution manages the data produced by its researchers using the Data Asset Framework.

The Data Asset Framework (DAF) provides an organisation with the means to identify, locate, describe and assess how it is managing its research data assets. The aim is to ensure that research data are preserved and remain accessible in the long term.

Data Asset Framework logo

The Data Asset Framework offers a set of methods to gather the information, views and experiences you need to scope research data support services.

DAF recommends a four-stage process:

  1. Planning, defining the purpose and scope of the survey and conducting preliminary research.
  2. Identifying what data assets exist and classifying them to determine where to focus efforts for more in-depth analysis.
  3. Considering the information lifecycle to understand researchers’ workflows and identify weaknesses in data creation and curation practices.
  4. Collating the information collected and developing recommendations for improving data management.

The DAF website has more information including a downloadable implementation guide (PDF) which provides practical tips and example questionnaires and interviews which have been used in data surveys.

Training and facilitation in using DAF is available (at competitive rates) from the Digital Curation Centre.

More about DAF

Free or paid for

Free

Product Features

  • Framework to assess management of research data
  • Implementation Guide available as a downloadable PDF
  • Designed for higher education institutions

Applicable Disciplines

  • Agricultural and Biological Sciences
  • Arts and Humanities 
  • Biochemistry, Genetics and Molecular Biology 
  • Business, Management and Accounting 
  • Computer Sciences 
  • Energy
  • Health Professions 
  • Material Science
  • Life Sciences
  • Neuroscience 
  • Physics and Astronomy 
  • Chemical Engineering 
  • Earth and Planetary Sciences
  • Engineering
  • Immunology and Microbiology 
  • Mathematics
  • Nursing
  • Psychology 
  • Geography
  • Chemistry
  • Economics, Econometrics and Finance 
  • Environmental Science 
  • Medicine 
  • Pharmacology, Toxicology and Pharmaceutics 
  • Social Sciences
  • Veterinary 

Terms & Conditions

Licensed under Creative Commons Attribution 4.0 International

Skills Required

  • Significant experience of the local research support infrastructure
  • A good understanding of the wider issues associated with supporting data management

Support and Training Available

  • Online documentation
  • Training and facilitation offered at competitive rates by the Digital Curation Centre
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