How to make your data FAIR

This page will show you how you can make your research data more FAIR by taking you through six FAIRification practices 

  1. Documentation 
  2. File formats 
  3. Metadata 
  4. Access to data 
  5. Persistent identifiers 
  6. Data licences 
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Case introductions

Throughout the FAIRification subpages, four research projects are used as examples of how you can make your research data more FAIR. You will see short interview clips of researchers in Engineering, Humanities, Health Sciences, and Social Sciences. The researchers share their methods and solutions for problems specific to quantitative data, qualitative data, and sensitive data. Watch all four case introductions - or just the ones you expect will be most relevant to your research field and data type.  

Quantitative data

Qualitative data

Sensitive quantitative data

Sensitive qualitative data

In summary...

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You make your research data findable for your collaborators and the rest of the world by: 

  • Publishing your data and/or metadata in a searchable resource such as a repository like Dataverse, Zenodo or Figshare that assigns a persistent identifier

  • Including rich accurate machine-readable descriptive metadata and keywords to your data, preferably according to a community-specific metadata standard (e.g. Dublin Core) or ontology
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You make your research data accessible by: 

  • Attaching a data licence or clear data accessibility statement in your openly available administrative metadata 

  • Ensuring your data are archived in long-term storage and retrievable by their persistent identifier using a standard protocol

  • Giving access to the metadata, even if the data are closed
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You make your research data interoperable by: 

  • Including sufficient and standardised structural metadata in accordance with your research community’s standard controlled vocabulary or ontology 

  • Including use of common standards, terminologies, vocabularies, ontologies and taxonomies for the data 

  • Preferring open, long-term viable file formats for your data and metadata 

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You make your research data reusable by: 

  • Attaching all the relevant contextual information required for re-use in either the documentation or metadata attached to your data 

  • Including sufficient and standardised structural metadata in accordance with your research community’s standard controlled vocabulary or ontology 

  • Preferring open, long-term viable file formats for your data and metadata

  • Applying a machine-readable data licence