Good data practice – five factors for success

New Springer nature white paper draws on several reports to recommend practical ways to accelerate data sharing.


“Data sharing and good data management has been found to make research studies more productive, more likely to be cited and unlock innovation for the good of society. Data archiving, for example, can double the publication output of research projects, and has been associated with an increase in the citation impact of research papers by as much as 50 per cent. According to a new report for the European Commission, the minimum cost to the EU of poor data practice is €10.2 billion per year.”

Throughout 2018 Springer Nature conducted and participated in several research projects that explored researcher behaviour and attitudes to data management and sharing. 

Some of the key issues raised by the research projects include:

  • 27% of researchers do not know how they would meet the costs of making their research data openly available.
  • 65% of researchers feel there is not enough training, support and advice about data management.
  • 58% of researchers don't think they get sufficient credit for sharing research data.
  • 79% of respondents said they would be willing to reuse open data in the future.

The new white paper now builds on these findings to recommend five factors that must be in place to facilitate and accelerate data sharing.

What links these five factors is that each relies on collaboration by a number of different stakeholders – no single factor can be achieved by stakeholders working in isolation.

Factor 1 – Clear policy

Funders, research communities, institutions, journals and publishers must all set unambiguous and specific requirements for data management and sharing to drive a shift in researcher behaviour.

Factor 2 – Better credit

Making data sharing worth the time investment for researchers by ensuring formal recognition through data citations and inclusion in research assessments.

Factor 3 - Explicit funding for data management, data sharing and data publishing

Because policy without funding is unlikely to encourage data sharing.

Factor 4 - Practical help

To support researchers in organising their data, finding appropriate repositories and easier methods of sharing data.

Factor 5 – Training and education

Resources to build skills and knowledge and to communicate the benefits of data sharing.

The white paper, along with the underlying data, can be downloaded here