Data as a science output

Open data as part of open science: Archiving & sharing research data

Making primary research data generated during the research process openly accessible is part of open science. Openness builds trust and engagement in science - research data form the raw fuel of science and greater transparency of all aspects of the research process is fundamental to the integrity of research outputs. Openness promotes innovation - many datasets have a significant re-use and re-purposing value beyond the original research.

The FAIR principles are a useful framework for thinking about sharing data in a way that will enable maximum use and reuse.

Properly publishing a research dataset in its own right means it is recognised as a science output, can be cited in science publications to acknowledge the data creators and optionally peer-reviewed through Data Journals

Proper plans should be made and recorded in a Data Management Plan (DMP) to ensure that these data are adequately safeguarded, and an audit trail provided for future re-use and re-purposing if appropriate.

How to share research data

NERC requires all environmental data of long-term value, generated from its funding, to be offered for archiving with one of its data centres. Archiving and sharing data through a NERC Data Centre guarantees secure storage, version integrity, discoverability and access of both data and the documentation that describes the data sufficiently for re-use or re-purposing, in perpetuity, and provides a DOI for the dataset. Archiving and sharing data through this approach is what is meant by 'publishing data'.

Sharing research data:

  • encourages scientific enquiry and debate
  • enables scrutiny of research outcomes
  • facilitates research beyond the scope of the original research
  • leads to new collaborations between data users and data creators
  • increases the impact and visibility of research
  • reduces the cost of duplicating data collection
  • provides important resources for education and training
  • encourages the improvement and validation of research methods
  • promotes the research that created the data and its outcomes
  • can provide a direct credit to the researcher as a research output in its own right

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