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What is Research Data Management (RDM)

Research Data management is how you organise, structure and store the data used or generated during a research project.  It includes how you manage data on a day-to-day basis during the research project and what happens to the data when your research is concluded.

Reasons to manage your research data

  • to reduce the risk of data loss
  • facilitates collaborative working
  • enables your data to be shared and re-used for future research
  • improves the research process

What are FAIR Data Principles?

FAIR Data Principles are a set of guiding principles that have been accepted by the international community as standard in promoting open science and open research.  The principles aim to make research data Findable, Accessible, Interoperable and Reusable.

FAIR Data Principles

Findable:

  1. Data are assigned a globally unique and persistent identifier
  2. Data are described with rich metadata
  3. Data are registered or indexed in a searchable resource

Corti, L. et al. (2020) Managing and sharing research data: a guide to good practice. London: Sage.

Accessible:

  1. Metadata and data are understandable to humans and machines
  2. Data is deposited in a trustworthy repository
  3. Metadata are accessible, even when the data are no longer available 

Interoperable:

  1. Meta(data) use a formal, accessible, shared and broadly applicable language for knowledge representation
  2. Meta(data) use vocabularies that follow FAIR principles
  3. Meta(data) include qualified references to other (meta)data

Reusable:

  1. Data and collections have clear and accessible usage license
  2. Meta(data) provide accurate information on provenance
  3. Meta(data) meet domain-relevant community standards

British Library Scholarly Communications Toolkit

British Library Guide to Research Data Management