Benefits of data sharing

Dr Abdoul Gadiri Diallo, Health Clinic, Guinea
health worker writing
Residents of Kashadaha village in Bangladesh, Credit Dominic Chavez, World Bank

Making your data available for reuse benefits you as well as the field 

Benefits for data contributors

Making your data available for reuse via IDDO:

  • Ensures long-term, secure storage for your data
  • Meets data sharing requirements from funders and journals
  • Increases the visibility of your work: anyone using IDDO-hosted datasets with a Digital Object Identifier is required to cite this DOI
  • Give you the opportunity to participate in further collaborations and publications, receiving academic credit, direct citation and tangible metrics where appropriate

Making data sharing F.A.I.R

We follow the the FAIR Guiding Principles for scientific data management and stewardship’: aimed at increasing the Findability, Accessibility, Interoperability, and Reuse of data.

We aim to assign and promote persistent digital object identifies (DOIs) for datasets in the IDDO inventory, to provide academic credit to the data contributor. DOIs also make the data more findable, and we also include information about how data are shared and licensed in the DOI information – making the data more Accessible and Reusable.  

We are registered with FAIRsharing.org and re3data.org. 

How data reuse benefits the field

  • Maximises the utility and impact of the data collected for research makes best use of the significant contributions made by trial participants, and ultimately contributes to improving public health.
  • Reusing existing data for secondary analyses addresses gaps in knowledge without enrolling more patients, thus reducing overall patient risk.
  • Pooling data can increase the strength of evidence relating to populations underserved by research, such as children, pregnant women and patients with comorbidities. Data can be combined to maximise statistical power in meta-analyses and used to explore questions that can’t be answered by individual trials, such as variable sub-population responses, regional diversity or changes over time