Research Data Management Resources

(Image credit)

"Openness increases transparency and reliability, facilitates more effective collaboration, accelerates the pace of discovery, and fosters broader and more equitable access to scientific knowledge and to the research process itself."
— National Academies of Sciences, Engineering, and Medicine. 2018. Open Science by Design: Realizing a Vision for 21st Century Research. Washington, DC: The National Academies Press. https://doi.org/10.17226/25116

Transparency

• Allows data to be audited

Innovation

• Data can be reused or recombined in unexpected ways
• Data can be used to plan new studies
• New markets for services related to curation, preservation, analysis, visualization

Efficiency

• Focus resources and efforts appropriately
• Avoid repeating studies
• Avoid repeating mistakes
• Work smarter and more quickly
• Prevent loss of data - A Canadian study reported that 80% of scientific data are lost within two decades: The Availability of Research Data Declines Rapidly with Article Age  (Current Biology, 19 December 2013)

Impact

• Studies show that papers with publicly available datasets receive a higher number of citations: Data reuse and the open data citation advantage (PeerJ, 1 October 2013)

Success stories of how open data has made a difference

• From the NCBI Insights blog, 16 September 2013: "NCBI’s Open Data – A Source of Experimental Data for Important Discoveries".  This post summarizes 3 recent cases where researchers used data from GEO, PubChem, and dbGaP to make significant discoveries.
• "Sharing of Data Leads to Progress on Alzheimers", by Gina Kolata, New York Times, 12 August  2010

This paper "Nine simple ways to make it easier to (re)use your data" by Ethan P. White et al. presents 9 recommendations for scientists on how to to make their data understandable, easy to analyze, and readily available:

1. Share your data
2. Provide metadata
3. Provide an unprocessed form of the data
4. Use standard data formats for files, tables, and within table cells
5. Use good null values
6. Make it easy to combine your data with other datasets
7. Perform basic quality control
8. Use an established repository
9. Use an established and liberal license

The Institute of Medicine has created a dynamic infographic for recommendations on when to share clinical trial data. This inforgraphic is freely available from their website.