Supporting scientific reproducibility through effective data management: The NIH Library’s role

Monday, September 22, 2014 — Poster Session I
12:00 p.m. – 2:00 p.m.	FAES Academic Center	OD	RSCHSUPP-6

Author

• L.M. Federer

Abstract

As concern grows over the lack of reproducibility in biomedical research, investigators need to learn and implement best practices in data management to ensure the integrity of their scientific research data. Indeed, in a recent Nature article, Francis Collins and Lawrence Tabak point to the trans-NIH Big Data to Knowledge initiative, which focuses on data transparency and training in data science for biomedical investigators, as one of NIH’s key actions in enhancing reproducibility . However, in a 2014 survey of the NIH community conducted by the NIH Library, more than 80% of respondents had never had any training in data management. The NIH Library intends to address this gap in knowledge through its new Data Services program, which provides training in data management and specialized data services. This poster outlines how the Library’s training and services address problems of reproducibility at each stage of the research life cycle by improving the ways that investigators gather, describe, organize, preserve, share, and re-use biomedical research data.

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