Data Sharing for Better Science and Better Health

Presentation Date: 

Wednesday, September 6, 2017

Location: 

XVII Congreso SESPAS, Barcelona, Spain

Presentation Slides: 

Keynote at the XVII Congreso SESPAS sobre Ciencia para la Acción:

slides at: http://slides.com/mercecrosas/datasharing20170906/fullscreen

Research generates more data than ever before. These data lead to new findings, disprove hypotheses, and are fundamental to understanding research results. However, often published findings are available to researchers while data supporting those findings are not accessible. Data sharing or publishing, is a relatively recent term defined as "the release of research data, associated metadata, accompanying documentation, and software code (in cases where the raw data have been processed or manipulated) for re-use and analysis in such a manner that they can be discovered on the Web and referred to in a unique and persistent way."  Sharing avoids duplication of expensive experiments, speeds up health and medical scientific discoveries, and is needed to reproduce and verify published findings. So why are not all researchers sharing their data? Several factors contribute: incentives for sharing are not clear, technologies for sharing are not readily available, and privacy concerns make sharing difficult. 

The Dataverse project, started in 2006 at the Institute for Quantitative Social Science at Harvard University, addresses all of these issues, reduces barriers, and helps make data sharing common practice in research. Dataverse software enables building repositories for research data that follow best practices for making data FAIR (Findable, Accessible, Interoperable, and Reusable) while incentivizing researchers by giving credit to authors through a formal and persistent data citation which can be directly used in bibliographic references. It allows authors to create rich metadata describing a data set so that it can be reused by others, as well as defining terms of use or licenses to protect data when privacy issues arise. Data sharing is already bringing transparency and validation to scientific fields. It is time for health sciences to embrace data sharing and its benefits.