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From data sharing to data publishing [version 2; peer review: 2 approved, 1 approved with reservations]
1Montreal Neurological Institute and Hospital, McGill University, Montréal, QC, H3A 2B4, Canada.
MNI Open Research
|June 4, 2019
Summary
Life science researchers are slow to adopt data sharing. The study advocates for data publishing, especially for neuroscience data, proposing practical steps for implementation.
Area of Science:
- Neuroscience
- Life Sciences
- Scientific Data Management
Background:
- Data sharing is crucial for scientific advancement but faces slow adoption in life sciences.
- Current data repositories are not sufficiently utilized by the research community.
- Sociological and cultural factors impede widespread data sharing practices.
Purpose of the Study:
- To analyze the reasons behind the slow adoption of data sharing in life sciences.
- To propose data publishing as a more effective alternative to data sharing.
- To focus on the specific needs and opportunities within neuroscience data.
Main Methods:
- Analysis of sociological and cultural contexts within scientific research.
- Comparative assessment of data sharing versus data publishing models.
- Development of practical strategies for implementing data publishing.
Main Results:
- Identified sociological and cultural barriers hindering data sharing.
- Argued for data publishing as a superior model for scientific data dissemination.
- Outlined actionable steps for transitioning to a data publishing framework.
Conclusions:
- Data publishing offers a more robust solution for scientific data accessibility than traditional data sharing.
- Neuroscience data presents a prime area for implementing data publishing initiatives.
- Practical steps are proposed to facilitate the adoption of data publishing across research communities.
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