Data Sharing in Biological and Medical Sciences
Data sharing in the biological and medical sciences refers to the practice of making research data available to other investigators or the public(1) , often through databases, repositories, or other means. This practice is crucial for several reasons:
- Advancing Scientific Research: Sharing data allows researchers to build on each others work, verify results, and conduct meta-analyses or pooled studies, which can lead to new discoveries and innovations faster than if each researcher worked in isolation.
- Transparency and Reproducibility: By making data available, other researchers can validate and reproduce findings. This enhances the credibility of the research and helps to eliminate biases or errors that might occur if data were kept private.
- Efficient Use of Resources: Data sharing avoids duplication of effort and maximizes the use of funding and resources. It allows scientists to use existing data to explore new questions without the cost and time associated with collecting new data sets.
- Ethical Responsibility: Participants in clinical trials and other studies often contribute their data with the understanding that it will be used to further knowledge and improve health outcomes. Sharing data respects their contribution by maximizing its utility.
Where do I start?
- The RDMkit provides a general introduction to data sharing, and what you should think about when you consider sharing and publishing your data.
- The digital strategy for data sharing from the Norwegian Government
- The Research Council of Norway's policy for open access to research data.
- Nature Scientific Data has a guide for Recommended Data Repositories
- There are tools that can help you select an appropriate licence for your data like The Public License Selector or ChooseALicense.com
Importance of Participation by Clinical and Research Personnel
For data sharing to be effective, it is essential that all clinical and research personnel actively participate. This includes not only the generation and collection of high-quality, well-documented data but also the support and implementation of data sharing policies and practices. Personnel must be trained in the ethical and practical aspects of data sharing, including data privacy and security measures to protect sensitive information.
"The problem is not really technical"
Lancet Oncol 2011;12:933