Biomedical Research Data Management and Sharing: From Policies to Culture Change
Submitted by Dawei Lin
• Raise awareness of Data Management and Sharing Policies in the biomedical research and RDA community
• Explore best practices for developing data management and sharing plans
• Identify measures needed to incentivize greater data sharing in the biomedical research community and effect cultural change
• Determine the need for an ongoing group to address issues relevant to cultural change identified in this meeting while considering the roles of other RDA working groups and interest groups
Collaborative session notes: https://docs.google.com/document/d/10niMLLKnGpqI3pFPTqvWVxz7d3PLDN5Blri4G7HX1pI/edit?usp=sharing
Presenters: Taunton Paine (US), Jeremy Geelen (Canada), Claudia Medeiros (Brazil), Tomasz Miksa (Austria)
Welcome and introduction (5 min) – Taunton Paine (NIH)
• Policy Presentations: (20 mins) Two presentations by funders to discuss funder policies and expectations for data management and sharing plans
• Questions and Answers: (10 mins)
• Data Sharing Plan Presentations: (20 Mins) Two presentations by researchers describing the process and needs for developing a data management and sharing plan
• Questions and Answers: (10 mins)
• Open Discussion: (25 mins) BoF Opportunities – Role of RDA and BoF in maintaining a working group or interest group to continue this discussion (participants will be from multiple continents, organizations, and roles related to biomedical research)
Theme: Practice of Data Management in Research
Session type: Mix of Research and Practice Presentations and panel (open to submissions)
Target Audience: Research funders, policy makers, data stewards and management professionals, curators and librarians, researchers
Data management and sharing allows scientists to expedite the translation of research results into knowledge, products, and procedures to improve human health. Sharing data reinforces open scientific inquiry, encourages diversity of analysis and opinion, promotes new research, makes possible the testing of new or alternative hypotheses and methods of analysis, supports studies on data collection methods and measurement, facilitates the education of new researchers, enables the exploration of topics not envisioned by the initial investigators, and permits the creation of new datasets when data from multiple sources are combined.
On October 29th, 2020, the National Institutes of Health (NIH), released the NIH Data Management and Sharing Policy, which will require that all NIH conducted and funded research generating scientific data develop and submit data management and sharing plans describing where, when, and how data will be managed and shared. The Policy will be effective beginning on January 25, 2023, and compliance with NIH-approved plans will be a requirement.
An important aspect of good data management and data sharing is the adherence to standards and best practices for data stewardship. In instances where community standards do not exist, they will need to be developed. It is widely recognized that different research communities may have their own data management practices and standards; that these norms will change over time; and, that lifecycles of usefulness will vary for different data types. Therefore, it is essential for scientific communities to guide needed standards development, share best practices, and to shape expectations for the sharing and archiving of data.
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