Open data refers to “data that can be freely used, shared, and built-on by anyone, anywhere.” Data which is considered “open” is further required to be legally acceptable, technically readable, and available to others. The many potential benefits attributed to data sharing are combined with its many challenges: assuring privacy and security, the autonomy of participants as it relates to their ability to give valid consent, population and cultural issues, measures for appropriate governance, commercialization, and sustainability of databases.
With no binding requirement, it is a scientist’s decision whether or not to share data. Since transparency, openness, and reproducibility are considered part of the scientific method in research, data sharing aligns with those tenets.
In response to the need for a universal framework as to how, when, and what types of data should be shared, the Institute of Medicine’s Committee on Strategies for Responsible Sharing of Clinical Trial Data, recently reported guiding principles and a practical framework to implement data sharing across the research enterprise. To advance understanding of this issue, PRIM&R held a webinar titled, Maximizing Benefits to Research with Human Subjects Through Data Sharing, during which speakers discussed the Committee’s recommendations as they apply to those who review research with human subjects, and addressed data sharing in a research environment and the culture of data sharing at academic institutions.
Many initiatives for data sharing have been driven by funders and research sponsors in order to maximize the usefulness of data gathered.
The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.