This is a guest post by Adriana Bankston, who participated in the pilot phase of this course along with fellow Future of Research board member, Calvin Ho.
Training in research data management is critical for early career scientists. Proper data management is a responsible research practice that can facilitate collaboration and ensure that research outputs are properly generated, stored and made available for future use. In addition, it allows for discussions on measuring the scholarly influence and impact of such data, which is critical for the scientific training and career progression of early career scientists. Finally, this type of course is also valuable to organizations who rely on evidence-based resources to effect change in the scientific enterprise, including Future of Research (FoR).
In fall 2017, Elaine Martin, DA and Julie Goldman, MLIS, from The Francis A. Countway Library of Medicine at the Harvard Medical School, led the pilot phase of the Best Practices for Biomedical Research Data Management Massive Open Online Course supported by the NIH Big Data to Knowledge (BD2K) Initiative for Resource Development. The pilot phase of the course consisted in nine online modules (approximately 20 hours of content) focused on specific components of data management best practices. Module topics included the research data lifecycle, metadata, data access, curation, long-term storage and preservation, as well as data ownership and related institutional policies. It also discussed open access and open data sharing, measuring the impact of research data, and the role of librarians in working with researchers to facilitate their data management needs.
While specific aspects of the pilot phase of the course are likely to be relevant to particular groups, it provided an overall useful overview on the timely issues related to research data management in the biomedical sciences. The course included an end survey to assess the usefulness of the modules, as well as additional opportunities for feedback through various focus groups. The focus groups allowed the participants to further discuss specific aspects of the course, and provided opportunities to connect with other participants. This was a valuable experience in creating a potential network of people who could work together in the future to encourage more groups to engage in biomedical research data management training, and discuss the most useful and efficient way to provide this type of training to early career scientists through an online course.
The full version of this course will be launched on January 8, 2018 using the open Canvas Network. The course is highly relevant to early career scientists, including those currently working at the bench, in thinking about how to store, share and preserve the data they generate. It is also important for other groups to engage in these courses in order to learn how to best support the efforts of current and future early career scientists in driving the research enterprise.
In addition to undergraduate and graduate biomedical students, and other biomedical researchers, the course is also geared towards librarians and other interested individuals who wish to learn more about methods facilitating the discoverability, access, integrity, reuse value, privacy, security, and long term preservation of biomedical research data. Overall, this course is valuable to multiple groups within the research community, including organizations that advocate for better training of early career scientists, such as FoR and others.
We hope that multiple stakeholders, including early career scientists, will take advantage of this course to learn more about strategies and resources available to them in terms of biomedical research data management. Please use this link to learn more about the full course content, objectives and how you can enroll.
Related Project Links:
OSF Companion Site: http://doi.org/10.17605/OSF.IO/VRNFX
Additional NIH BD2K Training Opportunities:
BD2K Training Coordination Center: https://bigdatau.ini.usc.edu