## Project Statement ## This project is led by he Francis A. Countway Library of Medicine at the Harvard Medical School, made possible by funding from the NIH Big Data to Knowledge (BD2K) Initiative for Resource Development (Award Number R25LM012284). The goal of this project is to provide online educational information and resources on research data management, through the development of a Massive Open Online Course (MOOC). The Countway Library of Medicine is committed to advancing education and research by ensuring access to adequate resources, and to providing advanced, high quality education and support for all. All educational resources developed under this project, and future funding, will satisfy this need, and also reach beyond the institution to fill the need for universal research data management education. Offering comprehensive online training in data management specifically targeted for biomedical information professionals and biomedical researchers anytime and anywhere, the educational resources developed under this project fills a gap in data management training resources and foster broader access to biomedical data; laying the groundwork for future discoveries and breakthroughs. ## Project Aims ## **Aim 1: To address specific areas of the National Institutes of Health Big Data to Knowledge Initiative related to accessing biomedical resources and enhancing training in biomedical data. Specifically:** - Facilitate broad use of biomedical digital assets by making them discoverable, accessible, and citable. - Enhance training in the development and use of methods and tools necessary for biomedical Big Data science. - Support a data ecosystem that accelerates discovery as part of a digital enterprise. **Aim 2: To develop a course focused on the education and training of Biomedical Data Management. Specifically to:** - Advance education and research by ensuring access to adequate resources by providing information and resources to librarians and researchers on biomedical data management. - Provide resources on best practices in biomedical research data management in a persistently open online educational form that can be used by librarians for training biomedical students and researchers, faculty, undergraduate and graduate biomedical students, research staff, and others. - Foster broader access to biomedical data and lay the groundwork for future discoveries and breakthroughs by providing comprehensive online training in data management. **Aim 3: To generate an open online resource and training modules to overcome barriers in the biomedical research data management process. Specifically addressing the:** - Need for biomedical research data management educational training materials and courses. - Need for openly accessible tools that users, librarians, students and researchers can use to educate themselves and use to provide training for their research communities. **Aim 4: To facilitate widespread education through innovative and novel technologies. Specifically through:** - The creation of a unique Massive Open Online Course biomedical data management course that is offered continuously and is relevant to a global biomedical audience. - A course that will address the unique data management learning needs of information professionals, students, and faculty in the biomedical sphere. ## Best Practices for Biomedical Research Data Management ## *The Best Practices for Biomedical Research Data Management* massive open online course (MOOC) will provide training to librarians, biomedical researchers, undergraduate and graduate biomedical students, and other interested individuals on recommended practices that facilitate the discoverability, access, integrity, reuse value, privacy, security, and long term preservation of biomedical research data. This MOOC is built upon and expands the training materials of the [New England Collaborative Data Management Curriculum][2] (NECDMC), developed by the Lamar Soutter Library at the University of Massachusetts Medical School in partnership with several libraries in the New England region. This course is both significant and innovative in its approach to course content and course development. We have created a standardized conceptual framework for online educational development design and delivery. This framework combines user experience and design elements into a self-paced, interactive open online course. Designed on the open course platform, Canvas, anyone, anywhere, at any time can access the online course. Each of the MOOC’s nine modules are dedicated to a specific component of data management best practices, including: types of data, benefits of data sharing, research data life cycle, data documentation, ensuring data privacy, legal and ethical concerns, data sharing and reuse policies, data preservation, and the collaborating roles of key stakeholders in the biomedical research enterprise. You can proceed through the modules sequentially or you may take them individually according to your needs. The module design framework includes these six components: video lectures, presentation slides, readings & resources, research teaching cases, interactive activities, and concept quizzes. The Canvas MOOC and curricular materials are under a [Creative Commons Attribution 4.0 License][3] unless otherwise noted (for example, video materials are Creative Common Attribution-NonCommercial-ShareAlike 4.0 License). We encourage individuals to use and adapt the MOOC’s instructional materials for local training. [2]: https://library.umassmed.edu/necdmc/index [3]: https://creativecommons.org/licenses/by/4.0/