University-wide effort will produce new data-lifecycle services for Harvard researchers.
May 28, 2013—The Harvard Library, in collaboration with the Office of the Provost, IQSS Dataverse Network and HUIT, is launching the Research Data Collaborative (RDC) to develop research data management services. The RDC program’s FY14 goals include creation of tiered data management training for researchers and librarians, a University-wide data compliance network, effective data management plan support and an assessment of the data storage and curation needs of Harvard researchers.
The RDC program members will provide training materials along with workshops that broadly address research data management. Topics such as data security, storage, archiving, preservation and curation will be covered, in addition to data advisory services regarding retention and compliance policies. A University-wide survey and assessment will lay the groundwork for effective data management support services for a Harvard audience.
The Program is led by Gosia Stergios and the following team:
Kathryn Hammond Baker, Countway Library, HMS
Sonia Barbosa, Dataverse Network, Institute for Quantitative Social Science
Amy Benson, Schlesinger Library, RI
Eleni Castro, Dataverse Network, Institute for Quantitative Social Science
Merce Crosas, Dataverse Network, Institute for Quantitative Social Science
Christopher Erdmann, Wolbach Library, CfA
Jud Harward, Harvard University Information Technology
Virginia Hunt, University Archives
Skip Kendall, University Archives
Jonathan Kennedy, Center for Biomedical Informatics, Countway Library, HMS
Michael Leach, Harvard College Library, FAS
Melissa Lopes, Office of the Vice Provost for Research
Megan Sniffin-Marinoff, University Archives
Rob Parrott, Harvard University Information Technology
Connie Rinaldo, Ernst Mayr Library, Museum of Comparative Zoology, FAS
Martin Schreiner, Harvard Maps Collection, FAS
Darla White, Countway Library, HMS
The RDC is actively recruiting team members from the University community.
See below an initial list of projects planned for this calendar year. For more information on a project, please contact the project lead.
Project 1A: Data Information Literacy for Researchers
Lead: Gosia Stergios (firstname.lastname@example.org)
Team: Melissa Lopes, Connie Rinaldo, Kathryn Hammond Baker, Dataverse team, Jud Harward
Goal: Develop a targeted series of training materials for researchers, research administrators, and IRB officials (in data security, use, retention and management).
Project 1B: General Data Management Training for Librarians
Lead: Michael Leach (email@example.com)
Team: Connie Rinaldo, Gosia Stergios
Goal: Develop and deliver a series of training sessions for librarians who will become the key point service providers for data management. The first sessions will be announced soon!
Project 1C: Week of Data: An Intensive Course for Graduate Students and Librarians
Team: Sonia Barbosa (IQSS), Eleni (IQSS), Amy Benson (Schlesinger Library)
Goal: To train graduate students to obtain necessary knowledge and skills for working with data and upgrade librarians’ skills and knowledge of current tools and methodologies used by researchers in the research data lifecycle.
Project 2: Data Retention Compliance Network
Team: Kris Bolt, Megan Sniffin-Marinoff, Connie Rinaldo
Goal: To facilitate and ensure researchers’ compliance with Harvard’s research data retention policy and funders’ policies by developing tiered advisory services by school-based teams that already have trusted working relationships with faculty and researchers, including librarians, archivists, IT and OA representatives.
Project 3: Data Management Plan Problem Assessment
Team: Jeff Liu, FAS OSP representative
Goal: A concrete, actionable plan for effective data management plan support services.
Project 4: Harvard Research Data Management Needs Assessment
Team: Martin Schreiner, Rob Parrott, Melissa Lopes, Jud Harward, Connie Rinaldo
Goal: To conduct a uniform, Harvard-wide survey/assessment of the types, volume, and attributes/characteristics of research data that require retention and preservation, per Harvard and NSF/NIH data management/retention policies.