Writing an Effective Data Management Plan for Grants Online
An increasing amount of funding agencies, including the National Science Foundation (NSF), National Institutes of Health (NIH), and the Belmont Forum, are requiring research teams to submit a data management plan at the time of submitting their grant proposals. While many agencies offer guidelines for how to write these plans, many researchers are unsure of whether their plans include all of the necessary portions required by their funding agency. In this workshop, we will explore what should be included in a data management plan, and use several national and international funding agencies as examples. We will engage with several online resources for creating data management plans, including DMPTool (https://dmptool.org/). While this workshop is tailored towards those writing data management plans for grant proposals, the tips and tricks will also be useful for those wanting to write personal data management plans for their own research, or creating a data management plan for their research lab. No prior experience with data science or data management is needed for this workshop.
Related LibGuide: Data 101 by Emily Bongiovanni
- Thursday, March 18, 2021
- 12:00pm - 1:00pm
- Time Zone:
- Eastern Time - US & Canada (change)
- Virtual Workshop
- This is a virtual event. A URL to participate will be sent via a reminder email 24 hours before the event.
Online Workshop Information:
- The link to join this event will be found in your confirmation and reminder emails.
- Please join a few minutes early to ensure that your audio setup is working correctly
- All events are shown in Pittsburgh time. Visit this time zone converter to see when this event will take place in your time zone.
Hannah Gunderman (any pronouns) is the Data, Gaming, and Popular Culture Librarian at Carnegie Mellon University Libraries, providing data and data management support and education for students, staff, and faculty in all areas of study, from fine arts to STEM, with a particular affinity for data used in gaming and popular culture research.