Deadline extended to October 1, 2021!
Do you currently share data with a network of researchers in an informal or ad hoc way? Would your data community benefit from more organized data sharing?
Ithaka S+R and the Data Curation Network invite proposals for researcher teams to participate in “Leveraging Data Communities to Advance Open Science.” This NSF-sponsored workshop will bring together representatives of informal or formal groups of researchers who would like to incorporate best practices for facilitating data sharing across disciplinary and institutional boundaries.
Building sustainable data communities requires a significant technical infrastructure that is best created through collaboration between scientists and information technology professionals. Unfortunately, these groups are often bifurcated by differing professional identities, and have relatively few opportunities for sustained dialog across disciplinary and professional perspectives, and institutional or geopolitical borders. The “Leveraging Data Communities to Advance Open Science” workshop will provide a rare forum for collaboration between information professionals and scientific researchers.
Successful applicants will receive one-on-one access to an information professional with specialized expertise who will help identify individualized solutions to data sharing challenges via remote and in-person meetings, including a two-day incubation workshop that will be held at the University of Michigan (Ann Arbor, MI) in the spring of 2022. The workshop will cover metadata and file format standardization, building or improving repositories and other sharing infrastructures, and developing schemas for interoperability and machine readability.
Who is eligible to apply?
We welcome applications from teams of researchers who are involved in existing data communities, or are interested in establishing one. Data communities are formal or informal groups of scholars who voluntarily share data across disciplinary and institutional boundaries for collective benefit and the advancement of science.
Project teams should include from two to five members. The composition of the team should reflect the diversity of roles required to successfully share data and thus include a combination of tenured- or tenure-track faculty, non-tenure-researchers, and postdocs, as well as information professionals, lab managers, or data management staff. We are particularly interested in teams that include individuals from multiple institutions and researchers from different disciplinary backgrounds.
What will participants do?
All members of the project team will be paired with an information professional for a mandatory virtual meeting, to be held in the fall of 2021. In addition, funding will be provided for two members of the project team to attend the in-person two-day workshop on February 28 and March 1, 2022, at the University of Michigan, Ann Arbor.
How do we apply?
Applications will be due on
Sept 1, 2021 October 1, 2021. To apply, submit the following information as a single PDF or word document to Dylan.firstname.lastname@example.org. Interested parties should submit the following information:
- List the names, email addresses, institutional affiliation, and job title of all members of your project, and indicate who will serve as the primary contact. Project teams must be composed of 2-5 individuals.
- List what kinds of data your data community wish to/currently share? (Approximately 100 words)
- Provide a brief narrative describing the data community your team represents or would like to create. Please describe your data community’s goals and methods for data sharing. If you have a web page or existing data repository, please include a link. (Approximately 250 words)
- We welcome applicants from established and emerging data communities, as well as from teams looking to create a new data community. Please be open about the status of your community, as our goal is to include communities at different stages of organization.
- Provide a brief description of the main challenges your data community faces and what you hope to learn from participating in Leveraging Data Communities. (Approximately 250 words)
- Provide a brief description of the efforts your data community has taken or anticipates taking to demonstrate a commitment to encouraging racial, ethnic, gender, social, and other forms of diversity within your team and/or data community. (Approximately 200 words)
Download a pdf of the official CFP. If you have any questions about the workshop or your eligibility, please contact Dylan Ruediger (Dylan.email@example.com). “Leveraging Data Communities to Advance Open Science” is supported by the National Science Foundation under Grant No. 2013433.