As part of the IMLS grant “Developing Specialized Data Curation Training to Address Needed Expertise in Focused Areas“ (RE-252343-OLS-22), the Data Curation Network and partners are currently recruiting information professionals working within academic libraries and/or archives for instructional cohorts to develop new curriculum for four specialized data types – code, geospatial data, scientific images, and simulation data. This project will extend the collaborative, community-driven, peer-to-peer model that the DCN has used to generate 27 Primers (open access guides for approaching the curation of a particular data type) and build upon DCN’s openly accessible instructional materials (see our online CURATED training modules).
Cohorts will be part of a knowledge network (see image below) to develop new content for the specialized data types and will share knowledge and experiences with other cohorts via informal and formal communication channels. A project mentor from the Data Curation Network will help guide the development process and connect the work to the broader DCN curriculum. Travel will be fully-funded for the in-person events (see below) and a $750 stipend will be provided for those selected.
Makeup of the Instructional Cohort Knowledge Network, which includes mentors and participants for the four groups: Code, Geospatial, Simulations, and Scientific Images.
The general timeline and commitments for the program include:
- January 2023: Attend a 1.5 day Kick-off Planning Meeting on January 25-26 in Washington DC
- Spring and Summer 2023: Participate in virtual monthly cohort meetings; perform independent work (estimated at a few hours per month) researching the data type and developing curriculum materials
- October 2023: Attend and provide instructional support at a 2 day pilot workshop that will present the new curriculum across the 4 data types
- Spring 2024: Respond to requested modifications to the curriculum prior to materials being made openly accessible with other DCN learning materials.
This project aims to grow our collective knowledge base to meet funder requirements (e.g., NIH policy and OSTP memo) around public access to research data including prioritizing ethical, equitable and accessible considerations for research data curation. Teams can explore new and emerging trends in data curation (for instance, what are the best practices for licensing code that are published as part of research workflows?) and learn about a variety of experiences and approaches to data curation of these data types from their peers. The cohort structure aims to give team members the time and space to learn about a given data type in a supportive environment, and then share that knowledge with the broader community.
If you are interested in applying for a spot in one of the cohorts, please complete this brief statement of interest form by November 4, 2022. Acceptance for cohort members will be announced by the end of November. If you have any questions, please contact sophia.lafferty.hess@duke.edu.
This project was made possible in part by the Institute of Museum and Library Services [RE-252343-OLS-22].