Monday, March 27, 2023
12:00 pm - 2:45 pm ET: Workshop 1: Communication Skills for Data & Information Science Professionals
Maximum capacity: 30
12:00 pm - 2:45 pm ET: Workshop 2: Facilitating use of Generalist Repositories to Share and Discover Data: A Workshop by the NIH Generalist Repository Ecosystem Initiative repositories
The NIH Generalist Repository Ecosystem Initiative (GREI), led by the NIH Office of Data Science Strategy, launched in 2022 with the goal of bringing together 7 generalist repositories to collaborate on enhancing support for NIH data sharing use cases including implementing common metrics and metadata, “coopetition”, and collaborative training and outreach. This workshop will present the GREI mission and goals and introduce the 7 generalist repositories participating in GREI and their common and unique features (Dataverse, Dryad, figshare, Mendeley Data, OSF, Vivli, Zenodo), offer hands-on training and guidance on supporting researchers in using generalist repositories for data sharing including listing generalist repositories as part of data management and sharing plans, use cases supported by specific generalist repositories, and recommended practices for data sharing in generalist repositories. The session will also provide guidance on searching for data across generalist repositories and tracking open data impact and compliance with funder policies. Importantly, this session will also be an opportunity for GREI to gather feedback from the data librarian community on the needs and use cases for generalist repositories to inform future GREI work.
3:15pm - 6 pm ET: Workshop 3: What if It [Didn’t] Happen: Data Management and Avoiding Research Misconduct
Heather Coates, Abigail Goben, and Kristin Briney
Maximum capacity: 30 - FULL
Exposés of research misconduct, power abuse, and large retractions have captured scientific and popular attention. But what about the times the crisis was averted, the data wasn’t misused or lost, and the reputations weren’t harmed? Can data management education serve as a mechanism to prevent harmful practices, and assist in ensuring that data are available for validation, replication, and attribution to promote the self-correcting nature of research. Designed for data librarians who provide instruction to students, post-docs, and early career faculty, this train-the-trainer workshop will explore the crucial role of data management practices in fostering a culture of research integrity. Through in-depth discussion of contemporary investigations into allegations of research misconduct, we will accomplish two goals. First, we will make explicit connections between data management practices and the production of verifiable and reproducible research products. There will be a particular focus on data management planning, record-keeping, defining roles and responsibilities, and negotiating credit and attribution. Second, we will discuss strategies for addressing sociocultural challenges, such as power dynamics and fostering a team culture that may differ from that within the department, school, or institution. We will also consider how the practice of sharing data with collaborators, trainees, and colleagues (“gift culture”) perpetuates “haves” and “have nots”. Participants will leave the workshop with ideas for how to discuss with researchers the connection between data management and research integrity.
3:15pm - 6 pm pm ET: Workshop 4: Introduction to Python Data Analysis
Malik Miguel Redwood
Maximum capacity: 20 - FULL
In learning the basics of python programming language along with the steps for data science methodology, participants will be able to apply their new skills to gather data, clean, and analysis data is for real world application.