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2023 Summit Schedule

Workshops

Monday, March 27, 2023

12:00 pm - 2:45 pm ET: Workshop 1: Communication Skills for Data & Information Science Professionals

Instructor:
Christopher Eaker

Maximum capacity: 30

Strong interpersonal communication skills can foster success in both professional and personal situations. This interactive workshop invites participants to explore and practice skills for networking effectively, for talking about difficult topics, and for communicating about complex issues. Participants will learn practical tools that can be applied immediately in both their workplaces and their personal lives. Small and large group activities keep participants engaged throughout the training, which is based on the NSF-funded CyberAmbassadors curriculum. The full CyberAmbassadors curriculum includes more than 20 hours of training in communications, teamwork, and leadership skills. The presenter is a trained CyberAmbassador facilitator. In this workshop, participants will explore three modules (of nine total) from the CyberAmbassadors curriculum, including: 1. “First Contact: Communicating with a Purpose” explores the ways that effective networking skills can foster learning, invite collaborations, and uncover new opportunities for personal and professional success. Participants will learn the value of First Contact in different settings and build skills for communicating in unfamiliar situations, with the goal of developing connections, sharing ideas, and building partnerships. 2. “Let’s Talk: Communicating about Problems” focuses on building participants’ capacity to engage in meaningful, one-on-one conversations about challenging topics. Participants will explore common types of problems and practice skills for resolving ability, motivation and interpersonal problem situations. And 3. “It’s Complicated: Communicating about Complexity” helps participants build skills for working on problems that are both technically complex and complicated by differences in collaborators’ expertise, backgrounds, and communication styles. Participants will learn and practice skills for communicating more effectively in both the speaker and listener roles. If participants want to achieve a certificate for going through the entire nine modules of the CyberAmbassadors curriculum, they can attend other no-cost training sessions after this one. Dates and registration information for these will be publicized in this workshop.


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

Instructors:
Ana Van Gulick, Julie Goldman, Eric Olson, Sarah Lippincott, Andrew McKenna-Foster, Nici Pfieffier, and David Scherer

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

Instructors:
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

Instructor:
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.


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