Summit Schedule
Monday, April 13
Workshops
12 PM ET - 3 PM ET
(9AM PT - 12PM PT)
Session 1A: Building Data Steward Career Pathways: A Persona-Based Approach to Professional Development
Shannon Sheridan, Pacific Northwest National Laboratory
Liise Lehtsalu, RDA Europe
Elizabeth Newbold, UKRI Science and Technology Facilities Council
Data stewardship has emerged as a critical profession supporting research and organizational data management, yet career advancement pathways remain unclear and inconsistent across institutions. Many data stewards find themselves in their roles without clear understanding of potential career trajectories or the diverse specializations within the field.
This interactive workshop equips data stewards with practical tools for understanding and navigating their career pathways using persona methodology. Participants will learn to create detailed professional profiles that clarify role distinctions, required competencies, and potential career transitions within data stewardship. Through hands-on exercises, attendees will develop data steward personas while testing an emerging methodology designed specifically for this profession.
The workshop provides immediate value for data stewards seeking career clarity and professional development direction. Participants will gain frameworks for articulating their current roles and identifying advancement opportunities within their organizations or the broader field. Whether you're new to data stewardship, considering a specialization change, or planning long-term career growth, this session offers concrete tools for professional navigation.
Participants will engage in collaborative small-group persona development exercises, share findings with other data stewards, and provide feedback on methodology effectiveness. This peer-to-peer approach ensures attendees learn from diverse professional experiences while developing practical tools they can immediately apply to their career planning.
The workshop targets practicing data stewards, research data managers, data librarians, data curators, and anyone currently working in data stewardship roles. By session end, participants will have concrete frameworks for career planning, vocabulary for discussing their professional development with supervisors, and clearer understanding of the diverse pathways available within data stewardship careers.
Session 1B: Data Danger: Crowdsourcing a Practical Learning Path for Research Data Integrity
Emily J. Blumenthal, The George Washington University
Dolsy Smith, The George Washington University
Daphna Atias, The George Washington University
Molly Hardy, Harvard University, Christopher Setzer, Harvard University (not presenting)
Trustworthy data is the backbone of reliable research, yet many researchers still struggle to assess whether the data they rely on is truly sound. As research data professionals, we excel at connecting people with datasets, but helping them evaluate the quality, integrity, and real-world reliability of those datasets is an equally critical, and often overlooked, part of our work. In practice, researchers face risks ranging from accidental data corruption to incomplete documentation to deliberate suppression.
This workshop is designed to bridge the gap between high-level conceptual frameworks and what researchers actually need in their day-to-day work. Our long-term goal is to co-develop a flexible, scalable learning path for research data integrity – one that research data professionals can personalize to their own communities. This workshop takes the first steps toward that broader objective. We will begin by identifying the core concepts researchers must understand, positioning data integrity not as a technical afterthought but as an ethical and methodological imperative. We then introduce a practical framework built around some common risks to trustworthiness: poor sampling strategy, intentional alteration or suppression, technical corruption, and metadata or version drift.
The session’s central activity is a curriculum-building exercise grounded in real-world implementation. Participants will collaborate to sketch out concrete teaching modules, learning objectives, and hands-on exercises tied to these risks, helping to surface what a robust, adaptable set of learning materials could look like. This collaborative approach addresses three foundational challenges: defining the essential learning path, structuring modular and extensible content, and identifying or surfacing high-quality existing resources.
We will conclude by outlining next steps for continuing this work beyond the session, including compiling ideas generated during the workshop and identifying opportunities for ongoing community contribution.
3 PM ET - 6 PM ET
(12PM PT - 3PM PT)
Session 2A: Navigating the Spaces Between Method and Technology with Qualitative Researchers
Jess Hagman, University of Illinois Urbana-Champaign
Qualitative research projects require a unique approach to data analysis based on the type of data, methodology, and the conceptions of research rigor within a community of practice in which the work is shared. For those consulting with or teaching qualitative researchers about technology for data management and analysis, this diversity can be a challenge, particularly when we have limited training in the range of qualitative methodologies.
The workshop will begin with an interactive discussion of the key terms and concepts that qualitative researchers use to describe their work, as we use a collaborative white board tool to model the relationship between these concepts. Attendees will then learn strategies for engaging with qualitative researchers in data services contexts, including questions that can facilitate a consultation or instruction setting. Using the framework of Big Q and small q research, attendees will explore how the type of research shapes how scholars make choices about technology, strategies for data analysis, and ways of communicating research quality.
Workshop attendees will practice identifying choices about technology, data analysis strategies, and research quality claims within published work and collaboratively develop a list questions they can bring to consultations or use to shape workshops about data management and analysis.
This workshop does not assume any prior knowledge of qualitative research methods or technology and will be taught by Jess Hagman, a librarian with extensive history teaching and consulting on the use of qualitative data analysis strategies and technologies.
Session 2B: A Gentle, Hands-on Introduction to Containers and Virtual Machines
WORKSHOP IS FULL
Hafeez Adepoju, University of Arizona
Chreston Miller, Virginia Tech
Fernando Rios, University of Arizona, Jeff Oliver, University of Arizona (not presenting)
Computational workflows increasingly make use of virtualization and containerization technologies to enable portability of the software environment (allows others to more easily examine and run the code), scaling of the workload (more easily run it in high performance computing environments), and research reproducibility. Librarians supporting data-intensive research or working in computationally adjacent areas should not only be aware of the existence of these technologies but also have a basic understanding of how they operate. The goal of this workshop is to introduce virtual machines and containers to a novice audience of librarians with interest in data management, data science, or research computing in general. Participants will gain exposure to the basic concepts of virtual machines and containers via exercises and will explore the technologies via hands-on activities using VirtualBox and Docker (Docker will be emphasized more than VirtualBox). Prior experience is not required but we assume some familiarity with basic computing concepts (e.g., what CPU and RAM are). Prior experience using the command line to run programs and navigate the file system (either in Unix or Windows) is useful but not required. Though not necessary, familiarity with reproducible research may also be useful to help contextualize some of the material.
Prerequisites for the hands-on activities include access to a computer (Windows, Linux, or Mac) with at least 8 GB RAM and about 10 GB of free disk space and the ability to install and run VirtualBox (freely available for personal, research, and educational use). The latter requires administrative access.
This workshop is designed for future inclusion in the Library Carpentry curriculum and feedback will be solicited from participants.
Tuesday, April 14
Session A
Session B
Welcome and Keynote Address
Session 1A
- Research Transparency in US Supreme Court Litigation
- Alex Zhang, Duke Law School
- Addressing Ethical Tensions in Archiving and Sharing Anthropological Research Data
- Celia Emmelhainz, Peabody Museum of Archaeology & Ethnology
- Unlocking the Potential of QDAS for Data Sharing and Reuse in Social Science Research: Learning from Researchers’ Views
- Dessi Kirilova, Qualitative Data Repository (QDR)
- Sebastian Karcher, Qualitative Data Repository, QDR
Session 1B
- Tailoring Data Acquisition Support for Business Students in an Era of 'Missing' Data
- Madison Golden , University of Utah - Marriott Library
- Lorelei Rutledge , University of Utah
- Data as Scholarship: A Practical Framework for Engaging Researchers in Open Data
- Alaina L Pearce , Pennsylvania State University
- How Should We Teach About Federal Data Now?
- Lena Bohman , Zucker School of Medicine at Hofstra/Northwell
- Beth Jarosz , Georgetown University
- The Data Nudge Approach to Practical, Reusable Information Design
- Sandi Caldrone , University of Illinois Urbana-Champaign
Session 2A
- Collections-as-data in the real world: Practical approaches for breathing new life into historical data
- Amanda Whitmire , Stanford University
- Marla Hertz , University of Alabama at Birmingham
- Sandi Caldrone , University of Illinois Urbana-Champaign
- Finding Meaning in the Data: Building data engagement by using real-life, local data to teach data management and analysis skills
- Jocelyn Swick-Jemison , University at Buffalo
- Collaborative Cases: Researching Preservation Processes
- Robyn Stobbs , Athabasca University
- The Emmett Till Project in New Orleans: Creating a Community Dataset of Racially-Motivated Cold Case Homicides from Physical Archives
- Andrew Mullins , City Archives & Special Collections / New Orleans Public Library
- Anwen Tormey , Orleans Parish District Attorney - Civil Rights Division
Session 2B
- FAIR Spreadsheets: A Simple Application to Facilitate the Curation of Spreadsheet-based Research Data
- Aditya Ranganath , University of Colorado Boulder
- Matthew Murray , University of Colorado Boulder
- Ellery Galvin , University of Colorado Boulder
- Andrew Johnson , University of Colorado Boulder (not presenting)
- You’re Almost There! How Applying the FAIR Principles Helps Create Digitally Accessible Content, and How To Move the Needle Forward
- Emma Wood , University of Massachusetts Dartmouth
- Sagan Wallace , Oregon State University
- Clara Llebot , Oregon State University
- Two Small Approaches to the Big Problem of Formatted Spreadsheets
- Summer Mengarelli , University of Notre Dame
- Luis D. Verde Arregoitia , Instituto de Ecología AC INECOL
- Spreadsheet Best Practices in Zenodo: Preliminary Findings
- Alexandra Provo , New York University
Social - New Members and First Time Attendees
Join us at the New Members/First-Time Attendees Event to learn more about RDAP, meet new Summit attendees and long-time members, and participate in trivia for the chance to win prizes!
Wednesday, April 15
Session A
Session B
Session 3A
- Development of a Programmatic Approach for Large-scale Metadata Re-curation in the Texas Data Repository
- Bryan Gee, University of Texas at Austin
- FAIR Facilities and Instruments: Recommendations for Adoption of Research Instrument, Platform, and Facility Persistent Identifiers
- Andrew Johnson, University of Colorado Boulder
- Renaine Julian, Florida State University
- Addressing Legacy Metadata and Data Management Practices in the Wisconsin Longitudinal Study
- Barry Radler, University of Wisconsin
- Examining the Value of Research Data in Earth Science: A Multi-stakeholder Perspective
- Chenyue Jiao, University of Illinois Urbana Champaign
Session 3B
- Building Capacity for Qualitative Data Support Through Collaborative Learning
- Emily J. Blumenthal, The George Washington University
- Taylor Baugher, The George Washington University
- Sara Hoover, The George Washington University
- Bo Yang, Lacey Johnson, Sheila Dougherty, The George Washington University (not presenting)
- Training Data Wizards: A Pilot Program for Peer-Led Workshops
- Maggie Marchant, Brigham Young University
- Adam Griggs, Brigham Young University
- Paul Robbins, Brigham Young University
- Ellen Amatangelo, Brigham Young University
- There’s No One Way to Learn Research Data Skills: Practical Lessons From Coordinating Library and IT Workshops
- Daniel Woulfin, Columbia University
- Jessica Eaton, Columbia University
Session 4A
- LiDS Task Force Report
- Some Tricks of the Trade for Fulfilling Collaborations
- E. M. Durham, University of Kansas
- Scout Calvert, University of Nebraska–Lincoln
- Strengthening Institutional Capacity for Research Data Stewardship
- Briana Wham, Penn State University
- From Vision to Implementation: Engaging Diverse Research Data Communities to Shape a National Data Platform
- Graham Jensen, Digital Research Alliance of Canada
Session 4B
- Developing a Data Management Dashboard: A Harvard University Case Study using Coldfront and Starfish
- Sarah Marchese, Harvard University, Faculty of Arts and Sciences
- Providing Practical, Personalized, and Impactful Learning Experiences for Working Librarians on Research Data Services
- Rong Tang, Simmons University
- Shabnam Shahvar, Harvard Medical School
- AI-Ready Data in the Real World: Transforming Vague Best Practices into Working Tools
- Shannon Sheridan, Pacific Northwest National Laboratory
- Data Concierge: Bespoke RDM consulting for PIs
- Lei Ma, Harvard University
Session 5A
- Evaluating Python DVUploader for Large Data Upload to the Texas Data Repository
- Leah Everitt, University of New Mexico
- Practicing What We Preach: Self-Directed Data Services for Publishing Dissertation Research
- Dani Kirsch, Oklahoma State University
- Curation for All: Introducing a Playbook for Community-Centered Data Curation
- Kelsey Badger, The Ohio State University
- Practical Takeaways from a Qualitative Case Study of Carpentries Institutional Membership
- Jamene Brooks-Kieffer, University of Kansas
Session 5B
- “Our repository doesn’t publish sensitive data…”: But how do we put this into practice?
- Amy Ferguson, Data Curation Network
- Alicia Hoeflich Mohr, University of Minnesota
- Leslie Kirsch, The Michael J. Fox Foundation for Parkinson’s Research
- Rachel Woodbrook, University of Michigan (not presenting)
Social - TBD
Thursday, April 16
Session A
Session B
Business Meeting
Session 6A
- From DMS Plans to FAIR Data: A Practical Model for Researcher Support
- Seonyoung Kim, Washington University in St. Louis
- DMP‑Check: Turning Static DMPs into Living, Policy‑Aware Companions
- Dykee Gorrell, San Jose State University
- DMPs in the Real World: Using the DART Rubric to Understand How Researchers Approach Data Management
- Rubab Shahzad, University of Texas at Arlington
- Anette Moreno-Lozano, University of Texas at Arlington
- Katie Pierce Farrier, University of Texas at Arlington
- The University of Arizona Libraries’ Data Management and Sharing Plan Ambassadors Pilot Program
- Jim Martin, University of Arizona Libraries
- Angela Murrell, University of Arizona Libraries
- Ahlam Saleh, University of Arizona Libraries
- Elizabeth Kline, University of Arizona Libraries (not presenting)
Session 6B
- Forging New Roles for Data Librarians in Open Access Publishing
- Julie Goldman, Harvard Library, Harvard University Managing Editor, Journal of eScience Librarianship
- Sally Gore, Lamar Soutter Library, University of Massachusetts Medical School
- Regina Fisher Raboin, Boston Architectural College Library, Boston Architectural College Editor-in-Chief, Journal of eScience Librarianship
- Allie Tatarian, Hirsh Health Sciences Library, Tufts University Data Editor, Journal of eScience Librarianship
Session 7A
- Building Data Confidence: Three Models for Digital Scholarship Mentorship in the Library
- Halie Kerns, Bridgewater State University
- Ruth Carpenter, Binghamton University
- Streamlining Data Access and Addressing Disciplinary Data Needs Through Data Spaces
- CJ Woodford, Digital Research Alliance of Canada
- Graham Jensen, Digital Research Alliance of Canada
- Data Accessibility Working Group Report
- Heather Charlotte Owen, University of Rochester
- Christine Nieman Hislop, University of Maryland, College Park
- Zooming In or Out: Defining the Scope of Data Visualization Support in Academic Health Sciences Libraries
- Xiaolan Qiu, East Carolina University
Session 7B
- Is it time for libraries to (re)consider direct-charge models for some research data services or infrastructure use?
- Betsy Gunia, Johns Hopkins University
- Stacy Winchester, University of South Carolina
- Leslie Delserone, University of Nebraska - Lincoln