Sessions will be held online through Zoom. Information and instructions to join sessions will be sent to registered attendees via email in the week before the symposium, along with links to join workshops for workshop registrants. Materials will be placed in this year's OSF after the symposium is over.
Attendees are expected to follow the symposium Code of Conduct and to be aware of the planning committee's Commitment to Accessibility.
All times are in Eastern Time (EDT).
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| Wed, Oct 8 | |
| Opening & Workshop 10:00 AM - 11:45 AM | 10:00 AM Welcome and Symposium Logistics
10:15 AM Ctrl+S: Library Decision-Makers' Sustaining and Shaping RDS Futures
This workshop offers strategies for sustaining data services and engaging with higher education institutions. Through a mix of presentations, hands-on activities, and peer discussion, attendees will gain a holistic framework for two levels of data advocacy across their campuses. In the first half, participants will explore how librarians can move beyond stewardship to embrace strategic advocacy, influence institutional policy, and reframe research data as a strategic asset. They will learn practical frameworks for building trust with partners, shifting the library from data steward to valued collaborator, and will begin building a personal data advocacy toolkit. The second half will focus on systems-level, values-driven budgetary decisions that enable libraries to sustain and grow data services in times of resource uncertainty. Presenters will share strategic pathways for prioritizing program investments while making the case for data services as critical to advancing institutional goals. Participants will leave with concrete strategies and a personalized plan for addressing their institution’s data services budgetary challenges and opportunities. Learning Objectives:
| Break 11:45 AM - 12:00 PM |
| Keynote 12:00 PM - 1:00 PM | 12:00 PM Saving What Counts: Lessons from Data Rescues for Today's Data Librarians
 Bio: Dr. Lynda Kellam is one of the founding organizers of the Data Rescue Project and the Snyder-Granader Director of Research Data & Digital Scholarship at the University of Pennsylvania Libraries. She has written and presented extensively on data services, data management, and government information. She is the current Secretary of IASSIST, an international data professional organization, and has served in multiple leadership positions in ALA, ACRL, and GODORT. She holds an MLIS, an MA in Political Science, and a PhD in American History. | Break 1:00 PM - 1:45 PM |
| Short Talks 1:45 PM - 2:25 PM | 1:45 PM Good Data in Bad Times: Advocating Open Science Practices for the Current Research Environment
Data librarians in the United States are currently in the tenuous position of advocating for open science practices (such as data sharing and reproducible analyses) to researchers whose work is being maligned, defunded, and scrutinized to a new degree. While it remains possible and vital to promote open science principles, librarians must be frank about the challenges facing researchers and communicate in a manner that takes their concerns seriously. Analyzing past studies on why researchers do not share data alongside current challenges, this presentation will discuss three distinct reasons researchers may be hesitant to share data—insufficient time or funds, fear of misrepresentation, and concern for misuse—and provide suggestions on how librarians of all levels can effectively engage with these concerns in outreach to researchers.
2:05 PM Data Rescue as Civic Engagement: Empowering Communities to Preserve Public Data
In an era of shifting federal priorities, at-risk government data threatens the transparency essential to a robust democracy. Our Government Data Rescue LibGuide was designed not only to help users find the data they need but to invite them to actively participate in safeguarding public information. Through this initiative, we engaged AU students, faculty, and a broader community to highlight data rescue as an act of civic engagement. In this session, we explore how data librarianship can support civic pluralism, public service, and interdisciplinary innovation. We will share lessons learned from our data rescue work, strategies for building community engagement around data preservation, and ideas for future programming to keep momentum alive. Learning Objectives:
| Break 2:25 PM - 2:45 PM |
| Workshop 2:45 PM - 4:15 PM | 2:45 PM Practical Python for Bibliometric Data
This session will provide an overview of a project conducted by the presenter, an early career librarian, utilizing Python scripts to address key questions, such as: "In which journals are our current faculty publishing, and how does this align with our existing open access transformative agreements?", "Where do we have open access transformative agreements without any publishers yet?", and "How many journals from the Financial Times 50 list are we currently publishing in?". The presenter will discuss the experimental process and share insights from their experience presenting these findings to the Dean of Research. Attendees will leave with access to a Google Colab Python notebook that includes: five Python scripts equipped with functions for data analysis, along with five sample datasets that they can modify to suit their own needs. No Python Experience Required. Learning Objectives:
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| Thu, Oct 9 | |
| Short Talks 10:00 AM - 11:00 AM | 10:00 AM From Data to Impact: Empowering Climate Justice Research with GIS at MIT Libraries
This presentation will highlight how we support GIS and climate justice research by equipping students, faculty, and staff with essential geospatial skills through workshops, 1:1 mentorship, and course-integrated support. We guide users in data collection, interpreting and writing metadata, conducting site-based suitability assessments, and using GIS products with a strong focus on climate justice applications. We also train users in creating high-quality maps using Adobe products and in developing interactive web maps, ensuring their spatial data storytelling is both analytically rigorous and visually compelling. Our work also emphasizes understanding the needs of end-users such as government agencies and community practitioners to ensure relevant and impactful outputs. We collaborate directly with faculty and students on research projects and independent studies, providing individualized support tailored to their specific goals.
Learning Objectives:
10:20 AM Visualizing Together: Data Visualization as an Entry Point for Data Engagement
Data visualization as public data storytelling offers a unique opportunity to build bridges across disciplines, institutional silos, and communities. At Binghamton University, the Libraries co-lead a DataViz group on campus. This group, once on life support during the pandemic, has been revived and is now a thriving, transdisciplinary network spanning faculty, staff, students, and local partners. Over two years, a strategic liaison model was created to connect departments, event attendance tripled, and programming evolved to sustained, interactive engagement from all audiences across campus. This talk will share how administrative planning, community-building strategies, and inclusive outreach (to both faculty and staff) positioned the library not just as a service provider, but as a co-leader in campus-wide data literacy. Attendees will leave with ideas for how data viz can act as a method of research sharing and an accessible entry point into deeper data engagement.
Learning Objectives:
10:40 AM Live Data Collection and Visualization as a Student Engagement and Data Literacy Tool
Looking for a fun way to engage students (and others) when tabling or promoting library resources? In this session we will discuss how we have continued to grow and expand our live data collection/visualizations from our first International Love Data Week to our own Scary Data Week and other tabling events such as Earth Week, student fairs, etc. The session will include: (1) how we have used live polling (data collection and visualizations) as a student engagement tool during tabling. events to promote our library's data services; (2) how the polling itself can be used as teaching/learning opportunities for basic data literacy skills and how to segue from the data polls to resource promotion; (3) and the lessons learned about interactive poll design including how to select questions/topics of interest to students and the everyday materials we use to "collect" and "visualize" our data. For all experience levels. Learning Objectives:
| Break 11:00 AM - 11:15 AM |
| Poster Sessions 11:15 AM - 12:15 PM | Building a Foundation: Creating an Institutional Slide Deck for Data Services Outreach and Instruction
As data services expand across academic libraries, clearly communicating available support is essential. This poster presents the development of a reusable slide deck designed to introduce data services at Indiana University Indianapolis to students, faculty, and staff. The slide deck provides an overview of core services—including data management, data literacy, and research support—while highlighting institutional tools, policies, and contacts. The project emphasizes adaptable design for a range of audiences and instructional contexts. Attendees will learn about the deck's creation process, strategies for stakeholder feedback, and ideas for customizing similar outreach materials at their own institutions.
Learning Objectives:
Providing Data Services to Expand Data Literacy
This poster outlines the intersection of ICPSR's "Providing Data Services: From Surviving to Succeeding" summer course and a summer-long project to refine information literacy instruction for algorithmic/AI, data, and misinformation literacy at Tufts University's Tisch Library. One of the initial outcomes from this intersection of intense learning and Silicon Valley style rapid project development is an adaptable lesson plan for teaching data search strategies. The poster also includes future concepts for refining Tisch Library's data literacy instruction to better align with our data services.
Learning Objectives:
The Earlier, the Better: Making a Case for Specialized Training Upon Employment
This poster session presents a case study from the perspective of an early-career librarian who recently stepped into a newly created role at an institution strategically expanding its capacity to support research data services. The presenter will share their experience and highlight the overall benefits of taking an ICPSR Summer Workshop course on providing data services while also participating in institutional onboarding, training, and orientation, all within the first three months of their employment. By discussing how they adapted and applied the capstone project from the training at their home institution, this session will demonstrate how targeted professional development can immediately and meaningfully contribute to the strategic efforts of research data teams and their institutions.
Learning Objectives:
Stranger Than Fiction: The Costs and Dangers of Generative AI
Skynet. M3gan. WALL-E. Popular culture has explored humanity's hopes and fears regarding AI for decades. And yet, our development and use of AI has been much less critical and more reckless. From environmental impacts to "hallucinations" to therapy bots, this poster will cover the costs of GenAI on our planet, our culture, and ourselves; examples of the intersection of GenAI and data librarianship; as well as "GenAI refusal", the AI Disclosure Framework, and tools for assessing AI, including Tribelhorn's Ethical AI Assessment Tool. Whether you're a skeptic or enthusiast, this poster will provide a counterpoint to the rapid adoption of AI tools
Learning Objectives:
Building a Data Services Plan from the Ground Up: A Practical Approach
With the need for data literacy and access to data resources growing among students and faculty, the Library at Santa Clara University recognized the need for a Data Services Plan. A primarily undergraduate teaching institution, SCU is pursuing a new strategic direction to support more faculty research, amplifying the need for the library to respond with intentionality and agility. However, data plan models for R01 institutions needed to be scaled appropriately to meet both current and projected needs. This poster outlines the process of developing a data services strategy from the ground up without prior experience or institutional precedent. It involved considering user needs, library capabilities, future planning, and building new partnerships.
Learning Objectives:
Solo datalib: Planning a strategic rollout to "do it all"
Solo data librarianship is challenging but fun, solitary but highly collaborative. After almost five years at University of North Carolina-Wilmington, a recent R2 university, this poster reflects on how one librarian created scalable data services for all of campus that could hit all areas of the research data lifecycle. Using takeaways from scholarly literature about data librarian responsibility areas and data librarian core competencies, this librarian will show her maturity model, a rollout plan for her data services adapted based on a research data management concept explained by Cox, Kennan, Lyon, Pinfield, and Sbaffi (2019). The poster will connect her rollout plan to a summative overview document identifying areas of data expertise at her university, which was a capstone project for the 2025 ICPSR Summer Program course "Providing Data Services: From Surviving to Succeeding." Learning Objectives:
| Break 12:15 PM - 1:00 PM |
| Short Talks 1:00 PM - 1:40 PM | 1:00 PM Meeting Researchers Where They Are - Workshops on "Good Enough" Data Management Practices
Although research data management (RMD) is critical to open access compliance, it is often learned via trial-and-error or inherited lab processes rather than formal instruction in PhD programs. Since many RDM publications/workshops focus on more advanced practices, I identified ‘good enough' data practices to meet researchers where they are in terms of RDM skills and time/effort they can dedicate. ‘Good enough' practices need to be low effort, have a shallow learning curve, have immediate and future benefits, and increase data reusability. I have delivered ‘good enough' practices to researchers at various stages from graduate students through mid-career faculty as part of stand-alone workshops, bootcamps, and choose-your-own-adventure style of training driven by audience interest. Feedback indicates attendees are motivated to implement these practices and often request additional, in-depth workshops on various RDM components. This presentation will appeal to attendees interested in providing RDM workshops in preparation for emerging open data policies.
Learning Objectives:
1:40 PM SHARPGrads: Preparing Students for Data Skills Needed in Graduate School and Beyond
The Skills, Habits, and Research Program for Graduate Students (SHARPGrads) is a data and research skills workshop series at the University of South Carolina. Co-sponsored by University Libraries, Research Computing, and the Graduate School, SHARPGrads exposes graduate students in all disciplines to data skills and concepts that are required for graduate work but are often not included in the curriculum. Since its first iteration in 2019 as a two-day, in-person event, SHARPGrads has evolved into a year-long virtual workshop series. The relationships formed to collaboratively deliver this programming have helped University Libraries situate itself as a partner in research. Lessons learned include event timing, organizing and administering a growing, distributed program, creating effective channels for communicating across units and populations, and figuring out the types of events and rewards that matter to graduate students. In this short session, participants will learn about some of this program's successes, challenges, and future directions for growth and improvement so that they can come away with implementation ideas of their own. Learning Objectives:
| Break 1:40 PM - 2:00 PM |
| Workshop 2:00 PM - 3:30 PM | 2:30 PM From Access to Action: Building Civic Data Literacy in Libraries
Ensuring continued access to public datasets has been a pressing concern in recent months, particularly as many datasets continue to be removed or altered. While safeguarding and disseminating this data is essential, an equally important responsibility for libraries is equipping patrons with the skills to understand and use it effectively.Public datasets are often difficult to locate and interpret, requiring both contextual awareness and technical literacy. As trusted community hubs, libraries are uniquely positioned to bridge this gap. This presentation will explore the common challenges patrons face when accessing and working with public data, outline key components of a civic data literacy curriculum, and demonstrate how libraries can harness civic data literacy to promote informed civic engagement and advocacy.Following the presentation, a hands-on workshop will guide participants through the process of exploring civic datasets using Tableau. Attendees will learn how to identify relevant data sources, access and prepare datasets, and visualize data for storytelling and advocacy. Learning Objectives:
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| Fri, Oct 10 | |
| Short Talks 10:00 AM - 11:00 AM | 10:00 AM Democratizing Access to Library Data Assets: AI enhanced curation model using Databricks
Academic libraries invest significant resources in acquiring licensed data assets— unique and valuable resources for research, such as historical census records. However, these assets often remain underutilized because of discovery and access barriers, particularly for researchers who lack programming expertise. Our proof-of-concept model addresses this challenge by reimagining how libraries can manage their licensed digital holdings. We propose a curation model that transforms licensed datasets into research-ready data products using Databricks, which is a unified, cloud-based data platform built on the lakehouse architecture. This platform allows us to manage large-scale data and computational workloads on a pay-as-you-go basis (measured in Databricks Units or DBUs), making these valuable assets more accessible to the wider research community without requiring significant upfront investment in local computing infrastructure. This system uses AI to enhance metadata, improving discovery and helping researchers locate the right assets quickly. It also allows for direct, in-browser interaction with the data, removing the need for large downloads or specialized software. By providing on-demand compute resources, the model allows researchers to provision the exact power they need for specific workloads in a fraction of the time, eliminating the traditional bottleneck of waiting for access to a supercomputer. This approach aligns with a library's core mission to democratize knowledge. By providing universal, scalable access to valuable data assets, we are helping libraries evolve their services to support computational scholarship and fulfill their role as stewards of information in the AI era.
Learning Objectives:
10:20 AM Integrating Generative AI into Research Data Management Instruction for Biomedical Engineering Students
Biomedical engineering students at [Institution Redacted] complete a senior laboratory course involving experiments and data interpretation. To enhance their data literacy, librarians offer a lecture on research data management (RDM) principles and organization strategies. Previous assessments indicate that librarian-led instruction can improve data literacy. In 2025, the lecture was updated to include generative AI tools for RDM. This presentation will describe our instructional approaches to using AI to teach RDM and share preliminary findings from an ongoing study that evaluates the effectiveness of this instructional method. Students participating in this training program complete assessments before and after the lecture, measuring changes in confidence and knowledge through Likert-scale and open-response questions on designing machine-readable datasheets, preserving data, organizing data, and integrating AI tools. While data collection is ongoing, we expect that students will demonstrate increased confidence and understanding in how to manage and analyze their own research data using AI tools.
Learning Objectives:
10:40 AM Improving OCR Workflows using Generative AI
Optical character recognition (OCR) is the process of transforming imaged text into machine actionable text. Corpora of scanned documents or images of documents can be transformed into corpora for data analysis. Tools like Tesseract or ABBYY FineReader have long been the go-to tools for bulk OCR tasks alongside Transkribus for handwritten character recognition (HCR). These tools greatly vary in accuracy depending on the documents, which can often result in much manual review and editing. Further, these tools don't offer much structured output. This presentation details how two data librarians have improved our bulk OCR workflows using generative AI to include structured outputs and accurate results. Learning Objectives:
| Break 11:00 AM - 11:15 AM |
| Poster Sessions 11:15 AM - 12:15 PM | When the data disappears: Adapting reference and instruction to current government data availability
Prior to 2025, the U.S. government was a largely reliable, stable source of social science research data. Given the current state of affairs, the tenuous availability of federal government data is proving to be a challenge for researchers who rely on this data, or who would like to, as well as librarians who support students and faculty of all levels working with government data. To understand how librarians are rethinking education around data literacy and the availability of government and other social science data in the context of this ever-changing landscape, I distributed a survey in spring 2025 to collect information on how librarians were making early adjustments to reference and instruction with social science data writ large. Early findings from the study will be discussed, as well as ways in which librarians can consider adapting their own research and instruction work.
Learning Objectives:
Understanding Your Doctor's Data: A Health & Data Literacy Partnership Between Librarians
As the public navigates increasingly complex health data, libraries are uniquely positioned to bridge the gap between access and understanding. This poster presents Understanding Your Doctor's Data, a collaborative model led by medical and data librarians. Informed by the presenter's national survey on public perceptions of medical librarians, the poster explores how these professionals can work together to address confusion around clinical terms, lab results, and health statistics. Medical librarians offer subject expertise and patient-centered communication, while data librarians contribute data literacy frameworks and visualization skills. Together, they help participants critically assess health information and reduce reliance on unverified sources like "Dr. Google." This poster underscores the role of cross-disciplinary librarian partnerships in promoting health equity and advancing public-facing data education.
Learning Objectives:
A Literature Review of Hosting Multilingual Content in Institutional Repositories
This presentation covers a literature review on multilingual research ephemera in western institutional repositories (IRs). While speculation of anglophone research publication is rampant in the field of scholarly communications as it pertains to academic publishing in peer-reviewed journals, literature covering the theoretics, policies, and case studies exploring non-English, non-Romanized research ephemera in IRs is sparse. As more western universities work towards strong IR infrastructures at their institutions, they must also keep in mind the scholars they support from non-native-English backgrounds when writing policy, conducting outreach, shaping metadata standards and investing in translation resources. Highlighted in this presentation are examples of institutions who have successfully created diverse IRs able to disseminate research ephemera that goes beyond the lingua franca. This presentation will be most beneficial to practitioners in the scholarly communications and data librarianship field, both who interact with their IRs and support non-native-English speakers in disseminating their research ephemera.
Learning Objectives:
Data Reflections: How a data services internship prepares librarians for a modern workforce
As participants of a ten-week summer internship teaching practical skills related to data librarianship, we dove into projects reviewing the metadata fields of an institutional data repository at an R1 university. Through three projects—revising the repository's depositor guide, conducting an environmental scan of metadata fields offered by peer institutions, and reassessing the licenses offered by the repository—we developed recommendations to make the repository more accessible, reusable, and open. This poster will include self-reflection from the participants on how these projects have better prepared them to be data librarians, support open scholarship, ponder strategies of best practices for data preservation, and analyze data structures. This poster will provide valuable insight into the impact of training on the growth of current and recent graduate students so they can become competitive for data librarian positions and grow in this complex and dynamic field.
First Free-Text Field Audit: Three Interns' Investigations of ICPSR's Metadata Schema
As a part of an online internship with a national data education center, we worked with a major social science data archive to examine a free text field in their local metadata schema: "Summary," "Collection Note," and "Data Source." Through our explorations and analysis, we developed recommendations for improving the metadata quality and depositor interface. Additionally, we developed recommendations for the implementation of the CARE principles for Indigenous data governance, investigating how a repository could implement the values and recommendations into their local metadata schema and data practices. In this poster, we will present our learnings and display our growth from our program, explain the skills we developed for the field of data librarianship skills, and demonstrate how the internship program supplemented our MLIS coursework by providing hands-on data experience and access to working professionals in a large data archive.
Learning by Teaching: Developing Resources as a Model for Advancing Mixed Methods Research Proficiency through Experiential Learning
As graduate students participating in a ten-week internship experience, we analyzed a multiple-institution survey facilitated by Weill Cornell Medicine in 2023-24. Because the survey responses included qualitative data, we were given access to MAXQDA, a mixed-methods data analysis software none of us had ever used before. To support our own learning and to create a resource for other new users, we created a LibGuide that documented our process and offered practical guidance. This poster will cover how creating a resource guide for a tool we were unfamiliar with reinforced our own understanding of the software, gave us experience with developing instructional materials, and helped us gain confidence in doing qualitative research. This poster presentation would be of interest to those seeking out internship opportunities, early career professionals, or instructors looking for experiential approaches to student learning.
Integrating Data Reference for Undergraduate Thesis Students in Political Science
Undergraduate students writing a thesis (or similar major research project) face a unique challenge when they need relevant and timely data. Though they may be familiar with sources such as databases or catalogs, students are often stymied by how data differs from other information sources and where and how to search for it. Academic librarians have an opportunity to provide valuable classroom instruction and reference consultations to reduce students' frustration and bolster their research skills. This poster shares the process of developing data-focused instructional materials to support students. Topics covered will include successful implementations and lessons learned for future iterations. Learning Objectives:
| Break 12:15 PM - 1:00 PM |
| Short Talks 1:00 PM - 1:40 PM | 1:00 PM Launching a Data Visualization Lab: Strategies for Maximizing Impact at a Small to Midsized University
This presentation will discuss the process of launching a Data Visualization and Virtual Reality Lab space at Coastal Carolina University's Thompson Library, a new facility that opened in Fall of 2024. Topics covered will include the process for assessing needs for the lab through survey data, planning for implementation and installation, and a discussion of complications that have arisen during our initial rollout of the space. The presentation will conclude with a brief update on the lab's status and our plans for future development and expansion. This information will be useful for data librarians with any level of experience who are exploring launching a similar space at their own institution, as well as those who are in the process of enhancing their data visualization services portfolio.
Learning Objectives:
1:20 PM Hands on data: a protocol for creating low-cost interactive data visualizations displays
Since 2023, our library has created interactive data visualization displays to celebrate International Love Data Week. The annual displays sustain high participation with 400-600 interactions per event. This low-stakes programming offers visitors a fun and accessible way to get involved at the library. It also serves as an informal means to learn about patron interests and preferences. As an added benefit, the data collected can be repurposed for data literacy instruction. This type of event can promote cross-departmental collaboration by customizing the theme of the displays to spotlight new or relevant library resources. Over the years we have developed a protocol that requires minimal time, effort, and resources to prepare the displays. This presentation will review the steps involved in implementing a collaborate data visual display to equip attendees with the necessary information to replicate this experience at their organization. Learning Objectives:
| Break 1:40 PM - 2:00 PM |
| Closing & Social 2:00 PM - 3:00 PM | 2:00 PM Closing Remarks & Birds of a Feather
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