Optional orientation session for new attendees (representatives of new member organizations and new representatives or alternate delegates from existing member organizations); guests and presenters are also welcome.

Why do we even care about data? What value do data bring us and what value do humans bring to the data landscape? As artificial intelligence (AI) becomes the default in data conversations, data curators are thinking critically about what this means. Intentional efforts from professionals such as curators invested in making data FAIR (findable, accessible, interopable, and reusable) are key to preserving the meaning of data. There is unique value and importance in people's labor and experiences when documenting and preserving data. It is the people who dig into the context and elevate what is missing to help make the data more FAIR. The session will address a project from the Data Curation Network (DCN) funded by Institute of Museum and Library Services grant [re-252343-ols-22] to support the development of a specialized curriculum for data curation training for information professionals and data stewards. Key to this work was drawing together data curators and information professionals to create in-depth training resources for four specialized data types: geospatial data, scientific images, code, and simulations. Using a cohort model with a guiding mentor, the project relied upon co-developing strategies to effectively and equitably work with volunteers to generate community-based resources. Community building, co-designing, bringing people from different types of disciplines, data backgrounds, and experiences are equally as important as developing a curriculum and sharing it. In fact, the curriculum benefits from and is made stronger when various intersectional voices are present. In this project briefing, the mentors will provide an overview of the community building that went into forming cohorts that developed, piloted, and refined specialized data curation curriculum, reflect on what worked well and where there are opportunities, and they will describe directions for future DCN work as well as how others can adapt this work for their own needs. The value that data curators in community bring to institutions, researchers, and data reuse will enable greater usability of data into the future.

https://datacurationnetwork.org/expanding-curation-training/

This briefing shares 18-month outcomes from a collaborative initiative among research libraries and iSchools at Virginia Polytechnic Institute and State University, the University of North Texas, the University of Colorado Boulder, and Los Alamos National Laboratory. This initiative aimed to strengthen academic libraries' role as research partners and promote library and information science research collaborations. The program combines open-access training, seed-funded collaborative projects, and structured fellowships. Outcomes include institutional policy reforms that recognize research contributions as a vital element of library staff career advancement and cross-departmental partnerships addressing digital scholarship, data curation, and other key priorities in library settings. The session highlights strategies for aligning workforce development with organizational priorities, including adaptable funding frameworks and mentorship models for early-career professionals. Presenters will discuss lessons learned from coordinating implementations across distinct academic libraries and sustaining a cultural shift toward research-intensive collaboration.

https://jointpdi.github.io/
https://prolearning.unt.edu/unt/course/course.aspx?catId=130
https://lib.vt.edu/center-for-digital-research-and-scholarship/program/grant-page.html
https://library.unt.edu/deans-innovation-grant/

The HBS Knowledge platform is a dynamic knowledge graph designed to enhance the discovery and integration of research, people, and ideas across Harvard Business School (HBS). First launched in June 2021 and rebooted in March 2025, the platform connects structured and unstructured data from heterogeneous sources across HBS, creating a rich network of insights. In the session, the presenters will explore how the graph was built, the ongoing data workflows that keep it up to date, current use cases, and their vision for further development. They will describe the technology stack and main challenges and learnings as they continue to iterate on the platform. With plans to leverage its structure for advanced semantic search and as a foundation for artificial intelligence-driven applications, HBS Knowledge represents a crucial step toward more intelligent and connected academic discovery and resources for administrative departments on campus.

As vast stores of research metadata built on persistent identifiers (PIDs) continue to grow, challenges around data siloing and inconsistent metadata quality have become increasingly evident. While various stakeholders-libraries, publishers, repositories, and discovery systems-have made significant localized efforts to address these issues, a unified, scalable approach has been missing. The Collaborative Metadata Enrichment Taskforce (COMET) emerged to fill this gap, convening a series of community-driven engagements in late 2024 and early 2025 to chart a collaborative way forward. This session will highlight how COMET is transforming isolated metadata curation efforts into collective value through the development of an open infrastructure service. The service will enable stakeholders to surface, share, and contribute validated metadata improvements, enhancing the quality and interoperability of the scholarly communications ecosystem. The presentation will provide insights into COMET's progress, including identified use cases, governance models, and upcoming pilot projects, while inviting further collaboration from the community.

https://www.cometadata.org

The panel will discuss how community-owned and -led digital infrastructure can, and should, incorporate contingencies for sunsetting into sustainability planning and how to embody core values and address diverse member needs throughout the sunset process. Through its twenty years of operation, MetaArchive, the first and longest-running Private LOCKSS Network (PLN) has been consistently defining what it entails to be a digital preservation network created and hosted by and for memory organizations. Now, as the first PLN to undergo a deliberative sunset, there is the opportunity to share lessons in how endings can be carried out with as much intention and care as beginnings. In a time of field- and nation-wide change and transition, investments in shared infrastructure and inter-institutional communities of practice are more valuable than ever for building a resilient information ecosystem-only collectively can we guarantee access to our cultural heritage in the long term.

https://metaarchive.org/metaarchive-leads-pln-transformation/
https://metaarchive.org/metaarchive-is-sunsetting-updates-and-learnings-from-a-community-in-transition/

Leveraging Artificial Intelligence for Improved Transcription in Special Collections and Academic Libraries

The Georgia State University Library houses an extensive collection of audio-visual assets that serve as invaluable resources for research and education, including oral histories, television and radio broadcasts, labor union meetings, and more. Historically, the process of transcribing these sensitive materials has been labor-intensive and time-consuming. This project briefing will explore an in-progress project to create a custom user interface for OpenAI's Whisper automatic speech recognition system to improve the processing of these materials. It will discuss the motivations and needs assessment for the project, project planning, development and challenges, and system testing and refinement, in addition to reporting on any findings regarding the project's impact on efficiency, accessibility, and cost savings.

Leveraging Consumer-Level Artificial Intelligence for Descriptive Metadata Creation in Archival Collections

The University at Buffalo, University Archives is leveraging consumer-grade artificial intelligence (AI) to enhance the creation of descriptive metadata for over 2,000 hours of audio in the UB-WBFO Radio Archive. Utilizing Microsoft Copilot, this initiative aims to produce concise and detailed program descriptions from audio transcriptions, facilitating inclusion in the University Libraries, Digital Collections, and the National Archive of Public Broadcasting. By developing targeted command prompts paired with transcription files, archivists have drastically reduced processing time, generating generic summaries efficiently. This innovative approach not only improves access to archival content and exemplifies the impact of AI on archival practices but also evidences how entry-level or consumer-grade AI tools can be integrated successfully into project workflows.

Designing SpeakEZ: An AI System to Transcribe and Process Audio and Video Collections

Over the past five years, the Louie B. Nunn Center for Oral History in the University of Kentucky Libraries has accessioned an annual average of over 1,000 new oral history interviews into the archival collection, exceeding the staff's capacity to process. This presentation reflects on designing the SpeakEZ system using AI and natural language processing to transcribe and process the Center's rapidly growing oral history collection, totaling over 20,000 interviews. SpeakEZ consists of automated transcription, the generation of new dimensions of descriptive metadata, the OHMS-ifier, which prepares draft versions of time logs/indexes for use in the Oral History Metadata Synchronizer (OHMS), and finally, the Riskalizer, which assesses and evaluates content for various points of potential sensitivity. The session will include discussion of the system's successes and role in addressing accessibility requirements, some of the design and workflow challenges introduced by the system, and possible applications of SpeakEZ for libraries beyond archived oral history collections.