CNI Spring 2026 Membership Meeting

Get acquainted with CNI and the membership meeting! This optional session will provide a quick rundown of CNI and meeting logistics, introductions all around, and time for your questions. Open to all attendees, so you'll be in good company.

Artificial intelligence (AI) has already transformed how people search, read, write, learn, and share information—the very terrain libraries have stewarded for generations. Yet many of the decisions shaping AI policy and adoption on campuses are being made without librarians in the room. In this framing plenary, Rebekah Cummings argues that library values and expertise make librarians essential participants and natural leaders in this critical conversation. Drawing on experiences ranging from a statewide political campaign to co-directing a Summer Institute on Humanities Perspectives on AI, Cummings reflects on her own journey finding a “seat at the table” and shares her conviction that wherever AI touches the information space, librarians must be centered in the conversation. This framing talk will be followed by a panel of library leaders from across the country who are actively shaping campus AI initiatives and demonstrating what it looks like for libraries to lead.

Note: The panel portion and Q&A will not be recorded. 

Access and discovery are at the heart of what academic libraries do.  With the Americans with Disabilities Act Title II’s requirement that public entities’ web and mobile content needs to meet Web Content Accessibility Guidelines (WCAG) 2.1 Level AA standards, libraries and institutions are challenged by the volume of digital content that needs to be remediated and understanding expectations and requirements that impact existing operations in a resource-constrained time. Many libraries are working with partners in legal, disability offices, and IT to explore and find solutions that scale.

This panel will explore these challenges from multiple perspectives and hear about approaches and pathways being pursued at a few institutions. Attendees will be invited to share examples of efforts their organizations are undertaking and their questions to help everyone learn more about this complicated but important area.

Open at Scale: Exploring the Value and Impact of the BTAA's Open Publishing Agreement Model
Maurice York and Jeffrey Spies (Big Ten Academic Alliance)
 
From 2021 to 2024, the libraries of the Big Ten Academic Alliance (BTAA) paved the way for a dramatic increase in open access publishing by Big Ten authors—from 38% to more than 86% open in library-negotiated agreements. This was accomplished by innovating the Open Publishing Agreement (OPA) model, a strategy centered on the author experience: no fees, no caps, and no hassle. This values-based approach has delivered significant benefits for author rights, widespread author adoption, and measurable increases in research impact. This presentation will describe the current effort to explore the network of data from Big Ten publications—citations, authors, disciplines, and institutions—to further analyze the impact of these agreements: lowering barriers, expanding opportunities for authors, expediting knowledge sharing, and advancing research. Utilizing network visualizations, the BTAA is examining indicators of impact, such as shifts in citation patterns and global engagement that are directly evident from this initiative. The presenters will also discuss their strategic negotiation approach, including practical elements they are developing, such as the assessment rubric, license agreement terms, and evidence metrics.

https://btaa.org/library/open-scholarship/strategy

Advancing Open Monograph Opportunities at UC: New Pathways for the Future
Lidia Uziel (University of California, Santa Barbara) and Miranda Bennett (California Digital Library, University of California)

In January 2026, the University of California (UC) Libraries released Advancing Open Monograph Opportunities at UC, a report that articulates a values-driven framework for advancing open access monograph publishing. In this session, speakers will present the report and share how its recommendations are being translated into practice through coordinated pilots across the UC system.

While journal-based open access (OA) models have matured, monographs (particularly in the arts, humanities, and social sciences) pose distinct challenges shaped by disciplinary norms, funding structures, and the publishing economics of long-form scholarship. The report responds to this complexity by advancing a model-agnostic, portfolio-based approach that recognizes the diversity of publishing traditions and avoids reliance on any single funding mechanism.

Four strategic directions anchor the framework: targeted investment in book processing charge-based initiatives aligned with institutional research and teaching priorities; expanded support for Diamond OA and free-to-read models that remove both author- and reader-facing fees while advancing bibliodiversity and multilingual scholarship; strengthened partnerships with university presses as trusted stewards of peer-reviewed work; and sustained investment in open, community-owned infrastructure that ensures discoverability, metadata quality, preservation, and long-term sustainability. These strategies are guided by shared scholarly values, including equity, fiscal responsibility, transparency, and community stewardship.

The session will include highlights and lessons learned from UC's implementation of this framework through systemwide pilots that open UC-authored monographs at no cost to authors, combine frontlist and backlist approaches, and provide predictable, scalable support for university presses. Together, the framework and pilots demonstrate how a large research university system is aligning values with action, offering practical insights for institutions seeking sustainable futures for open monograph publishing.

https://escholarship.org/uc/item/9r22k58w
https://osc.universityofcalifornia.edu/2026/01/advancing-open-monograph-opportunities-at-uc-new-pathways-for-the-future/
https://osc.universityofcalifornia.edu/2026/01/open-access-for-uc-authored-monographs/

Academic libraries are under increasing pressure to deliver fast, high‑quality virtual reference services amid rising demand, staffing constraints, and expectations for always‑available support. Generative artificial intelligence (AI) is frequently marketed as a scalable solution, often without sufficient evidence about where automation might genuinely help or where it may introduce new burdens or risks of suboptimal service. This project briefing details a multi-institutional study of nearly 35,000 anonymized transcripts using a structured natural language processing (NLP) framework. It shares lessons learned from methodological evolution, testing a spectrum of approaches from off-the-shelf interfaces (Microsoft Copilot, Gemini) to a custom-engineered API pipeline. By pairing human expertise with an auditable codebook, the framework generates AI-reasoning trails for every assigned code, allowing researchers to see exactly where model logic aligns with or diverges from professional judgment. The results highlight promising opportunities for responsible automation but also document the extensive iterative cleaning and error-correction cycles necessary to achieve reproducible results. By foregrounding these insights and the often-invisible labor required, the session will provide library leaders with a realistic roadmap for responsible AI integration, moving beyond theoretical promises to offer evidence-based guidance on staffing, workflow design, and long-term strategy in scaling AI-assisted virtual reference.

In January 2026, the University of Virginia Library conducted the first of many proposed hands-on exercises to test four major large language models' (Anthropic's Claude, OpenAI's ChatGPT, Google Gemini, and Microsoft CoPilot) suitability for the transcription and translation of handwritten documents from the University of Virginia Library's special collections. Thirty-two staff members from multiple disciplines were given standard prompts and rubrics for evaluation, divided into groups, and given an opportunity to select an item to scan and provide to each LLM for transcription, and, if necessary, translation. Time was provided at the end for groups to share their findings and key insights. This initial exercise will be used to calibrate prompts and rubrics for similar events that will be held to continue evaluation of LLMs for processing of collections, and to inform faculty, students, and researchers on the effective use of these tools.

 https://library.virginia.edu/news/2026/gamechanger-can-ai-accurately-transcribe-primary-source-documents

Thousands of institutions have adopted the International Image Interoperability Framework (IIIF) to provide access to digitized collections, yet the content served through these APIs, including hundreds of thousands of maps, remains largely undiscoverable by location and difficult to use across institutional boundaries. Allmaps is an open source ecosystem that enables anyone to curate, georeference, and explore these resources without requiring GIS expertise or specialized infrastructure. In 2025, following the termination of a National Endowment for the Humanities grant, the IIIF Consortium formalized a tiered partnership with Allmaps to sustain its development. This is intended to be the first in a broader effort to help institutions realize the collective value of the content their shared infrastructure makes accessible via IIIF. This briefing will present the strategic rationale for this new consortial model from both the IIIF Consortium and Yale University Library, an early Allmaps Innovator. The session will explore how the partnership delivers tangible benefits to the community, from lowering barriers to georeferencing and cross-collection map discovery, to providing institutions with crowdsourcing tools, integration services, and governance participation without requiring specialized GIS infrastructure. Discussion will focus on how consortial organizations can move beyond standards-setting to actively steward and unlock the value of the content communities have collectively invested in digitizing.

https://allmaps.org/iiif-partnership

The University of Texas Libraries (UTL) entered into a charter program with ITHAKA in the fall of 2025 with the objective of testing Seeklight, JSTOR's artificial intelligence (AI)-based metadata generation tool. The goal for the first year of the charter was to test the quality of Seeklight's metadata output and its compatibility with multilingual and complex records. UTL evaluated the quality and changes over time over several months of testing, using born-digital and digitized records sourced from UTL's Benson Latin American Collection and Alexander Architectural Archive. The rubric used during this testing period is a four-point, subjective rating scale, which was developed by UTL's AI Metadata Creation Working Group during earlier tests with out-of-the box LLMs. This presentation will highlight our initial impressions of Seeklight's metadata output on a field-by-field basis. We will explore UTL's continued testing of Seeklight and its current ability to provide the subject knowledge and enhanced discoverability needs for archival records.

As artificial intelligence (AI) companies increasingly seek access to archival collections for model training, archival organizations face high-stakes decisions with limited precedent and no shared standard. The University of Virginia (UVA) Library has developed the UVA Archival AI Protocol (UVA AAIP), a practical framework grounded in a core rule: irreversible AI models do not get access to archival materials unless item-level provenance and meaningful attribution can be demonstrated, and the institution retains contractually enforceable control to stop further use. The Protocol distinguishes between retrieval-based AI systems—which keep source materials under institutional control and are generally permitted—and general-purpose model training, which absorbs knowledge into model weights irreversibly and is blocked by default. Built on three foundational pillars (provenance and attribution, donor and community responsibilities, and institutional control), the Protocol provides a decision framework for evaluating AI requests, sample contract clauses for deeds of gift and vendor agreements, minimum provenance standards for AI-generated citations, and a phased implementation plan designed for organizations of any size. This briefing addresses both the strategic rationale for the Protocol and the practical realities of putting it into action. Attendees will leave with a freely available adoption kit—including customizable templates, sample clauses, and implementation checklists—that any archival organization or memory institution can use to establish a principled, consistent position before the next AI partnership request arrives.

https://doi.org/10.18130/5dqf-9w86

The injustices embedded in the collecting and descriptive practices of libraries, museums, and archives are now widely recognized and have prompted many cultural institutions to pursue inclusive and reparative initiatives, such as harmful language statements and content warnings. Remediating outdated and offensive language in metadata is, however, a far more daunting task, especially at scale. While resources like the Inclusive Metadata Toolkit support informed reparative decision-making, identifying problematic terms remains a tedious and emotionally taxing process dependent on individual keyword searching. Consequently, many institutions either lack the time and resources to engage in this work or are constrained by the sheer volume of potentially harmful language present in metadata records. With the support of an internal library seed grant program, the J. Willard Marriott Library at the University of Utah  developed the Marriott Reparative Metadata Assessment Tool (MaRMAT), an open source, schema-agnostic, Python-based application for bulk metadata assessment. MaRMAT assesses tabular metadata against pre-curated and custom lexicons, generating a report flagging potentially harmful terminology by field, category, and context. By making large-scale assessment more accessible, MaRMAT empowers cultural heritage organizations to circumvent individual bias and advance equity in digital collections. MaRMAT's successful development also demonstrates the impact of small seed grant programs.

https://www.marmatproject.org/
https://github.com/marriott-library/MaRMAT

As generative artificial intelligence (AI) reshapes how students conduct research, academic libraries face a critical opportunity to redefine their value proposition. This session presents findings from two years of research with over 1,000 undergraduate and graduate students across disciplines, revealing that while AI chatbots have become essential cognitive partners for brainstorming and navigating complex research, students consistently turn to library resources for credibility verification and validation. The data demonstrates that students are thoughtful, skeptical consumers of AI who routinely cross-check AI-generated content against library sources, who view AI outputs, particularly citations and reasoning, with appropriate caution. Rather than displacing libraries, AI has elevated their role as the authoritative validator underlying AI-mediated workflows. This research offers evidence-based insights to inform strategic decisions around discovery systems, research support services, and resource access in an AI-integrated environment, positioning libraries not as competitors to AI tools but as essential stewards of trustworthy, credible knowledge in an era of information abundance.

Building Infrastructure by Investing in People: Seven Years with CollectionBuilder
Evan Williamson, University of Idaho

Introduction to Project VECTOR, Creating Open Engineering Visualizations
Macarena Lange, Colorado State University

Deploying an AI Sandbox: A Libraries-Led Service Pilot for Scalable Research Infrastructure  
Varun Sayapaneni, University of Oklahoma

Facilitating Use of Unencumbered Publications as Data for AI
Nicholas Taylor, Los Alamos National Laboratory

JOLT: A Tool for University of California Authors to Find Journals with Open Access Fee Support
Jade Yonehiro, California Digital Library

Persistent Identifiers for Facilities and Instruments: Supporting FAIR Data Collections
Matthew Mayernik, National Science Foundation National Center for Atmospheric Research

Operationalizing Quantum Computing Through the Academic Library
Seth Porter, University of Colorado Colorado Springs