abstract: In academic librarianship, calls to teach a version of artificial intelligence (AI) literacy that requires generative AI (GenAI) use are usually accepted as common sense. Most in our profession would agree that libraries and instruction librarians need to respond to technological changes and to help prepare students to engage with the research tools available to them. At the same time, the well-documented costs and harms bound up in the development and use of GenAI technologies are in conflict with the values and goals of many librarians, especially those who align their teaching with critical pedagogy principles like examining systems of power and social and political inequities, investigating assumptions and working for a more just world, and affirming student and teacher agency. To explore current and potential ways to teach about GenAI technologies through a critical pedagogy lens, I examine discourse on (critical) AI literacy and related resources and how they reflect or deflect critical pedagogy principles.
abstract: Linked data technologies present significant opportunities for enhancing interoperability across distributed information systems. This article examines linked data as a boundary object that facilitates knowledge exchange between heterogeneous communities, while addressing technical challenges in representing diverse epistemological frameworks and advancing epistemic justice. Through an analysis of three implementation cases—Mukurtu, Wikidata, and Linked Jazz—this study demonstrates how linked data architectures can accommodate varied knowledge representation requirements while maintaining technical coherence. The findings suggest that boundary object theory offers a valuable framework for understanding and optimizing linked data implementations in culturally diverse contexts, revealing patterns of epistemic mediation that can inform the design of more equitable knowledge infrastructures.
abstract: Artificial intelligence (AI), large language models, and their associated crawlers are the newest users for university libraries, special collections, and institutional repositories. Generative AIs want data from library collections and repositories for training their models. In some cases, they ask for it through the robots.txt protocol. In other cases, they cause accessibility issues for repositories and create copyright concerns. This article investigates these issues and offers potential solutions, including donor outreach and communication, working within the system, and enacting restrictions. Ultimately, we conclude that the development of sustainable, ethical, and effective strategies for dealing with AI cannot rest on the shoulders of individuals. Digital librarians, archivists, professional societies, and working groups must have conversations that work through these tensions between digital collections and AI tools while still advocating for our digital creators and meeting our patrons’ research needs.
abstract: This article investigates how Romanian librarians interpret and apply the principle of neutrality across traditional library services and digital platforms, using Wikipedia as the functioning model. Based on semistructured interviews with thirteen professionals from public libraries and academic institutions, the study explores how neutrality is understood and practiced in the context of a postsocialist, semiperipheral European country. Although professional codes of ethics define neutrality as a core value, participants often described it as a strategy for avoiding conflict and protecting themselves in politically sensitive or under-resourced environments. Wikipedia’s Neutral Point of View policy provides an evidence-based model that some librarians found useful for clarifying their approach to neutrality. This research found that tensions emerged between institutional policies, personal beliefs, and public expectations, especially in rural areas where librarians often work in isolation and face local political pressures. Findings reveal a gap between abstract ethical standards and day-to-day practice, shaped by historical censorship, uneven professional training, political interference, and a culture of cautious engagement. This study offers an Eastern European perspective to discussions on library ethics and concludes with recommendations for developing locally grounded training programs and updating ethics codes to better support librarians in physical and digital service contexts.
abstract: This article draws on queer theory to explore the tensions between openness and regulation in library and information science against the backdrop of historical and digital protest media produced by student activists. It examines how these shifting dynamics inform the evolving role of the library in today’s digital era, characterized by information disorder. I begin by outlining queer theory’s utility for this project, highlighting its capacity to subvert existing identity categories beyond gender and sexuality and to embrace broader counterhegemonic possibilities without reinscribing binaries. I then analyze the indeterminacy embedded in historical banners and daejabos from the Kent State shootings and the Gwangju Uprising, as well as in contemporary livestreamed protest videos, to situate them within a continuum of queer media forms that challenge traditional information literacy concepts such as authority and coherence. From there, I trace the shift in libraries’ podcasting initiatives from faculty-driven research tools to platforms for student creativity, constructing this evolution as a library-driven queer turn toward openness, even within digital infrastructures that appear to demand tighter regulation. Ultimately, the paper calls for a queer reimagining of pedagogy and practice, open to indeterminacy, where students are empowered as agents of resistance and meaning-making through self-regulation.
abstract: This article explores the tension between generative artificial intelligence (GenAI) and library reference service as options for information seeking, arguing that with the recent proliferation of GenAI tools, we have entered a post-reference epoch. This epoch is defined by a change in not only where and how patrons may seek information but their expectations of that information. After refining the idea of the “post-reference epoch,” the article outlines specific sites of tension between the values of generative AI and the values of academic librarianship, as well as potential futures for library reference service. This article’s AI-skeptical stance envisions the post-reference epoch as an opportunity to review past services and revise service provision to reflect new knowledge. The lack of immediate answers to questions about the future of reference is the most compelling tension we will explore; our first steps along this path will be guided by critical theory, Marxist theory, and the philosophy of information. We seek not to resolve this tension within a single article but to begin charting a potential path toward new definitions of value and service.
abstract: This article examines the ethical and operational tensions inherent in archival commemoration, using the Northern Illinois University February 14, 2008 Memorial Collection, which documents a devastating mass shooting on campus. The article questions whether this and similar efforts can truly facilitate catharsis or inspire action against gun violence, given the materials’ limited use and the community’s measured reluctance to engage with the trauma. The central tension explored is between collecting for utility, where the archive must yield practical lessons for change, and collecting for posterity, which fulfills a social desire for enduring memory. The open-ended, affect-driven collecting strategy led to an emotionally potent but unwieldy resource. Drawing on Pierre Nora’s concept of lieux de mémoire (sites of memory) and the notion of temporal subjectivity, the article considers how the archive institutionalizes historicized memory and trauma. The author grapples with the ethical burden of promoting the collection’s value without exploiting the victims’ story, ultimately asking whether this enduring commemorative effort risks becoming a durable, but ultimately impotent, monument to grief.
The 2024 Standards for Library Services for the Incarcerated or Detained establishes an expanded vision for the intellectual freedom of incarcerated people. In California, reforms implemented across the state correctional system helped create an environment where educational programming could take root. The "California Model" signaled expansion of the state's commitment to improving the lives of incarcerated people. One "pillar" of the model, normalization, seeks to make life in prison as close as possible to life outside alongside a renewed commitment to educational programming. As part of this approach Fresno State created the Degrees of Change program to establish in-person college courses at two penal institutions in Chowchilla, California. As academic librarians at Fresno State, we were asked to share our expertise as the program took shape. As our involvement grew, difficult questions arose. What does intellectual freedom mean where freedom is denied? Could our university's presence implicate librarians and educators in a "normalization" of prisons? How can librarians work toward abolition of prisons without jeopardizing our incarcerated students' information access? Abolitionist librarianship requires critical practice and taking tangible actions to build solidarity with incarcerated people and our wider communities.
This article explores inclusive approaches to data literacy in academic libraries through a case study of Python Camp, a four-day introductory programming workshop offered by George Washington University Libraries and Academic Innovation. We position computational literacy as a dimension of data literacy, emphasizing the ability to engage with data through code, modeling, and algorithmic reasoning. Unlike traditional boot camps that prioritize technical skill acquisition, Python Camp fosters collaborative learning, frames computation as a communicative and exploratory act, and embeds coding within interdisciplinary, context-rich problems. Drawing on facilitator reflections and semistructured interviews with participants, we argue that academic libraries are uniquely positioned to challenge exclusionary norms in data education. Our pedagogical approach centers relevance, learner agency, and ethical engagement with data, aligning with broader library trends toward inclusive, user-centered instruction. We describe how our team-based model supports a growth mindset and inclusive learning culture through varied lesson structures, reduced educator bias, and peer communication. We conclude by framing computational literacy as a social, situated practice. More than acquiring syntax, it is a process of building fluency, confidence, and relevance. Library-based data literacy programs that foreground ethical, critical, and user-centered approaches can broaden access to computational tools while modeling inclusive pedagogy. Reflection by both participants and facilitators is essential, not only for assessing program effectiveness but as a core practice of inclusion itself.
This study investigates community college students' perceptions of data literacy, specifically its perceived relevance and importance, and explores whether their demographic characteristics can predict these perceptions. Survey data from a sample of 445 students across five community colleges in the United States were analyzed. The study findings indicate that community college students see data literacy as imperative for career readiness. Various demographic characteristics, including personal attributes and educational and employment-related characteristics, were found to be factors predicting students' perceptions of the relevance and importance of data literacy. These findings emphasize the necessity for community colleges to integrate data literacy into the curriculum and prepare students for future career attainment.
American public opinion polls show a sustained and substantial loss of faith in the institutions that were historically trusted to establish and convey knowledge. Institutions produce and disseminate broadly accepted knowledge in many ways, and data is often a critical part of the process. Unsurprisingly, then, the loss of faith in these institutions is also manifesting as a lack of faith in the data that they create and disseminate. In this environment, teaching data literacy using traditional information literacy-based methods, emphasizing criteria such as authority and credibility, is extremely challenging. A vital part of effective education has always been meeting students where they are. In this distrustful moment, how can librarians find an initial point of agreement with students and work from that point toward a productive and literate approach to understanding and using data? This article argues that the recently emerged field of critical data studies provides such a starting point and offers some ideas for integrating concepts from critical data studies into information literacy instruction sessions.
As personal data collection and use grow in the digital age in the United States, people can work to protect their personal information from misuse by learning personal data literacy skills. This is especially true as policy changes in the United States and the use of data by law enforcement put immigrants in a more vulnerable position. Situated in the current social and political context, this article aims to create a case for why personal data literacy is more critical than ever, particularly for noncitizen immigrants, and why public libraries are well positioned to provide training for those skills. This article will include some recommendations for incorporating personal data literacy into existing programs for public library users, framed within specific issues that may concern not just noncitizen immigrant library users but all users who might be interested in making informed decisions about their personal data.
Every day, people are tasked with analyzing data to make decisions that impact their personal lives. Yet data literacy education initiatives for the public are limited. When such initiatives are supported by public libraries, they are usually targeted toward specific domains or audiences, such as workforce data literacy or census data literacy. This is problematic because an everyday life data-literate public fosters community resilience and produces data citizens who actively work to improve their quality of life. Still, more research is needed to determine how data literacy fits into community contexts. To better understand this phenomenon, Walker and Avant's concept analysis approach was used to develop an operational definition of community data literacy and compare its attributes with a model case of adult literacy, numeracy, and adaptive problem-solving skills from the Program for the International Assessment of Adult Competencies. Findings from the analysis show that community data literacy strongly correlates with Program for the International Assessment of Adult Competencies Level 3 proficiency levels in literacy and numeracy. As a result, it may be concluded that community data literacy can serve as a surrogate of critical literacy in public libraries' adult literacy programs.
This article offers a case study of the two-semester experiential-learning course designed and taught in Fall 2023 and Spring 2024 by the Georgia State University Library's Research Data Services faculty. Tied to the Public Interest Data Literacy (PIDLit) grant-funded initiative, the Tackling Food Insecurity PIDLit Learning Lab course connected students with community partner organizations to apply data skills to address the real-world problem of food insecurity. The article details the partner-driven quantitative and qualitative data collection, analysis, and reporting activities in which students engaged. It next introduces the course content and array of assignments, available as open educational resources, which were geared to develop students' data literacy skills. It then presents findings from mixed-methods course evaluation measures, including a quantitative pre-post assessment of students' data literacy attitudes, knowledge, and skills teamed with a qualitative thematic analysis of their end-of-semester reflections. It concludes by offering lessons learned for others who wish to develop and teach similar applied data literacy courses or smaller-scale curricular units.
Data literacy transcends disciplinary boundaries, yet academic libraries often struggle to provide inclusive support that bridges science, technology, engineering, and mathematics (STEM) approaches with humanities and social sciences needs. At Carnegie Mellon University Libraries, we have developed an interdisciplinary approach to data literacy that addresses this challenge. Drawing on our individual expertise in arts and humanities, anthropology and archaeology, and psychology and social sciences, we support diverse disciplines by equipping researchers with the skills needed to work meaningfully with data. Our approach positions data literacy at the intersection of critical thinking, technical competence, and ethical awareness- emphasizing that all data emerges from specific social, cultural, and political contexts. This paper examines our implementation strategies, including individual consultations, workshops, core competency development, and course-embedded instruction. We demonstrate how data literacy can be contextualized across disciplines while challenging STEM-centric models that privilege quantitative over qualitative approaches. Our work has influenced university policy and enhanced student engagement with data concepts, particularly in communication and critical assessment. Through an analysis of our experiences, we offer a perspective for other librarians seeking to develop similar educational initiatives that empower researchers across academic communities, recognizing that effective data literacy instruction must respect diverse epistemologies while building essential capacities for participation in data-driven discourse.
To support graduate students in managing their research projects through temporal gaps, we created a research data management guide for graduate students, providing easily implementable practices that can be integrated into projects and workflows with as minimal burden as possible to the student or interruption to their team. This quick-start guide is designed to teach graduate researchers data literacy through the curation of their own project materials. In other words, by learning curation best practices and integrating them into an existing research project-where they have a vested interest in seeing the project succeed-graduate students can also become comfortable with how to evaluate data for use in their future research, how to set up projects from the beginning to plan for starts and stops in the work, and how to effectively manage and describe project materials.
As academic libraries expand research data services, library and information science programs face growing pressure to prepare graduates for data-intensive roles. This study examines data-related course offerings in forty-nine American Library Association-accredited programs (232 courses total) through content analysis of course titles and descriptions collected in 2022. The analysis reveals a significant curricular imbalance: Over 70 percent of the courses emphasized technical skills (data science, programming, infrastructure), while fewer than 5 percent explicitly addressed service delivery competencies that practicing librarians identify as most critical. This mismatch between educational emphasis and professional practice requirements has implications for program directors developing curricula, accreditation standards, and hiring institutions evaluating graduate preparedness. The study also documents substantial resource inequality, with three institutions offering 22 percent of all identified courses, while twenty-eight programs offered fewer than five courses each. These findings suggest three priority actions for library and information science education: integrating service delivery training with technical coursework, developing strategic cross-departmental partnerships, and establishing clearer terminology around data science education.
The Civic Switchboard project works to advance libraries' critical role as "civic data intermediaries," or organizations that help individuals find, understand, and use open civic data. Since 2017, Civic Switchboard has focused on developing library workers' civic data literacy, enabling them to serve as local data intermediaries in their communities and, in turn, grow patrons' civic data literacy. This article introduces the Civic Switchboard project's practical, theoretical, and communal approaches to civic data literacy. Because we define civic data as data about our communities, we emphasize communities and a local context in our literacy effort. We introduce three theories and methods that have guided our development of online resources, workshops, and a community of practice: adult learning theory, paper-based data literacy methods, and data justice scholarship. In this paper, we address the value of these approaches to civic data literacy and the ways that these approaches are manifested in our work. We contend that such approaches make civic data literacy education local and personal, giving more grounding and meaning to abstract data literacy concepts. We offer recommendations for library-centered civic data literacy programs that emphasize local relevance, reduce technical barriers, build peer learning networks, and integrate justice principles, ultimately enabling libraries to better serve as intermediaries that help community members engage critically with data affecting their lives.
