Data Culture in Academic Libraries: A Practical Guide to Building Communities, Partnerships, and Collaborations, Marcela Y. Isuster and Alisa B. Rod (eds.), Association of College and Research Libraries, 2025. 326 pp. Softcover, $98.00. 9798892556156.
Data-related research is, as editors Marcela Y. Isuster and Alisa B. Rod note, increasingly “a driver of social capital in the academic context” (p. ix) and an impetus of rising demand for data literacy and innovative, expansive data-related research services. To address these needs, academic libraries are increasingly focusing on the strategic development of data culture, which refers to “the norms, values, skills, and behaviors that shape how data is produced, shared, and used in a given context” (p. ix). This practical guide is a novel contribution; it offers academic and data librarians working in diverse roles concrete ways to approach fostering data culture and community at their own institutions, as well as broader ways of examining what data is, how it is produced and collected, and how to teach its ethical analysis, management, and use.
The editors structure the book in five loosely thematic sections. Most chapters share emphases on practical guidance, interdisciplinary and cross-institution collaboration, and strategies for building trust within and across communities. The chapters in Section I: Data at All Levels share approaches to incorporating data best practices into the academic culture and curriculum. Section II: Data Services and Instruction offers more conceptual chapters describing innovative ways of thinking about data within the context of data literacy training and data services. Section III: Data Outreach offers numerous accessible, practical examples of activities, events, and initiatives that academic librarians can employ to promote data culture in their home libraries, as well as reflections on lessons learned and future directions for these projects. Sections IV: Data Communities and Section V: Data Partnerships overlap more, as they both present chapters focused on the collaborative development of data partnerships, relationships, and communities.
Befitting a practical guide, the chapters largely avoid disciplinary jargon and offer clear definitions of key terms, such as research data management (RDM), research information management (RIM), and FAIR principles (findability, accessibility, interoperability, and reuse). A key strength of the book is its clear situation of data practices and culture within a variety of institutional contexts, from large research universities to multicampus university systems and small liberal arts colleges. Librarians seeking ways to promote their own data culture initiatives will find a wealth of resources, such as checklists and considerations for hosting a Love Data Week (Chapters 11 and 12); screenshots of materials prepared for K–12 educators using Michigan historical archive data (Chapter 1); ideas for hosting a Dear Data visualization project (Chapter 13); and considerations for creating asynchronous online research data management trainings (Chapter 6). The DataSquad model from Carleton College charts a detailed path for student-worker-led data support services (Chapter 15), and staff from UC Berkeley’s Ready4Research program describe how it prepares nontraditional students for research support roles (Chapter 3). Other chapters offer narratives of how services and outreach initiatives were built at their libraries (Chapters 8, 10, 14, 19), including two chapters outlining the history and development of the Canadian data repository Borealis (Chapters 20, 21).
Alongside this practical information are several chapters introducing conceptual frameworks. Librarians from Florida International University describe the biology-inspired model of “data mutualism” between libraries and service communities (Chapter 18). The “archival ethics of care” in Chapter 7 contextualizes the need for a critical data literacy that emphasizes “trust, accountability, and empathy” (p. 100) within the increasing digitalization of historical and archival materials available at GLAM (galleries, libraries, archives, and museums) institutions. Throughout the volume, authors reflect on the potential biases, limitations, and distortions inherent in data practices and data visualization, which are important considerations for librarians when designing training and community outreach. Data best practices are clearly positioned within broader social and institutional realities, offering a realistic understanding of the challenges, as well as the benefits, of nurturing an ethical data culture in an academic library context.
While this book represents a wide-ranging, ambitious addition to the field, it is not without its limitations. The institutions represented are almost exclusively Anglo-Western (primarily the United States and Canada), with only one institution based in Asia (New York University Shanghai, Chapter 17), and none in Africa or South America. Moreover, although the book includes a careful and thought-provoking chapter on the limitations of data on racialized and Indigenous populations in Canadian data repositories (Chapter 16), its authors acknowledge that they are not racialized or Indigenous people themselves. It would be would be immensely helpful if future volumes with a similar focus on practical guidance alongside theoretical approaches incorporated a greater diversity of institutions and perspectives, particularly given the relationship between a strong data culture and increased social capital that is reiterated throughout the book. Another surprising omission is a lack of focus on the enormous implications of generative artificial intelligence (GenAI) for data literacy and data culture, with only Chapter 17 paying sustained attention to this rapidly proliferating area.
These considerations notwithstanding, the ideas and approaches in Data Culture in Academic Libraries: A Practical Guide to Building Communities, Partnerships, and Collaborations are accessible, scalable, and adaptable for academic librarians and data professionals with a range of expertise and resourcing, including long-time professionals and those at large research universities, as well as early career librarians and those at less-resourced institutions. The rapidly changing data environment requires innovative approaches to data culture; thus, whether the goal is to support curriculum-driven data literacy, strengthen RDM infrastructure, or foster community around data best practices and ethics of care, Data Culture in Academic Libraries is an invaluable resource that should be seriously considered by academic libraries of all types and sizes. — Megan J. Callaghan, MLIS student, Valdosta State University, and Professional Writing Consultant, Augusta University
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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