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Jenna Hartel

An Award-Winning Conference Paper and An Educational Video that Situate Generative AI in Library and Information Science

The paper, “Theorising Notions of Searching, (Re)Sources, and Evaluation in the Light of Generative AI” (Sundin, 2025) won the Best Long Paper Award at the 2025 Conceptions of Library and Information Science (CoLIS) conference in Glasgow, Scotland. For me, reading it sparked a eureka! moment. The author, Olof Sundin, argues that generative AI has a precedent in the European Documentation movement of the early 20th century. In addition to historical insights, the paper analyzes how today’s search systems increasingly provide answers or facts, whereas conventional retrieval tools point information seekers to sources.   

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Shalini Urs

The Commons of Science—Why It Takes a Village: Christine Borgman on Collaboration, Curation, and the Invisible Infrastructure of Knowledge

This article examines the evolution of scientific knowledge infrastructures through the influential work of Christine L. Borgman, Distinguished Research Professor at UCLA. Framed around the concept of science as a commons, it traces a three-decade transformation—from digital libraries in the 1990s to cyberinfrastructure in the 2000s, culminating in today’s sociotechnical framing of knowledge infrastructures. Borgman’s scholarship highlights how data acquire value not in isolation, but through complex systems of people, practices, tools, and institutions that enable their curation, sharing, and reuse.

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Shalini Urs

Reframing Information: From “Information as Thing” to “Everything as Document” to the Identity of iSchools — Conversations with Michael Buckland

Michael Buckland, a pivotal figure in information science, has profoundly shaped the field through his scholarship and leadership. In this episode of InfoFire, Buckland engaged with me on foundational concepts, practical applications, and historical perspectives, offering provocative critiques that challenge conventional thinking. He declared “information” a problematic term— “It is a bad word; it is to be abolished”—arguing that its overloaded meanings obscure clarity. Similarly, he labeled bibliometrics a “pseudoscience,” questioning its methodological rigor. These rhetorical provocations underscore his effort to reframe information science around precise, document-centric frameworks.

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Shalini Urs

LLMs, AI, and the Future of Research Evaluation: A Conversation with Mike Thelwall on Informetrics and Research Impact

In this episode of InfoFire, I sit down with Professor Mike Thelwall, a well accomplished scholar of Informetrics, to explore the intersections of Large Language Models (LLMs) and research evaluation. We delve into how LLMs are reshaping the landscape of research assessment, examining the promises they hold and the challenges they present in ensuring fair, meaningful, and context-aware evaluations.

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