In this episode of InfoFire, I speak with Dr. Stephen Robertson, a pioneering figure in the field of Information Retrieval (IR), who offers a reflective account of its conceptual and methodological evolution.
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This editorial contains four topics of importance to the Journal. The first topic is to celebrate our expert reviewers, some by name. Second, we discuss the move to Wiley’s Research Exchange for submissions. Third, we discuss the Journal’s expectations of data sharing, balancing both with the emerging norms of more scientific openness and the realities of what is possible given the different funding, ethical, legal and operational arrangements that scholars face. The fourth topic is the Journal’s stance on uses of artificial intelligence.
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In the world we are living in, a digital world, some data slips past our awareness, but very little data ever truly disappears. As we, information scientists, are concerned with reproducibility and responsibility of research, data lifecycle models have been developed to manage the complexity. To foster open, transparent, and collaborative science, data is often archived in a repository at the end of the project according to such data lifecycle models. This is often followed by the last step of the lifecycle models, data reuse. Traditionally, this model is cyclical, with reused data leading to new questions and fueling subsequent rounds of research.
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This study explores how artificial intelligence (AI), specifically deep representation learning, can predict the scholarly impact of new scientific papers without relying on citation data. Using the SciBERT model, the research introduces two key indicators—Topicality (τ) and Originality (σ)—to estimate the potential impact of newly published papers. The approach is validated using the COVID-19 Open Research Dataset, demonstrating that papers with high topicality or originality are more likely to gain scholarly attention. The findings suggest that AI can complement traditional citation-based metrics, particularly for early-stage research, offering insights into knowledge creation dynamics and interdisciplinary research potential.
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Older adults are the fastest-growing segment of the population. In Canada, one in five people are 65 or older, and by 2065, this will increase to more than one in four. Yet, despite their growing numbers, older adults often face exclusion and marginalization in technology design. This digital divide has significant consequences, leading to isolation, loneliness, frustration, and poor health outcomes, particularly when we intersect factors like lower socioeconomic status, race, gender, and immigrant status.
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Pedagogy Patchwork, a new 14-episode video series, has just been published at the YouTube channel, INFIDEOS. It contains a collection of creative classroom strategies for educators in Library and Information Science.
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Longitudinal research in information science is rare, but an exception to that rule is a Canadian study that has surveyed academic librarians at multiple points over a 30-year period to understand their instructional goals and practices. This research program highlights the value of longitudinal and geographic comparisons.
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Communication technologies help people communicate with each other, whether through email, computer-mediated technologies such as message boards and Internet forums, and through voice, video, or conferencing systems, and the long list of new media (virtual reality, augmented reality, AI communication, podcasts, video sharing platforms, etc.). These communication technologies influence social and cultural transformations by evolving how people communicate, impacting the patterns of communication they use, and resulting in social interactions designed and carried out through a web-based environment.
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Lessons from research on the governance of misinformation in everyday life apply widely to individual and community experiences.
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While keeping pace with the new developments in generative AI and LLM reasoning models is in itself a challenge, new ‘deep research’ agents are beginning to surface at a remarkably rapid rate.
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