Guest Post — Scholarly AI Search Shortcomings and the Need for Better Metadata
AI scholarly search tools often miss important literature due to incomplete metadata. Better full-text-derived metadata could significantly improve discovery.
AI scholarly search tools often miss important literature due to incomplete metadata. Better full-text-derived metadata could significantly improve discovery.
Today’s post shares the results of an initiative designed to answer the question: what would it actually take to build a publishing model fit for the research ecosystem we have now, rather than the one we inherited?
In honor of Global Accessibility Awareness Day, today’s post shares results from an experiment with qualitative data analysis — demonstrating that, while AI can detect patterns, humans must decide what those patterns mean.
Today’s guest post proposes a method for identifying, measuring, and managing robotic usage of scholarly content.
Today’s guest post sounds an alarm about the use of AI in research and warns that no amount of computational efficiency can compensate for the loss of our capacity for human thought.
Today’s post calls for collective action to address the researcher identity verification gap in scholarly communications and champions STM’s Researcher identity group.
Today’s guest post explains the new data space pilot, which will be the focus of the upcoming BISG/SSP webinar on May 12, 2026.
In this post, Robert attempts to embrace a gloomy optimism as he muses on the state of publishing at scholarly societies.
Today’s guest post demonstrates how publishers can reduce their carbon footprint and be leaders in environmental sustainability.
Today’s guest bloggers explain how semantic enrichment of scholarly content allows publishers to shape the next generation of technology by making it indispensable to AI.
Today’s guest blogger proposes the “Continuum of Consensus” as a solution to shore up research integrity, peer review, and the public trust in scholarly research.
A review of eight technology industry trend reports that offer a similar conclusion: AI is no longer a feature. It’s becoming infrastructure — and the unit of value is moving from “a better tool” to “a better system.”
Today’s guest bloggers spotlight a gap in traditional usage reporting, third-party AI usage, and recommend steps needed to recover missing usage data.
How are two competing neuroscience journals faring since the editorial board of one departed to create the other?
Today’s guest post features an interview with William Gunn discussing how AI will (or won’t!) change the future of reference management tools.