Building robust citation and attribution into generative AI systems are foundational to usage, credit and trust. We need to expect more from AI.
Today, guest blogger Rob Johnson speaks with the creator of Research Nexus Score, and observes that metadata quality has gone from a niche concern to a sector-wide anxiety.
A conversation on AI retrieval, the provenance problem, and the shared infrastructure scholarly publishing needs.
Today’s guest post asserts that AI infrastructure will let publishers truly leverage machines, while brand and community are what will keep them meaningful to humans.
Federated identity should be a natural fit for library access. So why isn’t it?
China’s publishing ambitions create genuine competitive pressures, but they also open opportunities for collaboration and highlight challenges that neither side can address alone
China is no longer simply a major contributor to global research output; it is increasingly becoming a key force shaping the future of scholarly publishing. Understanding what is actually happening, and why, is the necessary first step before considering how publishers should respond.
A powerful way to quantify article quality has been hiding in plain sight. It’s time to bring data citations into the limelight.
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?
For scholarly publishers, the user has changed faster than the systems designed to serve them, and the gap between the two is where most of the difficult work is happening.
Today’s guest post proposes a method for identifying, measuring, and managing robotic usage of scholarly content.
The new STM Trends 2030 was released, symbolizing a world full of opportunities but also with dangers lying just below the surface for scholarly publishing.
AI in science should not be viewed merely as a productivity tool layered onto existing workflows. It represents a structural shift in how knowledge moves through society, and therefore in how scientific authority is established and maintained.
Today’s post calls for collective action to address the researcher identity verification gap in scholarly communications and champions STM’s Researcher identity group.