What’s Hot and Cooking In Scholarly Publishing
We asked some of the attendees of the recent SSP Annual Meeting in Chula Vista, CA, to answer the question: “What are some takeaways from your experience at SSP 2026?”
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?
The Chefs offer their reflections on last week’s SSP Annual Meeting.
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.
New guidance from the US government on research funding makes publishing and journal subscription costs unallowable.
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.
With CC Signals, Creative Commons wants to help authors put rules on use of their licensed content for AI training. The problem is, one of the licenses already permits free and unlimited reuse of that content, for any and all purposes. And the licenses are irrevocable.
We are out of office for the US holiday. In the meantime, maybe peruse a phenomenal new live music archive….
Today, we feature a friendly debate on the question: which parts of the research lifecycle should be more automated, and which require more of a human touch — and why?