Two environmental researchers argue that open-access publishing has undergone major “environmental” shifts, triggering rapid and far-reaching evolutionary responses, not unlike natural ecocystems.
Open Science 2.0 must focus not only on access, but also on trust, interpretation, learning, and effective communication. The challenge facing the scholarly publishing ecosystem is ensuring that what is open is also trustworthy, understandable, and genuinely useful.
Today’s guest post presents outcomes of the WCRI’s (World Conferences on Research Integrity) Focus Track to address this gap in clarity and standardization of AI disclosure.
The future of scholarly communication will not be determined by how powerful AI becomes, but by whether the research community remains clear about the purpose those capabilities are meant to serve and whether it can govern them together.
A Cambridge workshop proposes new standard work to support provenance, attribution and metrics in scholarly communications AI tools.
Today’s post explores what happens to the scholarly content platform when AI agents become the users.
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.