Guest Post – The Next Era of Reference Management: An Interview with William Gunn
Today’s guest post features an interview with William Gunn discussing how AI will (or won’t!) change the future of reference management tools.
Today’s guest post features an interview with William Gunn discussing how AI will (or won’t!) change the future of reference management tools.
Today’s guest blogger observes how advances in technology create unprecedented opportunities in open scholarship, and asks: Can incentive structures keep up?
Todd Carpenter looks back on the past quarter century of a digital revolution in scholarly publishing.
At the STM innovation and Integrity days in London last week, it’s clear that research integrity has become an increasingly pressing issue. Many publishers are reporting significant increases in submissions of questionable legitimacy. perhaps now is the time for a new alliance between publishers, funders, institutions and researchers to protect the integrity of the scholarly record, before it’s too late.
Today’s guest post spotlights a new scientific intelligence engine inspired by Thomas Kuhn’s theory of scientific revolution and the mission to give humanity the ability to see its own progress while it unfolds.
Today’s guest post argues that academic libraries are an investment in the very foundation of quality scholarship and responsible publishing.
A review of 12 major publishers finds that they display an average of 6 journal-level impact metrics on their platforms. The Journal Impact Factor is the only metric displayed on all 12.
In the fast-moving world of AI research tools, there are many community-focused concerns that vendors should have strong opinions on and plans for, from privacy and security to sustainability and copyright. But the most misunderstood issue, in my view, is the one at the heart of it all — how AI will reshape the economics of academic research.
Today’s guest bloggers share analysis on the relationship between impact and policy during Global Goals Week 2025.
Today’s post discusses research metrics and their relationship to research integrity, inclusivity, and long-term impact.
If LLMs are the future of information discovery, valuable scholarly content risks being left behind — unless we build a bridge with better licensing.
The French Open Science Monitor Initiative shows a path toward improving recognition of data sharing and open science assessment.
It is time for OA proponents to engage in public debate with academic associations, universities and national funding agencies, because the widespread use of academic content in AI models poses significant risks for the research ecosystem.
I tried three different large language models (LLMs) to rewrite a potential article.
Publishers should support scholarly authors by requiring license deals with AI developers include attribution in their outputs.