The exponential surge in research data, coupled with the advent of cutting-edge computational tools, is ushering in an era of unprecedented opportunities for research performing organisations. However, with many still in the process of adopting basic research data management practices and support mechanisms, the current state of play is concerning.

I help Canadian neuroscience research institutes create and adopt an institute-level approach to open science. Inevitably, I end up talking to researchers, administrators, academic commercialization offices, and businesses about open science, intellectual property (IP), and technology transfer.

Although advances in artificial intelligence (AI) ¹ have been unfolding for over decades, the progress in the last six months has come faster than anyone expected. The public release of ChatGPT in November 2022, in particular, has opened up new possibilities and heightened awareness of AI's potential role in various aspects of our work and life.

In November of 2022, the Research Software Alliance (ReSA) and the Netherlands eScience Center organized a two-day international workshop titled “The Future of Research Software.” In the workshop, funding organizations joined forces to explore how they could effectively contribute to making research software sustainable. The workshop had many participants from all continents and was a huge success.

Infrastructure: what’s at stake Infrastructure often is perceived as a “given”, as something that was always there, as “natural”. In the digital age, infrastructure seems more “natural” than ever (it's hard to imagine there was a time without internet connectivity in our mobile phones or even a time when phone lines were a luxury item) and the social and economic dimension of infrastructure tend to be invisibilized and are left out of

Since its release towards the end of 2022, ChatGPT has been dominating the majority of AI-related conversations on social media. One could almost say it has made AI more mainstream and accessible than ever. AI is quickly revolutionizing the modern-day research landscape. According to a CSIRO report, nearly 98% of scientific fields use AI in some way.

Since 2015 I’ve been steeped in the world of open access, academic publishing, and funder policies. This is a blip of time compared to many other experts and advocates in this space. I’ve often sardonically joked that if I had received a dollar for every time I’ve heard that open access will become the norm once the United States changes its policy I could retire early.

Take a look at the picture below. What do you see? Think for a moment and write down your observations or say them out loud. Did you see tracks in the snow and the shadow of trees in the background? Maybe you were more specific, noting there are different kinds of tracks going in different directions, and at least two trees casting shadows.

In the Open Scientist Handbook, I argue that open science supports anti-rivalrous science collaborations where most metrics are of little, or of negative value. I would like to share some of these arguments here.

Scholarly publishing at times seems to want to hold on to some outdated processes. At the top of my list is the dreaded RFP (Request for Proposals) process. In the scholarly comms world, consultants send these out on behalf of publishers that are seeking solutions or services. My career involves designing and building publishing technology and so I have been on the receiving end of many RFPs for developing new platforms.