OpenResearch.wtf

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Mark Hahnel

OpenResearch WTF - February 2024

Content eLife’s New Model: One year on eLife's new publishing model, a year after its launch, has led to over 6,200 submissions, with more than 1,300 reviewed preprints published. This model emphasises speed and transparency, combining preprints with expert peer reviews and assessments to facilitate

Making poorly described data FAIR-er using GenAI

This small experiment looks at whether Generative AI tools, in this case ChatGPT 4 can improve the metadata (and thus FAIR-ness) of poorly described published datasets.

Who benefits when, from FAIR data? Part 3 - The Public

By making research findings, scholarly articles, and educational resources openly available, open academic data promotes a more inclusive and equitable dissemination of knowledge.

Who benefits when, from FAIR data? Part 2 – Machines

AI and machine learning can be used to create more detailed, FAIR-er datasets to be consumed by the machines.

All of the knowledge for all of the machines

By processing and analysing vast amounts of scholarly work, AI will enable breakthroughs in research, innovation, and problem-solving across numerous disciplines. But what can be legally accessed and what can be trusted?

Who benefits when, from FAIR data? Part 1 – Researchers

We are optimistic of a future state world, where a group of researchers generates new information based on new hypotheses, for others to then pull together the combined world’s knowledge to look for new patterns and discoveries that the original authors had not thought to look for.

Academic data publishing is the biggest ROI in research today

Data publishing is the biggest ROI in research today. It is truly an agent of change and I for one am excited that we have made it this far. Now funders have mandated data publishing writ large, I am also excited for the road ahead.

Halfway to happiness — what the OSTP update means in the grand scheme

As is the tradition in academic publishing, we can continue to stand on the shoulders of giants, specifically the decades of work done by early open access advocates and SPARC. The speed at which dissemination of research is improving itself is accelerating.

Why fast but good publishing matters

If we are to enter the world of fast and good academic publishing, we need a dataset curation model that scales.

Academic Research Data. Is it being cited?

Obviously with the many different types of outputs that researchers want credit for, there are some that lend themselves to reuse and traditional citation metrics better than others.