OpenResearch.wtf

OpenResearch.wtf

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Latest — Aug 14, 2024

The Data Citation Corpus - tracking NIH funded open academic data

By combining this dataset with Dimensions.ai data in Google Big Query, we we're able to add more dimensions to the dataset (pardon the pun), such as funder or institution. This allows us to track how well things like the NIH open data policy is encouraging linking to datasets from papers.

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Some Gold Open Access (OA) Article Processing Charges (APC) data

Open research is essential. Open Access is essential. My question as always is whether we can be doing this in a manner that is faster and cheaper? Is this the most efficient way to publish open access research. The new data will help ignite more conversations like this. Watch this space.

OpenResearch WTF April 2024

Policy Barcelona Declaration on Open Research Information More than 40 organisations have committed to being more transparent about how they share information about their research processes and outputs. The Barcelona Declaration, released April 16, calls for open research information—or metadata—to be the norm. Signatories include funders and higher

Open Access: Mo money, mo problems

At the start of my PhD in Stem Cell Biology, I was not aware of Open Access despite Open Access journals being a thing since the late 1980s. arXiv came along in the early ‘90s, followed by PubMed Central and the first commercial OA journal, Biomed Central in the late

OpenResearch WTF - March 2024

Content The Bill & Melinda Gates Foundation’s 2025 Open Access Policy Refresh No APCs! Preprints required “We will work to support an Open Access system and infrastructure that ensures articles and data are readily available to a wider range of audiences” Huge Figshare, Digital Science and Springer Nature Publish

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?