Do we actually need to write research papers at all?
If we are going to lean on the creativity and the cross-domain thinking of human researchers, then surely that should be where the human time goes.
Topic
FAIR data
Findable, Accessible, Interoperable, Reusable — and the gap between data that technically meets FAIR and data anyone can actually reuse.
BioSingularity. The substrate determines the ceiling
Biology becoming computationally tractable depends less on model size than on the data substrate underneath. The ceiling is infrastructure.
FAIRdata.ai: Making Open Data FAIR-er
Most repository data is technically FAIR and practically unusable. FAIRdata.ai is an experiment in closing that gap automatically.
Moving from "share data because you should" to "share data because you'll get something back."
Allen AI's AutoDiscovery generated its own hypotheses from an open dataset. That return on sharing is exactly why I founded Figshare.
Machine-First FAIR: Realigning Academic Data for the AI Research Revolution
FAIR treats humans and machines as equal priorities. It should not. Prioritising machines is the faster route to human benefit.
DataCite DOI prevalence in the published literature by country
Combining the Make Data Count Citation Corpus with Dimensions to see which countries actually link to datasets from their published papers.
The Data Citation Corpus - tracking NIH funded open academic data
Joining the Wellcome-funded Data Citation Corpus to Dimensions to track how well the NIH open data policy is actually working in practice.
Who benefits when, from FAIR data? Part 3 - The Public
Part 3: the public fund research through taxes but cannot read most of it. What open academic data owes the people paying for it.
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.
Who benefits when, from FAIR data? Part 1 – Researchers
Part 1: seven years on from the FAIR principles, what do researchers themselves actually get back from making their data reusable?