Share of Science reads the scientific literature to show which labs adopt which instruments, at which institutes, and which grants pay for them. Revenue is a lagging indicator. Science leads it.
Every methods section names the instruments it used. We read them all, against a curated catalogue of products and aliases — not a keyword search.
Grants say who paid and for what. DFG's FUGG programme funds instruments outright, which turns an award record into a purchase signal.
A lab publishes on a platform years before the purchase appears in a vendor's revenue. That gap is the product.
“You measure share-of-revenue. We measure share-of-science. Revenue is a lagging indicator; publications are leading.”
Europe PMC full text is parsed for methods sections. Platform names are matched against a curated catalogue (123 products, 366 aliases), quote-anchored, and labelled by deterministic rules — no model decides whether a lab used an instrument. This edition keeps only the verified tier and hand-checks every row shown. Institutions are as printed; ROR resolution and lab-level identity are the next build.
Sources: Europe PMC full text · CORDIS · GEPRIS. Public literature and public award records only. No personal data.
Mahdi Moradi is the founder of Share of Science. The pipeline reads methods sections from open-access papers, matches instrument names against a curated catalogue, and joins the result to public grant records — so a vendor can see adoption before it reaches revenue.
I started this because the adoption question I kept asking — who is actually running what, where — had no dataset behind it. The literature does. It was just never machine-read against a product catalogue and a grant registry.
Corrections are welcome and published. If a row is wrong, send the paper and it will be fixed in the next edition.
LinkedIn: linkedin.com/in/mamoradii