# Linking Global Science Funding to Research Publications

arXiv: https://arxiv.org/abs/2603.24147 · HTML: https://mlsanity.com/paper/2603.24147/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Mar 2026.

## Built on by (most cited first, 1 of 1)

- [Multi-Functional Embedding Models for Funder Name Disambiguation in Scientific Publication Records](https://mlsanity.com/paper/2609.09984/) (2026)

## Abstract (arXiv)

Funding acknowledgments in scholarly publications provide large-scale trace data on organizations that support scientific research. We present a dataset for linking global science funding organizations to research publications by systematically disambiguating unique funding acknowledgment strings extracted from publication metadata. Funder names are matched to standardized organizational identifiers using a multi-stage pipeline that combines lexical normalization, similarity-based clustering, rule-based matching, named entity recognition assistance, and manual validation. The resulting dataset links 1.9 million unique funder strings to canonical organization identifiers and records match types and unresolved cases to support transparency. Technical validation includes paper-level comparisons across bibliometric sources and manual verification against full-text acknowledgment sections, with reported recall and precision metrics. This dataset supports analyses of funding flows, institutional funding portfolios, regional representation, and concentration patterns in the global research system.