Funding COVID-19 research: Insights from an exploratory analysis using open data infrastructures is a dataset published in Quantitative Science Studies (2022). On theSindex it has a DataRank of 0.722, placing it in the top 45.1% of the data-sharing corpus. It has been cited 15 times, with 13 citing works in its 1-hop citation network. Its calibrated FAIR score is 23/100.
Abstract To analyze the outcomes of the funding they provide, it is essential for funding agencies to be able to trace the publications resulting from their funding. We study the open availability of funding data in Crossref, focusing on funding data for publications that report research related to COVID-19. We also present a comparison with the funding data available in two proprietary bibliometric databases: Scopus and Web of Science. Our analysis reveals limited coverage of funding data in Crossref. It also shows problems related to the quality of funding data, especially in Scopus. We offer recommendations for improving the open availability of funding data in Crossref.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
Base Score Contribution
0.416
From this paper's citation signal
Citation Network Contribution
0.307
From 9 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 58% comes from its base citations and 42% from the citation network (9 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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