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Estimating transformative agreement impact on hybrid open access: A comparative large-scale study using Scopus, Web of Science and open metadata

T0 review · 2 major / 5 minor · reviewed 2026-08-16 · deepseek-v4-flash

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Pith's one-line read Open metadata matches Scopus and Web of Science on transformative agreements, a 13,000-journal comparison finds.

desk verdict A transparent large-scale three-way comparison that validates open metadata for monitoring transformative agreements; the WoS Elsevier misclassification is a real but non-fatal caveat. read the letter →

arxiv 2504.15038 v2 pith:GAGPQOMB submitted 2025-04-21 cs.DL

Najko Jahn This is my paper · ORCID
classification cs.DL
keywords hybridopenaccesstransformativeagreementsmetadatabibliometricdatasourceshoaddataCrossrefAlexcurativebibliometrics
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper asks whether openly available metadata can replace or complement the proprietary databases Scopus and Web of Science when measuring how much open access in hybrid journals is enabled by transformative agreements. Hybrid journals are subscription journals that let individual articles be made open access, and transformative agreements are licensing deals meant to flip them to full open access. It applies the same journal- and institution-matching method to all three sources — hoaddata, an open dataset built from Crossref, OpenAlex, and the cOAlition S Journal Checker Tool, alongside Scopus and Web of Science — covering more than 13,000 hybrid journals from 2019 to 2023. The central finding is that the sources agree: by 2023, transformative agreements enabled the majority of hybrid open access, and country-level ranks correlate above 0.9 across data sources and author roles. The paper concludes that open metadata alone already supports reliable large-scale monitoring of the open access transition, while using multiple data sources together is safer than relying on any single one.

What carries the argument

The load-bearing mechanism is a DOI-based matching pipeline that connects the cOAlition S Journal Checker Tool's ROR (Research Organization Registry) institution and journal-agreement records to each database's own affiliation identifiers: OpenAlex ROR IDs for hoaddata, Scopus Affiliation IDs, and Web of Science enhanced organization names. A two-step algorithm pairs millions of articles by DOI, selects the most frequent ROR-to-proprietary-identifier match, then attributes an article to a transformative agreement only when the agreement was active in that year according to the ESAC registry. This pipeline is what lets the same estimation logic run inside all three data sources. The paper's quality check on fifty random pairs found a 6% mismatch rate for Scopus and a 22% mismatch rate for Web of Science, concentrated among institutions with few publications.

What would settle it

Recompute the country-level Spearman correlations after removing all institutions involved in mismatched affiliation pairs or with fewer than about ten articles; if the correlations drop materially below 0.9, the equivalence claim fails. A stronger test would compare open-metadata estimates with actual invoicing data from several national consortia: if the per-country error is no smaller than the cross-source differences, the open metadata are not in fact reproducing the proprietary databases.

Watch

Extended reading notes

Core claim

The discovery is that agreement-enabled hybrid open access can be estimated consistently from open metadata and from proprietary databases, and that by 2023 such agreements had become the dominant route to open access in hybrid journals. Depending on the source, 61% (hoaddata), 64-65% (Scopus), or 68-69% (Web of Science) of hybrid open access articles in 2023 were attributed to transformative agreements; in absolute terms, hoaddata linked 501,649 articles to agreements over 2019-2023. Agreement between sources is strongest at the country level, where Spearman rank correlations exceed 0.9 for article volume, open access share, agreement-enabled output, and agreement share, and remain above 0.85 when small countries are included. First-author and corresponding-author attributions give nearly the same national picture, which matters because open metadata often lack corresponding-author fields. The discrepancies that do appear, such as Web of Science counting Elsevier's delayed open access as hybrid or Unpaywall missing Wiley articles, are used to argue that multi-source verification is the safer path.

Load-bearing premise

The estimates stand on the assumption that the DOI-based mapping from ROR institutions to Scopus and Web of Science affiliation identifiers is accurate enough that errors mostly cancel out at the country level, despite a 22% mismatch rate found for Web of Science in a fifty-pair quality check.

Editorial extensions

If this is right

  • Country-level monitoring of transformative agreements can be done with open metadata alone, without buying Scopus or Web of Science access.
  • First-author affiliation is an adequate proxy for corresponding-author affiliation in national-level agreement uptake statistics.
  • Any single database, open or proprietary, mislabels some hybrid open access; Web of Science's treatment of Elsevier delayed open access and Unpaywall's Wiley parsing failures show that triangulation changes conclusions.
  • Journals missing from selective databases, especially newly launched hybrid titles, are visible in Crossref-based open metadata, so relying exclusively on Scopus or Web of Science undercounts the agreement landscape.
  • Agreements accounted for 61-69% of hybrid open access by 2023, meaning the remaining open access is paid for outside agreements, and most hybrid articles are still paywalled.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the matching errors are concentrated in small institutions, institutional-level league tables built from Web of Science without ROR support are likely to be noisier than country-level tables; the paper's quality check points in that direction but does not demonstrate it.
  • The same pipeline could be pointed at funder-level or discipline-level subsets, where a testable prediction is that agreement shares will vary more across disciplines than across data sources.
  • As more publishers begin depositing CC-license metadata in Crossref, the open-metadata share of detected hybrid open access should rise, so the 61% figure is probably a lower bound for current hoaddata coverage rather than an upper bound.
  • The high first-versus-corresponding correlation may not survive in fields with large international author teams, so first-author proxies should be checked within disciplines before use at finer granularity.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 5 minor

Summary. The paper compares hoaddata, an open metadata pipeline built from Crossref, OpenAlex, and the cOAlition S Journal Checker Tool, with Scopus and Web of Science to estimate the impact of transformative agreements on hybrid open access publishing between 2019 and 2023. For more than 13,000 hybrid journals, the author computes open access uptake and the share of open access articles attributable to transformative agreements, using first- and corresponding-author attributions where available. The central claims are that the three data sources agree strongly at country level (Spearman rho > 0.9 for most comparisons) and that by 2023 transformative agreements enabled the majority of hybrid open access, with agreement-attributed shares of 61% (hoaddata), 64-65% (Scopus), and 68-69% (Web of Science). The paper also documents coverage differences, including journals missing from one or more sources and discrepancies in open access labelling, particularly for Elsevier open-archive articles in Web of Science and Wiley redirect issues in Unpaywall.

Significance. If the results hold, this is a valuable contribution to bibliometric methodology and open access monitoring. The study uses a transparent, reproducible pipeline with public code, data, and a test suite, and it validates an open dataset against independent proprietary databases rather than against itself, which makes the comparison informative. The detailed coverage diagnostics and the explicit acknowledgement of known labelling discrepancies are notable strengths. The finding that open metadata can produce country-level estimates consistent with Scopus and Web of Science is practically important for consortia and funders that cannot afford proprietary data. However, the reliability of the headline range depends on resolving the Web of Science open-archive issue and on the robustness of the institutional identifier mapping, so the contribution needs revision before it can be fully endorsed.

major comments (2)
  1. [Section 3.2, Figure 5] The Web of Science upper-bound estimates of 68% (first author) and 69% (corresponding author) include Elsevier 'open archive' articles that are labelled as hybrid open access in Web of Science even though they are not published under a CC licence, as the paper itself documents in the discussion of Figure 5 and the surrounding text. The manuscript reports this discrepancy qualitatively but does not quantify its effect on the agreement-attributed share. Because the 68-69% figures are used as the upper endpoint of the flagship claim that transformative agreements enabled the majority of hybrid open access by 2023, the paper should either correct the Web of Science estimates by excluding Elsevier open-archive articles, or report the Web of Science values with and without those articles and adjust the conclusion accordingly. As it stands, the headline range mixes a quantity measured under the paper's CC-licence definition (hoaddata, Scopus) with a quantity that includes a known source misclassification (Web of Science).
  2. [Section 2.2, harmonising author affiliations] The quality check for the ROR-to-proprietary identifier mapping is based on a random sample of 50 pairs, with 22% mismatches for Web of Science and 6% for Scopus. The paper acknowledges that mismatches mainly involve less-represented institutions, but the mapping is used to attribute every agreement-enabled article, so a 22% mismatch rate in the Web of Science mapping could materially affect the country-level and global estimates. The high country-level correlations (rho > 0.9) could be partly an artifact of aggregation if errors average out across institutions within countries. To support the claim that results are consistent across data sources, the paper should provide a confidence interval for the mismatch rate, stratify the mismatches by institution size or country, and report a sensitivity analysis, for example by recomputing the main indicators after excluding low-confidence institutional matches.
minor comments (5)
  1. [Section 2.1] The word 'affilation' should be 'affiliation' in the description of hoaddata, and the Introduction contains 'open accesss' instead of 'open access'.
  2. [Section 3.2] The sentence 'Since 2021 (hoadata, Scopus) resp. 2022 (Web of Science), transformative agreements have enabled the majority...' should be rephrased as formal prose rather than abbreviated notation, and 'hoadata' should be 'hoaddata' for consistency.
  3. [Section 2.2] The sentence beginning 'Because neither Web of Science nor Scopus supported ROR-ID at the time of data retrieval, the institution identifier used by the JCT, a two-step matching process...' is a sentence fragment and should be rewritten.
  4. [Section 3.1] In the Figure 2 caption, 'The x-axis represents the set intersections in a matrix layout' is imprecise; the x-axis of an UpSet plot represents the intersection membership matrix, not the intersections themselves.
  5. [Section 2.3, Table 1] The table note should state more explicitly that hoaddata counts are based on DOI-bearing articles, while Scopus and Web of Science counts use database identifiers; this distinction is described in the text but the table could be misread without it.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the paper validates an author-created open metadata dataset against external proprietary databases, and its self-citations are methodological precedents rather than load-bearing derivations.

full rationale

The paper's central claim is a comparative, empirical consistency result: hoaddata estimates of hybrid open access enabled by transformative agreements are compared with independently sourced Scopus and Web of Science records. The open dataset is fully reproducible (code, data, tests, CI/CD workflow), and the proprietary databases contribute independent article coverage, open access status via Unpaywall, author roles, and country-level affiliation data. The closest potential circularity is the ROR-to-proprietary-affiliation matching step (Section 2.2), where WoS and Scopus agreement-eligibility is inferred through a mapping learned from hoaddata's ROR-tagged articles. However, this is an identifier crosswalk, not a fitted prediction of the outcome: the WoS/Scopus agreement counts still depend on their own article sets, open access flags, author role fields, and country assignments, and the paper openly reports a 22% WoS and 6% Scopus mismatch rate in the mapping quality check. The method is adopted from the author's prior work (Jahn, 2025), but that prior work is code-reproducible, and the specific matching approach is also supported by an external validation study (de Jonge et al., 2025) using Dutch NWO invoicing data. The paper's own discussion explicitly acknowledges the lack of invoice data, the approximate nature of institution-level attribution, and the possibility that institutional-level correlations may differ from country-level ones (Section 4). These are stated limitations rather than hidden reductions. No equation in the paper reduces the reported agreement shares to the inputs by construction, and the consistency claim is not a renaming of a known result. The Elsevier/WoS open-archive discrepancy flagged in Section 3.2 is a data-quality and definitional concern about the WoS upper-bound estimate, not a circularity in the derivation chain. Overall, the comparison against external benchmarks breaks the validation loop, so no significant circularity is present.

Assumptions & free parameters 0 free parameters · 4 assumptions · 0 invented entities

The central claims rest on four domain assumptions: the correctness of the JCT/ESAC agreement and hybrid journal lists, the fidelity of the ROR-to-proprietary-ID mapping, the reliability of OA detection via Crossref licenses and Unpaywall, and the interchangeability of first and corresponding author for country-level attribution. None are invented entities or fitted parameters; they are standard bibliometric measurement assumptions, with the ROR mapping being the most fragile due to the reported 22% WoS mismatch rate.

assumptions (4)
  • domain assumption The JCT/ESAC transformative agreement data and the DOAJ-based exclusion correctly identify hybrid journals covered by agreements.
    The entire journal universe is defined by this curated list; errors in the list would propagate to all coverage and uptake estimates. Location: Section 2.2.
  • domain assumption The DOI-matching algorithm that maps ROR IDs to Scopus Affiliation IDs and WoS enhanced organization names preserves agreement eligibility.
    The paper reports 22% and 6% mismatch rates on 50 random pairs; if these rates generalize, institutional-level attribution is noisy, though country-level aggregates remain stable. Location: Section 2.2.
  • domain assumption Crossref license metadata and Unpaywall correctly identify hybrid open access status, and Web of Science's tagging of Elsevier delayed OA is treated as an error.
    OA classification differences are the main source of cross-source discrepancy; the paper documents but cannot fully correct them. Location: Sections 3.1 and 3.2.
  • domain assumption First-authorship can stand in for corresponding-authorship when measuring agreement uptake, given high observed correlation.
    hoaddata lacks corresponding author data; the paper relies on the first/corresponding correlation to claim consistency. Location: Sections 2.3 and 4.

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Pith. "Pith review of Estimating transformative agreement impact on hybrid open access: A comparative large-scale study using Scopus, Web of Science and open metadata." pith.science (2026). https://pith.science/paper/GAGPQOMB

@misc{pith2026250415038,
  author       = {Pith},
  title        = {Pith review of: Estimating transformative agreement impact on hybrid open access: A comparative large-scale study using Scopus, Web of Science and open metadata},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/GAGPQOMB}},
  note         = {Machine review of arXiv:2504.15038}
}
read the original abstract

This study compares open metadata from hoaddata, an openly available dataset based on Crossref, OpenAlex and the cOAlition S Journal Checker Tool, with proprietary bibliometric databases Scopus and Web of Science to estimate the impact of transformative agreements on hybrid open access publishing. Analysing over 13,000 hybrid journals between 2019-2023, the research found substantial growth in open access due to these agreements, although most articles remain paywalled. The results were consistent across all three data sources, showing strong correlations in country-level metrics despite differences in journal coverage and metadata availability. By 2023, transformative agreements enabled the majority of open access in hybrid journals, with particularly high adoption in European countries. The analysis revealed strong alignment between first and corresponding authorship when measuring agreement uptake by publisher and country. This comparative approach supports the use of open metadata for large-scale hybrid open access studies, while using multiple data sources together provides a more robust understanding of hybrid open access adoption than any single database can offer, overcoming individual limitations in coverage and metadata quality.

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Pith tools

Reviewed August 16, 2026 · model on record in the stance chip above.