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REVIEW 3 major objections 4 minor 37 references

Analysing the coverage of the University of Bologna's bibliographic and citation metadata in OpenCitations collections

T0 review · 3 major / 4 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read The paper shows that OpenCitations holds a comparable share of the University of Bologna's publications and citations as Scopus and Web of Science, despite matching only 36% of the full IRIS record set by persistent identifier.

desk verdict A transparent, reproducible coverage audit of a large Italian CRIS against OpenCitations, with a headline 36% that is really a lower bound because a third of IRIS records were never searched. read the letter →

arxiv 2501.05821 v2 pith:XPZOIFIE submitted 2025-01-10 cs.DL

Erica Andreose , Salvatore Di Marzo , Ivan Heibi , Silvio Peroni , Leonardo Zilli This is my paper · ORCID
classification cs.DL
keywords BibliographicmetadataCitationdataCRISsystemsIRISOpenCitationsresearchinformationCoverageanalysisBarcelonaDeclaration
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 an open scholarly infrastructure can stand in for the closed commercial databases that universities currently rely on for research assessment. Taking the University of Bologna's IRIS system as a test case, it measures how many of the university's 402,505 bibliographic records appear in OpenCitations and how many citations those records receive. The headline result is that 36% of all IRIS records, or 145,143, are found in OpenCitations Meta, with journal articles covered at 91.6%; the same matched records receive 5,129,406 citations in the OpenCitations Index. When compared by citation count, OpenCitations performs on par with Scopus and Web of Science, with roughly 35 citations per matched record in all three systems. If this holds, institutions have a concrete quantitative basis for moving research-information workflows toward open data.

What carries the argument

The load-bearing object is a five-stage identifier-matching pipeline. The Trimmer extracts IRIS records carrying a DOI, PMID, or ISBN; the Validator normalizes and discards malformed identifiers; the Deduplicator collapses 86,306 duplicate identifier assignments using a type-priority table that prefers journal articles over books, book chapters, and proceedings articles; the Comparator aligns the remaining 204,999 unique identifiers against OpenCitations Meta with a publication-year cutoff, producing the Iris in Meta and Iris Not in Meta datasets; and the Citation Scanner and Citation Counter extract all OpenCitations Index citations involving the matched OMIDs and compare per-record averages to Scopus and Web of Science counts. The OMID and OCI identifiers are the connective tissue: each IRIS record is matched to one OMID through its persistent identifier, and that OMID is then used to pull every citation from a 2.2-billion-citation index.

What would settle it

Take a random sample of the 138,926 records in Iris No ID, search OpenCitations Meta by title and author, and recompute the coverage fraction; if more than a small fraction of that sample is found, the reported 36% understates OpenCitations' actual coverage. Separately, requesting Scopus and Web of Science citation counts for exactly the 145,143 records matched in OpenCitations would show whether the three systems' per-record averages still align when computed on an identical record set.

Watch

Extended reading notes

Core claim

The central claim is that, in the local context of the University of Bologna, open citation data are quantitatively equivalent to proprietary data for describing institutional research output. The authors arrive at this through a set of measurements: 145,143 of 402,505 IRIS records match OpenCitations Meta, which is 70.8% of the 204,999 deduplicated identifier-carrying records; 5,129,406 citations in the OpenCitations Index point to IRIS records; and the average number of citations per matched record is 35.34 for OpenCitations, 36.05 for Scopus, and 34.71 for Web of Science. The paper interprets the similarity of these averages as evidence that the open infrastructure can replace closed systems for quantitative purposes, at least within a single institutional context.

Load-bearing premise

The entire coverage rate depends on matching IRIS records to OpenCitations using only one of three identifiers (DOI, PMID, or ISBN), and the 138,926 records that have none of these are counted as uncovered without ever being looked up in OpenCitations, so the reported 36% figure is really a lower bound.

Editorial extensions

If this is right

  • For the University of Bologna, OpenCitations already provides article-level coverage sufficient for many assessment workflows, since 91.6% of journal articles in IRIS are matched.
  • The published CC0 IRIS dump and the open pipeline give other institutions a reusable template for measuring their own coverage in open infrastructures.
  • The main barrier to higher coverage is the 34.5% of IRIS records that carry none of the three matched identifiers; the paper's Crossref experiment shows at least 10,387 of these could be recovered through metadata-based reconciliation.
  • Citation counts extracted from OpenCitations can be used to benchmark against Scopus and Web of Science in annual reporting, with known comparability of the per-record averages.
  • The new OpenCitations ingestion workflow could, in principle, absorb IRIS-compliant data directly, turning the current one-way matching into a mechanism for closing the coverage gap.

Reading between the lines

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

  • The 36% figure is best read as a lower bound: records without DOI, PMID, or ISBN are never searched in OpenCitations Meta, so the true fraction of Bologna output present in OpenCitations is likely higher than reported.
  • The comparability claim rests on per-record averages computed over different sets of matched records in each system; a stricter test would compare citation counts for exactly the records present in all three systems, but the proprietary data needed for that test is not disclosed.
  • If the same pipeline were run at other Italian universities using IRIS, the result would show whether Bologna's quantitative parity is a general property of OpenCitations or specific to this institution's publication mix.
  • A useful next experiment is to measure the overlap of the actual citing entities, not just citation counts; the paper notes that this is impossible with the aggregated data available from Scopus and Web of Science.
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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

3 major / 4 minor

Summary. The paper describes a methodology to measure the coverage of the University of Bologna's IRIS bibliographic records in OpenCitations Meta and the number of citations involving them in OpenCitations Index. Using dumps from May–July 2025, the workflow filters IRIS records to those with DOIs, PMIDs, or ISBNs, selects one PID per record (DOI > PMID > ISBN), deduplicates, and matches against OC Meta. The authors report that 145,143 of 402,505 IRIS records (36%) are present in OC Meta, that journal articles have the highest coverage (91.6%), and that 5,129,406 citations in OC Index point to IRIS records, with an average of 35.34 citations per record, similar to Scopus (36.05) and Web of Science (34.71). All datasets and code are publicly available.

Significance. If the results were taken at face value, the paper would provide a reproducible, open methodology for institutional coverage analysis and evidence that open citation infrastructure can offer quantitative coverage comparable to proprietary databases. The paper is transparent about data provenance, publishes all intermediate datasets and code, and discloses the OpenCitations affiliation of two authors. The central coverage estimate, however, is an identifier-based lower bound rather than a precise rate; the companion study cited in the paper shows that at least 10,387 additional IRIS records without DOIs/PMIDs/ISBNs can be matched to OC Meta, so the true coverage is higher than 36%. This does not invalidate the methodological contribution, but it means the headline finding and the comparison to Scopus/WoS are not yet established at the claimed precision.

major comments (3)
  1. [Results / Bibliographic Records types; Abstract] The headline 'only 36% of IRIS is covered' is presented as a precise rate, but it is a lower bound. By construction of the Trimmer step, 138,926 IRIS records without DOI, PMID, or ISBN (34.5% of the dump) are never queried against OC Meta, and the paper's own companion study (Andreose & Zilli, 2025) reports that 10,387 of those records can be matched to OC Meta via Crossref-derived DOIs. Adding these alone raises the coverage to at least (145,143 + 10,387) / 402,505 = 38.6%, and the true figure may be higher still. The abstract, RQ1 answer, and Discussion should either quantify this as an identifier-based lower bound or incorporate the reconciliation results. This is load-bearing for the paper's central claim.
  2. [Validator; Bibliographic Records not included in OpenCitations Meta] The Validator selects exactly one PID per record (DOI > PMID > ISBN). A record with a DOI that is absent from OC Meta but with an ISBN or PMID that is present is counted as unmatched, even though a valid match exists. The paper does not report how many of the 59,856 unmatched deduplicated PIDs have alternative identifiers, so the magnitude of this second undercount is unknown. Please add a quantification (for example, by querying OC Meta with all PIDs per record or by reporting the number of records with multiple PID types and the match rates by fallback identifier). Without this, the 36% figure cannot be interpreted as an accurate coverage estimate.
  3. [Discussion, second paragraph] The explanation that 'OC Meta only includes bibliographic resources that take part in citations... resulting in a missing value for the present study' applies to PID-bearing records that are absent from OC Meta, but it does not address the 138,926 no-PID records that were never looked up. The paper should distinguish between 'coverage by PID-based lookup' and 'coverage by any available metadata (title/author/other identifiers).' Since RQ1 asks about 'the current coverage of the publications... in OpenCitations', the operational definition of coverage should be stated explicitly, and the reported rate should be qualified accordingly.
minor comments (4)
  1. [Methodology] The methodology text says the workflow comprises five steps, but Figure 3 and the following description list six (Trimmer, Validator, Deduplicator, Comparator, Citation Scanner, Citation Counter). Please align the count.
  2. [Table 13] Table 13's heading contains the typo 'Iris in Idex' — it should be 'Iris in Index'.
  3. [Validator] The Validator states that 'the first is picked' when multiple identifiers exist; the order in which identifiers appear in the IRIS CSV is not documented, so this selection is not fully reproducible. Specify that the priority scheme is applied to an explicit ordered list.
  4. [Data Availability Statement] The data availability statement for Scopus and Web of Science notes that raw data cannot be published; the paper still reports exact citation counts and averages. A brief statement on the provenance of the Scopus/WoS snapshots (query date, API version) would improve transparency.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: all headline quantities are direct counts over external dumps and external proprietary API results, with no fitted parameters and no claim defined in terms of its own conclusion.

full rationale

The paper's central quantities are (i) the number of IRIS records matched in OC Meta by persistent identifier, (ii) the number of OC Index citations involving those matched OMIDs, and (iii) per-record citation averages compared with Scopus and Web of Science using external proprietary API data provided by the university's APPC unit. None of these is fitted, and none is defined in terms of the comparability conclusion. The 36% coverage figure is computed as 145,143/402,505 after the Trimmer/Validator/Deduplicator/Comparator pipeline; the paper explicitly reports the 138,926 records that lack DOI/ISBN/PMID and discusses a companion reconciliation study, so the lower-bound nature of the headline is disclosed rather than hidden. The choice to search OC Meta using one prioritized PID per record (DOI over PMID over ISBN) is an operational decision that could undercount coverage, but it is not circular: coverage is operationalized in the methodology, not assumed in the conclusion. Self-citations (Peroni & Shotton 2020; Heibi et al. 2024; Massari et al. 2024; Heibi & Peroni 2022) describe the OpenCitations data sources and prior applications; they are not used to justify the empirical claim, and the relevant data dumps and code are openly available for independent verification. The conflict of interest (two authors are Director and CTO of OpenCitations) is disclosed and does not make the measurements circular. Overall the derivation chain is self-contained against external data sources; no circular step can be exhibited by construction.

Assumptions & free parameters 2 free parameters · 3 assumptions · 0 invented entities

The paper is a measurement study, so the ledger is short. Two hand-set parameters shape the matched set: the PID priority order (DOI then PMID then ISBN) and the deduplication type-priority tables that resolve the 86,306 records sharing a PID. Three domain assumptions are load-bearing: OC Meta contains every cited work (so uncited works cannot be found), the May 2025 IRIS dump is a complete inventory of University of Bologna output, and one normalized PID per record decides presence or absence. No fitted model and no invented entities.

free parameters (2)
  • Deduplication type-priority tables (DOI, PMID, ISBN) = DOI: journal article 0, book 1, book chapter 2, proceedings article 3; PMID: journal article only; ISBN: edited volume…
    Priority rankings in Tables 6-8 were 'devised following the manual investigation of sample duplicate records' (Deduplicator section). They determine which BR survives when 86,306 records share a PID (28,803 PIDs), and therefore set the 204,999-PID list that all coverage and citation numbers are computed from.
  • PID selection heuristic (DOI > PMID > ISBN) = DOI first, PMID fallback, ISBN last
    Validator step: for records with multiple PID types, the first in this order is used for matching in OC Meta. No analysis of how the choice affects the 145,143 match count.
assumptions (3)
  • domain assumption A single matched PID is sufficient to decide that an IRIS bibliographic resource is, or is not, present in OC Meta.
    The entire Iris in Meta / Iris Not in Meta split (Results) rests on lookup by one normalized PID per record; mismatched or duplicate PIDs in OC Meta are resolved by a completeness-based selection of 1,121 duplicate occurrences.
  • domain assumption OC Meta contains all bibliographic resources that have any citation in the OC Index, and citation coverage is representative for comparison with Scopus and WoS.
    Stated in Discussion: resources with no incoming or outgoing citation in OC Index are absent from OC Meta by construction, so coverage is bounded by the citation sources (Crossref, DataCite, NIH-OCC, OpenAIRE, Japan Link Centre).
  • domain assumption The UNIBO IRIS dump of May 2025 is a complete record of the University's scientific production.
    The denominator of the 36% coverage figure is the 402,505-record IRIS dump; incompleteness or duplicates in IRIS (e.g., 86,306 detected duplicates) directly scale the headline rate.

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Cite this review

Pith. "Pith review of Analysing the coverage of the University of Bologna's bibliographic and citation metadata in OpenCitations collections." pith.science (2026). https://pith.science/paper/XPZOIFIE

@misc{pith2026250105821,
  author       = {Pith},
  title        = {Pith review of: Analysing the coverage of the University of Bologna's bibliographic and citation metadata in OpenCitations collections},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XPZOIFIE}},
  note         = {Machine review of arXiv:2501.05821}
}
read the original abstract

This study focuses on analysing the coverage of publications' metadata available in the Current Research Information System (CRIS) infrastructure of the University of Bologna (UNIBO), implemented by the IRIS platform, within an authoritative source of open research information, i.e. OpenCitations. The analysis considers data regarding the publication entities alongside the citation links. We precisely quantify the proportion of UNIBO IRIS publications included in OpenCitations, examine their types, and evaluate the number of citations in OpenCitations that involve IRIS publications. Our methodology filters and transforms data dumps of IRIS and OpenCitations, creating novel datasets used for the analysis. Our findings reveal that only 36% of IRIS is covered in OpenCitations, with journal articles exhibiting the highest coverage. We identified 5,129,406 citation links pointing to UNIBO IRIS publications. From a purely quantitative perspective, comparing our results with broader proprietary services like Scopus and Web of Science reveals a comparable quantitative coverage in the number of IRIS bibliographic resources included in all the systems analysed (OpenCitations, Scopus and Web of Science) as well as in the number of citations received by them.

Figures

Figures reproduced from arXiv: 2501.05821 by the authors.

Figure 1
Figure 1. The number of publications per year of publication in IRIS. The considered range [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 2
Figure 2. The number of publications per year of publication in OpenCitations Meta. The [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
Figure 3
Figure 3. Overview of the workflow for the adopted methodology. The workflow consists of six steps, beginning with the entire collection of bibliographic resources from IRIS, refining the data, and culminating in a comparison with the OC Meta and Index datasets. A final step also includes a quantitative comparison with research information coming from two proprietary services, i.e. Scopus and Web of Science. Output numbers fo… view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: Overview of the mismatching types between IRIS and OC Meta. Bibliographic Records without Permanent IDs Analysing Iris No ID, we found that 34.5% of the BRs in the original IRIS data dump (138,926 records) do not have any of the PID schemes that OC Meta collects in the…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

37 extracted references · 34 canonical work pages

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    Analysing the coverage of the University of Bologna’s bibliographic and citation metadata in OpenCitations collections Erica Andreose1 [orcid:0009-0003-7124-9639], Salvatore Di Marzo1 [orcid:0009-0006-0853-1772], Ivan Heibi2,3 [orcid:0000-0001-5366-5194], Silvio Peroni2,3 [orcid:0000-0003-0530-4305], Leonardo Zilli1 [orcid:0009-0007-4127-4875] 1 Digital H...

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    The number of publications per year of publication in OpenCitations Meta. The considered range shown in the graph spans from 1953 to 2025 (incomplete). Table

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    is hosted in the AMSActa Institutional Research Repository. It comprises bibliographic metadata of all UNIBO publications (research articles, books, databases, etc.) available in IRIS. To better understand the time coverage of the dataset and the distribution of records over the years, Figure 1 presents the annual count of publications included in IRIS fr...

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    The number of publications per year of publication in IRIS. The considered range spans from 1953 to 2025 (incomplete). This dataset contains seven distinct CSV files, each describing a specific aspect of the publications, with a total of 402,505 bibliographic records. As summarised in Table 1, it includes details about the people involved, such as authors...

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    Count of the citations in Iris in Idex involving IRIS BRs. Role of IRIS BR Citation count Citing 5,281,530 Cited 5,129,406 Citing and Cited 459,323 We also extract the citation counts received by IRIS BRs retrieved in Scopus and Web of Science on the 1st of April 2025 to have ...

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    A sample taken from the OC Meta CSV dump; the first column represents the attributes (columns in the CSV) of the corresponding bibliographic entity. Attribute Value id doi:10.1007/978-3-030-00668-6_8 openalex:W2891148407 omid:br/061602192186 title The SPAR Ontologies author Pe...

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    If the publication date in OC Meta is missing, the corresponding publication year present in IRIS is used as a fallback for the temporal filtering. Since the IRIS dataset was extracted at the beginning of May 2025, we assume that no resources in it should have a publication da...

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    and Web of Science (Birkle et al., 2020), on the 1st of April 2025, of all the IRIS entities included in our dataset. These data enable us to quantitatively compare the data extracted from OpenCitations with well-known proprietary sources, and to measure the average number of ...

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    for traditional publications and other archives and repositories for different kinds of research outcomes – e.g. Software Heritage (Di Cosmo & Zacchiroli, 2017). On the other hand, IRIS includes many types of research outputs (as summarised in Appendix

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    – working on the European Open Science Cloud (EOSC) (Burgelman, 2021), set up by the EOSC Association (https://eosc.eu) in recent years. Recent efforts in this direction have been devised and proposed in the context of the RDA Scientific Knowledge Graphs – Interoperability Fra...

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    Scopus and Web of Science data – The citation data used in the study from Scopus and Web of Science have been obtained using their respective APIs by specifying the Scopus ID and the Web of Science ID of each IRIS BR considered, since such identifiers are stored within the IRI...

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    [Structured data; XML, Parquet]. Figshare. https://doi.org/10.6084/m9.figshare.25897708.v3 Appendix 1: BRs type counting in the deduplicated IRIS dataset and Iris In Meta Table

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    PnYnMnD”, where “P

    having the shape “PnYnMnD”, where “P” indicates the period, “nY” indicates the number of years, “nM” indicates the number of months, and “nD” indicates the number of days. Attribute Value id oci:06404659278-06201483429 citing omid:br/06404659278 cited omid:br/06201483429 creat...

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    The relatively low number of records for 2025 is instead explained by the fact that the data dump only includes publications stored by researchers by the beginning of May

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    stands out as a prominent example that has been used for studies to determine potential alternatives to commercial sources for research assessment exercises in Italy (Bologna et al., 2022), for assessing the quality and utility of OpenAIRE in monitoring EU-funded research (Mug...

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    Most Italian universities adopt this software to handle their current research information system (CRIS)

    has been developed by CINECA, a not-for-profit Consortium comprising 70 Italian universities, 4 Italian Research Institutions, and the Italian Ministry of Education. Most Italian universities adopt this software to handle their current research information system (CRIS). IRIS ...

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    214–222)

    (pp. 214–222). Edizioni Efesto. https://enressh.eu/wp-content/uploads/2017/02/WG3_Supplementary_material_Ma-Cleere-ISSI2019.pdf Maddi, A., Maisonobe, M., & Boukacem-Zeghmouri, C. (2025). Geographical and disciplinary coverage of open access journals: OpenAlex, Scopus, and WoS....

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    As a last example, OpenAlex (Priem et al.,

    is an open scholarly infrastructure dedicated to the publication of bibliographic metadata and citation data that have been used in several studies within the scientometrics community to analyse particular aspects of scholarly phenomena such as retractions in the Humanities (H...

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    is another relevant provider that has been used in several recent studies to examine its coverage compared to commercial alternatives (Culbert et al., 2025; Maddi et al., 2025; Céspedes et al.,

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    enables the creation of components for plugging additional sources of bibliographic metadata and citation data in and can be used to facilitate the processing of these missing data in IRIS. Such components will, in principle, allow any IRIS installation to be interoperable wit...

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    and bibliometric analysis (Alperin, 2024). Even if, in recent years, the data from open scholarly infrastructures has been already used in research studies, including those highlighted above, there has not been a broad evidence of adoption of such open research information in ...

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    Materials and methods

    to use for the analysis. Second, we needed to work with one of the authoritative sources of open research information containing bibliographic metadata and citation data to measure the data coverage highlighted in RQ1 and RQ2 (commitment collaboration). We chose to interact wi...

    2020

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