CASRAI Dictionary

Tag: Web of Science

  • Scopus vs Web of Science: Bibliographic Databases Compared

    Scopus is Elsevier’s large multidisciplinary abstract and citation database, and it is the principal alternative to Clarivate’s Web of Science for tracking scholarly literature and its citation relationships. Both index peer-reviewed publications and the citations between them, but they differ in coverage philosophy, the headline metrics they publish, and how each is used in research assessment.

    This article compares the two systems across the dimensions that matter for choosing and interpreting them, and offers a side-by-side table to summarise the differences.

    Coverage and selection

    Both databases are curated rather than exhaustive, applying editorial selection to the titles they index, but they make different trade-offs. Scopus is generally regarded as having a broader title list and wider coverage of disciplines, regions and document types, while Web of Science’s Core Collection is associated with a more tightly selective tradition rooted in the citation-index approach pioneered by Eugene Garfield. Neither covers the entire scholarly literature, and any analysis drawn from them is shaped by what each chooses to index. We unpack the Web of Science side in detail in our Web of Science explainer.

    The headline metrics: CiteScore and the Impact Factor

    Each platform has its own flagship journal-level metric. Scopus publishes CiteScore, a citation-per-document measure computed over a multi-year window from Scopus data. Web of Science, through the Journal Citation Reports, publishes the Journal Impact Factor, computed over a shorter window from Web of Science data. Because the two metrics use different source databases and calculation windows, a journal’s CiteScore and Impact Factor are not directly comparable, and a title may rank differently depending on which system you consult.

    Both are journal-level indicators. Neither is a reliable measure of the quality of an individual article or researcher, and responsible-metrics frameworks consistently warn against that misuse.

    Side-by-side comparison

    Dimension Scopus Web of Science
    Provider Elsevier Clarivate
    Type Abstract & citation database Citation-index platform (Core Collection)
    Coverage style Broad, multidisciplinary selection Selective Core Collection
    Headline journal metric CiteScore Journal Impact Factor (via JCR)
    Metric source data Scopus citations Web of Science citations
    Access Subscription Subscription

    Use in research assessment

    Both databases are widely used in research evaluation, university rankings and bibliometric studies, and many institutions subscribe to both because their differing coverage produces different — and complementary — views of the same literature. A bibliometric analysis can yield materially different results depending on which database supplies the underlying data, so methodological transparency about the source is essential.

    Crucially, citation databases describe attention and connectivity, not intrinsic merit. Movements such as responsible-metrics and narrative-CV approaches encourage assessors to use these tools as one input among many, alongside qualitative judgement and contributor-level information such as that captured by the CRediT contributor-roles taxonomy. Both systems also depend on persistent identifiers — especially the DOI — to disambiguate and link records accurately, and they sit within the broader landscape of research information systems.

    Which should you use?

    There is no universally correct answer. For the widest net across disciplines and document types, Scopus is often preferred; for the longer-established citation-index tradition and the Journal Impact Factor specifically, Web of Science is the source. For any serious analysis, using both and being explicit about coverage limitations is the most defensible approach. Definitions of the metrics named here are maintained in the CASRAI dictionary.

    Frequently asked questions

    Is Scopus bigger than Web of Science?

    Scopus is generally described as having a broader title list and wider document coverage, while Web of Science’s Core Collection is more selective. The right database depends on whether breadth or selectivity matters more for your purpose.

    Can I compare a CiteScore directly with an Impact Factor?

    No. CiteScore and the Journal Impact Factor are computed from different source databases over different time windows, so the two numbers are not interchangeable and should not be compared head to head.

    Do universities subscribe to both?

    Many research institutions subscribe to both Scopus and Web of Science precisely because their differing coverage gives complementary perspectives on the literature and on journal performance.

    Are these databases suitable for evaluating individual researchers?

    Their journal-level metrics are not designed to assess individuals, and responsible-metrics guidance cautions strongly against using them that way. They are best treated as one input within a broader, qualitative assessment.

  • Web of Science: What It Indexes and How It Works

    Web of Science is a curated, selective citation-indexing platform operated by Clarivate that records scholarly publications and the citation links between them, enabling researchers to trace how ideas connect across the literature. Rather than indexing everything it can find, Web of Science applies editorial selection criteria, and its data underpins widely used research metrics including those published in the Journal Citation Reports.

    This article explains what the Web of Science Core Collection contains, how citation indexing works, its relationship to the Journal Impact Factor, and why a citation index is fundamentally different from a general search engine.

    The Core Collection and selective indexing

    At the heart of Web of Science is the Core Collection, a set of citation indexes covering the sciences, social sciences and arts and humanities, together with conference proceedings and book content. The defining characteristic is selectivity: journals are evaluated against editorial and quality criteria before being accepted, and coverage is curated rather than exhaustive. The intention is that the corpus represents influential, well-edited scholarly literature, so that the citation relationships drawn from it are meaningful.

    This selectivity is the central trade-off of the platform. A narrower, vetted corpus yields cleaner citation data, but it also means many legitimate outputs — particularly in regions, languages or fields with less established journals — may fall outside coverage. Understanding what is and is not indexed is essential before using the data for any kind of assessment.

    The citation index: Garfield’s idea

    The conceptual foundation of Web of Science is the citation index, an idea developed by Eugene Garfield, who founded the Institute for Scientific Information. The insight was simple but powerful: by systematically recording which papers cite which other papers, you create a navigable network of the literature. From any article you can move backwards to the references it cites and forwards to the later papers that cite it.

    This forward-and-backward navigation is what distinguishes a citation index from a bibliographic list. It lets researchers follow the development of an idea over time, identify foundational works, and gauge the influence of a paper by the citations it accrues. The same citation graph is the raw material from which bibliometric indicators are computed.

    The Journal Citation Reports and the Impact Factor

    Web of Science citation data feeds the Journal Citation Reports (JCR), Clarivate’s annual analysis of journal-level citation performance. The JCR is the source of the well-known Journal Impact Factor, a journal-level metric calculated from citation counts to a journal’s recent articles. Because the Impact Factor is derived from Web of Science data, a journal must be indexed in the relevant part of the Core Collection to receive one.

    Element What it is
    Core Collection The curated set of citation indexes underpinning the platform
    Citation index The network of citing–cited relationships between publications
    Journal Citation Reports Annual journal-level citation analysis built on the data
    Journal Impact Factor A journal-level metric published within the JCR

    It is important to stress that the Impact Factor is a journal-level measure and is widely cautioned against as a proxy for the quality of any individual article or researcher. Responsible-metrics initiatives encourage using it carefully and in context.

    How it differs from a search engine

    A general web search engine indexes pages it can crawl and ranks them by relevance and popularity signals. Web of Science is different in three respects: its corpus is selected rather than crawled; its core data structure is the citation graph rather than full-text relevance; and its records are structured bibliographic metadata — authors, affiliations, references, funding — rather than raw web content. This makes it a tool for analysis and discovery within the scholarly record, not a general-purpose finder of web pages. Related tools and systems are covered across our research information systems section.

    Web of Science is frequently compared with Elsevier’s Scopus, the other large multidisciplinary citation database; we set the two side by side in our Scopus versus Web of Science comparison. Both rely on persistent identifiers such as the DOI to link records reliably, and definitions of the metrics involved appear in the CASRAI dictionary.

    Frequently asked questions

    Is Web of Science free to use?

    No. Web of Science is a subscription product from Clarivate, typically licensed by universities, research institutions and libraries. Access depends on your organisation’s subscription.

    Does being in Web of Science mean a journal is high quality?

    Inclusion signals that a journal met the platform’s selection criteria, which is a meaningful editorial threshold. It is not, however, an absolute or universal measure of quality, and many reputable journals sit outside its coverage.

    What is the difference between Web of Science and the Journal Citation Reports?

    Web of Science is the underlying citation database; the Journal Citation Reports is an annual analytical product built from that data, and it is where the Journal Impact Factor is published.

    Who invented the citation index?

    The citation-index concept was developed by Eugene Garfield, founder of the Institute for Scientific Information, whose work established the systematic recording of citation links that Web of Science still embodies.

  • Recognising peer reviewers: from anonymous service to credited contribution

    Peer review is the labour the scholarly system depends on most and rewards least. Reviewing a manuscript well takes hours of expert attention — reading carefully, checking methods, catching errors, sometimes reshaping a paper substantially — and almost all of it happens anonymously, unpaid, and unrecorded. The reviewer’s name never appears, the report is rarely seen, and the work leaves no trace on any CV. Making that contribution visible and creditable, without necessarily compromising the anonymity that protects candid review, is the problem this article is about. It sits in the credit-extensions domain and connects to the wider question of who gets credit for what, addressed through the CRediT taxonomy.

    Why review is the great uncredited contribution

    The invisibility of review is not an oversight; it is structural. Most review is single- or double-anonymous by design, and for good reason — anonymity lets a reviewer write a frank, critical report without fear of reprisal, particularly when assessing the work of someone more senior. But the same anonymity that protects candour also erases recognition. A researcher who reviews thirty manuscripts a year has nothing to show for it, while the system quietly assumes they will keep doing it. The result is a recognition gap that bears hardest on the early-career researchers who do a great deal of reviewing and have the most to gain from having it counted.

    It is worth being clear about scope. The CRediT taxonomy deliberately covers authorship contributions to a specific paper; it has no role for the reviewers of that paper, because they are not contributors to it in the authorship sense. Recognising review is therefore an adjacent problem to CRediT rather than something CRediT itself solves — which is exactly why a dedicated vocabulary and dedicated infrastructure for reviewer recognition matter.

    The shift from anonymous service to recorded activity

    The key insight behind reviewer recognition is that you can record that a review happened — and credit the reviewer for it — without revealing what the review said or which way it leaned. The unit of recognition is the review activity: a verified record that a named researcher completed a review for a named venue on a given date. The content stays confidential; the contribution becomes visible. This decoupling is what makes it possible to credit review without breaking the anonymity that makes honest review possible in the first place.

    ORCID review records

    ORCID supports peer review as a first-class activity type on a researcher’s record. A journal or platform that integrates with ORCID can deposit a structured review record directly onto the reviewer’s ORCID profile: it states that the person performed a review for a particular organisation, at a particular time, typically without disclosing the manuscript or the verdict. Because the record is asserted by the venue rather than self-claimed, it is verified — it carries the weight of having come from the journal, not merely the reviewer’s say-so. Over time, a reviewer accumulates a trustworthy, machine-readable record of their review activity that travels with their ORCID iD into CVs, funding applications, and institutional systems.

    Web of Science reviewer recognition

    Web of Science reviewer recognition — the service that grew out of the platform formerly known as Publons — provides a complementary route. It lets reviewers build a verified record of their reviewing (and editorial) activity across journals, again typically capturing the fact and venue of a review rather than its confidential content, and presents it as a profile a researcher can point to. Many publishers feed verified review activity into this system automatically, and it interoperates with ORCID so that the same activity can surface on a researcher’s ORCID record. The two together — ORCID as the open, portable identity layer and Web of Science as a recognition platform that aggregates and displays activity — form the practical backbone of reviewer recognition today.

    Open review and stronger forms of credit

    Where a venue practises open peer review, the recognition can go further. If a reviewer chooses to sign their report, or if the report is published alongside the article (with or without the reviewer’s name), the review becomes a citable object in its own right — an output a reviewer can point to directly, not merely an activity record. This is the strongest form of review credit, because it makes not just the fact of the review but its substance part of the public record. It is optional and not appropriate for every context, but where it is used it turns review from invisible service into a visible scholarly contribution. (For the trade-offs of opening review, the distinction between signed and transparent models matters a great deal.)

    Why recognition matters beyond fairness

    Crediting review is not only about being fair to reviewers, though it is that. It also serves the system. A reviewer-recognition record gives editors a verifiable signal of who reviews, how much, and in what fields — useful for finding and acknowledging reliable reviewers. It gives funders and hiring committees, increasingly under responsible-assessment reforms that value contribution over output-counting, a legitimate way to see and reward an activity that crude publication metrics ignore entirely. And by making the labour visible, it makes the implicit bargain of the system explicit: review is work, work deserves recognition, and recognition can be recorded without compromising the confidentiality review depends on. The same principle that animates the credit due to authors applies to reviewers — contribution should be recorded honestly and in a form that travels.

    Where shared vocabulary fits

    “Peer review”, “reviewer recognition”, “review record”, “signed review”, and “review activity” are recorded inconsistently across journals and platforms, which is exactly how review contributions get lost or double-counted. A shared, federated vocabulary that defines these terms precisely — and points back to ORCID’s peer-review schema and the recognised reviewer-recognition platforms — is what lets a review credited in one system be understood in another. Supplying that definitional layer is the role the CASRAI dictionary is designed to play; the relevant terms sit in the credit-extensions domain.

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