Bibliometrics is the quantitative analysis of scholarly publications and the citations between them, used to measure research output, impact and collaboration patterns. For a research office, the practical challenge is rarely gathering these numbers — library systems, funders and university dashboards supply them constantly — but recognising which of the three main types of bibliometrics a given report represents, and what it can and cannot responsibly tell you.
In its simplest form, bibliometrics is the statistical analysis of books, articles and other publications, most often using citation counts to describe patterns in scholarly communication. That one-line definition, drawn from the OECD’s usage and echoed by university library guides, is the starting point for everything that follows.
- What is bibliometrics?
- What are the three types of bibliometrics?
- What bibliometric indicators will appear in a metrics report?
- How should research offices use bibliometrics responsibly?
- Common questions about bibliometrics
- What this means for research offices
What is bibliometrics?
Bibliometrics applies statistical methods to bibliographic data — publication counts, citation counts, co-authorship networks and, increasingly, download and mention data — to describe and evaluate scholarly activity. It sits alongside scientometrics, a closely related field that extends the same statistical logic to science and technology output more broadly; in practice research offices treat the two terms as near-synonyms.
Eugene Garfield, founder of the Institute for Scientific Information and creator of the Science Citation Index in 1964, is widely credited as a founding figure of modern bibliometrics. His citation-indexing work established the infrastructure — later commercialised as Web of Science — that most present-day bibliometric reporting still depends on.
A metrics report a research office receives is rarely a single “bibliometric score.” It is usually a blend of three distinct analytical modes, and conflating them is the single most common source of misread reports.
What are the three types of bibliometrics?
Library and information science distinguishes descriptive, evaluative and relational bibliometrics. Each answers a different question, and each carries a different risk of misinterpretation when applied outside its proper scope.
| Type | Core question it answers | Typical output | Main risk if misread |
|---|---|---|---|
| Descriptive | How much has been published, by whom, where? | Publication counts, output by year, discipline or department | Treated as a quality signal when it only measures volume |
| Evaluative | How much impact or influence has that output had? | Citation counts, h-index, Journal Impact Factor, Field-Weighted Citation Impact | Used to rank individuals directly, ignoring field and career-stage differences |
| Relational | How are researchers, topics or institutions connected? | Co-authorship networks, co-citation maps, research-front clustering | Read as a measure of quality rather than of structure or collaboration |
Descriptive bibliometrics is the safest category for research offices to report externally, because it counts rather than judges. Evaluative bibliometrics is the category most prone to misuse — a single h-index or Journal Impact Factor figure says nothing about an individual paper’s quality. Relational bibliometrics is the least familiar to non-specialists but the most useful for identifying emerging collaboration opportunities or research strengths across a department.
What bibliometric indicators will appear in a metrics report?
Most institutional metrics reports combine a handful of recurring indicators. Knowing which category each one belongs to prevents a descriptive count being read as an evaluative judgement.
- Citation count — the raw number of times a work has been cited; evaluative, but highly field- and age-dependent.
- h-index — an author-level figure meaning a researcher has h publications each cited at least h times; evaluative, and known to disadvantage early-career researchers and those in low-citation-rate fields.
- Journal Impact Factor (JIF) — the average citations per article in a journal over the preceding two years; a journal-level, not an article-level, indicator.
- Field-Weighted Citation Impact (FWCI) — a normalised indicator comparing a publication’s citations against the global average for its subject, document type and publication year; a value above 1 indicates above-average performance for that field.
- Altmetrics — non-citation signals such as policy-document mentions, news coverage, social media activity and downloads, which supplement rather than replace citation-based evaluation.
These indicators are drawn from different underlying databases, and coverage varies. Web of Science and Scopus apply curated, subscription-based indexing; Google Scholar offers broad, free coverage with less curation; Dimensions links publications to grants and clinical trials on a freemium basis. A report’s headline number can shift depending on which source supplied it.
How should research offices use bibliometrics responsibly?
Bibliometrics should inform, not replace, expert judgement. Three widely referenced frameworks set out how research offices can operationalise that principle rather than treat it as an aspiration.
The San Francisco Declaration on Research Assessment (DORA), launched in 2012, commits signatory institutions to avoid using journal-based metrics such as the Journal Impact Factor in hiring, promotion or funding decisions. Imperial College London, for example, states it has applied this commitment since becoming a DORA signatory in 2017.
The UK’s Metric Tide review, commissioned by the then Higher Education Funding Council for England (now part of UK Research and Innovation) and published in 2015, set out five principles for responsible metrics: robustness, humility, transparency, diversity and reflexivity. Those five principles remain the reference point most UK research offices cite when drafting internal metrics policies.
INORMS’ Research Evaluation Working Group publishes the SCOPE framework — Start, Context, Options, Probe, Evaluate — a five-step method research administrators can apply before commissioning or interpreting any metrics report, rather than defaulting to whichever indicator a database happens to surface first.
- Start by clarifying the purpose of the evaluation before selecting any indicator.
- Establish the context: discipline, career stage, output type and comparator group.
- Identify the options available, including qualitative alternatives such as peer review or narrative CVs.
- Probe the suitability and limitations of each proposed indicator.
- Evaluate the process itself once the assessment is complete, and refine it for next time.
Momentum toward narrative-based assessment has also grown outside the UK: the 2022 Coalition for Advancing Research Assessment (CoARA), joined by many Horizon Europe-affiliated funders and institutions, commits signatories to reduce reliance on journal-based and output-count metrics in funding and hiring decisions.
It is worth distinguishing bibliometrics from contributor-level attribution. Bibliometrics counts citations and outputs; it does not record who did what on a given paper. CASRAI originated the CRediT contributor role taxonomy in 2014 for that separate purpose, and the standard is now stewarded by NISO as ANSI/NISO Z39.104-2022. A research office reconciling a bibliometrics report with authorship disputes should reach for CRediT roles, not citation counts.
Common questions about bibliometrics
What is the meaning of bibliometric?
“Bibliometric” describes any measure derived from the statistical analysis of published scholarly output — most commonly publication counts and citation counts. The term covers the underlying data point (a bibliometric) and the wider field that studies it (bibliometrics), and applies equally to authors, journals, institutions and individual articles.
What is an example of bibliometrics?
The h-index is the most commonly cited example: an author with an h-index of 20 has 20 publications that have each received at least 20 citations. Other everyday examples include a journal’s Impact Factor, a department’s annual publication count, and a co-authorship map showing collaboration between institutions.
What is bibliometrics in simple terms?
In simple terms, bibliometrics counts and analyses publications and citations to show how much research is being produced and how much attention it receives. It turns scattered publication records into structured evidence — useful for funding reports and CVs, but never a full substitute for reading the work itself.
Who is the father of bibliometrics?
Eugene Garfield (1925–2017) is widely regarded as the founding figure of bibliometrics and scientometrics. As founder of the Institute for Scientific Information, he created the Science Citation Index in 1964, establishing the citation-indexing infrastructure that underpins most bibliometric analysis conducted today.
What this means for research offices
A metrics report that blends descriptive, evaluative and relational bibliometrics without labelling which is which will inevitably be misread by whoever receives it next — a promotion panel, a funder, or a departmental head. Labelling each figure by type, and pairing evaluative indicators with the field-normalisation context they need, is a low-cost fix most research offices can apply immediately.
As narrative-assessment frameworks such as CoARA and DORA gain signatories, research offices should expect bibliometric reports to sit alongside, not instead of, qualitative evidence in funding and promotion decisions. Building that dual capability now — clear metrics literacy plus a credible narrative-CV process — will matter more with each assessment cycle, not less.
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