Evidence map›Paper›PMID 33870066›Full record

ArticleFrontiers in research metrics and analytics2020

Interpreting Bibliometric Data.

Martin Szomszor, Jonathan Adams, Ryan Fry, Chris Gebert, David A Pendlebury, Ross W K Potter, Gordon Rogers

Abstract read
In one paragraph

Article in Frontiers in research metrics and analytics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Review
  7. Article
  8. Review
  9. Article
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  15. Mapping Global Trends inAnimals : an open access journal from MDPI · 2026
    Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. Global Trends in Diabetic Foot Research (2004-2023): A Bibliometric Study Based on the Scopus Database.International journal of environmental research and public health · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Martin SzomszorInstitute for Scientific Information, Clarivate, London, United Kingdom.
Jonathan AdamsInstitute for Scientific Information, Clarivate, London, United Kingdom.
Ryan FryInstitute for Scientific Information, Clarivate, Philadelphia, PA, United States.
Chris GebertInstitute for Scientific Information, Clarivate, Philadelphia, PA, United States.
David A PendleburyInstitute for Scientific Information, Clarivate, Philadelphia, PA, United States.
Ross W K PotterInstitute for Scientific Information, Clarivate, London, United Kingdom.
Gordon RogersInstitute for Scientific Information, Clarivate, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many academic analyses of good practice in the use of bibliometric data address only technical aspects and fail to account for and appreciate user requirements, expectations, and actual practice. Bibliometric indicators are rarely the only evidence put before any user group. In the present state of knowledge, it is more important to consider how quantitative evaluation can be made simple, transparent, and readily understood than it is to focus unduly on precision, accuracy, or scholarly notions of purity. We discuss how the interpretation of 'performance' from a presentation using accurate but summary bibliometrics can change when iterative deconstruction and visualization of the same dataset is applied. From the perspective of a research manager with limited resources, investment decisions can easily go awry at governmental, funding program, and institutional levels. By exploring select real-life data samples we also show how the specific composition of each dataset can influence interpretive outcomes.

Indexed as

bibliometricsdata interpretationresearch assessmentresearch policyresponsible metrics

Identifiers

PMID33870066
PMCPMC8025976

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.