Evidence map›Paper›PMID 40852436›Full record

ArticleScientometrics2025

Towards multiple ontologies in science mapping. A tribute to Loet Leydesdorff.

Ismael Rafols

Abstract read
In one paragraph

Article in Scientometrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Ismael RafolsINGENIO (CSIC-UPV), Universitat Politècnica de València, València, Spain.ORCID 0000-0002-6527-7778

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article reviews Loet Leydesdorff's contributions to science mapping. It explains how over the years, his mapping techniques evolved from journal mapping to global maps of science and finally towards interactive interfaces portraying multiple classifications and ontologies. It then critically reviews the challenges faced by current approaches to science mapping, which implicitly assume a 'natural' epistemic structure, with examples from two recent case studies. We observe that bottom-up algorithmic approaches, either based on citation or semantic approaches, lack conceptual consistency regarding the type of categories used: in a same classification a category captures methods, another one has materials, a third one contains empirical objects and a fourth is focused on theories, rather than having a single logic. I argue that science mapping would produce more useful representations by using ontologies based on a single logic that aligns with the particular conceptual needs of the analysis. Novel classification methods based on machine learning and language models hold promise to produce these tailored, question-driven ontologies.

Indexed as

ClassificationOntologiesScience maps

Identifiers

PMID40852436
PMCPMC12367962

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.