Evidence map›Paper›PMID 42054306›Full record

ArticlePloS one2026

The Graphic Descriptor Ontology: An ontology for semantic annotation of graphics and its application to graphic libraries of anatomical standards.

Melissa D Clarkson, Noah C Perry, Landon T Detwiler

Abstract read
In one paragraph

Article in PloS one, 2026. 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

3 authors.

Melissa D ClarksonDivision of Biomedical Informatics, University of Kentucky, Lexington, Kentucky, United States of America.ORCID https://orcid.org/0000-0001-9979-176X
Noah C PerryInstitute for Biomedical Informatics, University of Kentucky, Lexington, Kentucky, United States of America.ORCID https://orcid.org/0009-0004-0450-6022
Landon T DetwilerDivision of Biomedical Informatics, University of Kentucky, Lexington, Kentucky, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The information held by visual representations is typically opaque to information processing systems and able to be interpreted only by human viewers. We introduce the Graphics Descriptor Ontology (GDO) to serve as an ontology for domain-independent annotation and description of graphics and their elements. Our goal is to represent information about graphics that corresponds to what a human observer could conclude from viewing a graphic or that would help to inform a viewer about a graphic. This work builds upon ontological modeling of information content entities and uses theories and vocabularies from the fields of semiotics, visual arts, technical communication, and computer graphics. We define a graphic as a spatial composition composed of graphical marks. The three types of graphical marks are line mark, point mark, and region mark. We present an approach to representing roles and qualities for information content entities, including graphical marks and graphics. Anatomical graphics serve as our use cases, and we provide an anatomy extension for the GDO to model anatomy-specific content. We introduce our work as an illustrated ontology available through a web browser, accompanied by over 100 explanatory graphics.

Indexed as

AnatomyBiological OntologiesComputer GraphicsSemanticsHumans

Identifiers

PMID42054306
PMCPMC13127929

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.