Evidence map›Paper›PMID 27642503›Full record

ReviewComputational and structural biotechnology journal2016

Evolution of biomedical ontologies and mappings: Overview of recent approaches.

Anika Groß, Cédric Pruski, Erhard Rahm

Abstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. A change language for ontologies and knowledge graphs.Database : the journal of biological databases and curation · 2025
    Article
  2. Evaluating MedDRA-to-ICD terminology mappings.BMC medical informatics and decision making · 2024
    Article
  3. Using FlyBase: A Database of Drosophila Genes and Genetics.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
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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.

Anika GroßInstitute of Computer Science, Universität Leipzig, P.O. Box 100920, 04009 Leipzig, Germany.
Cédric PruskiLuxembourg Institute of Science and Technology, 5 Avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg.
Erhard RahmInstitute of Computer Science, Universität Leipzig, P.O. Box 100920, 04009 Leipzig, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biomedical ontologies are heavily used to annotate data, and different ontologies are often interlinked by ontology mappings. These ontology-based mappings and annotations are used in many applications and analysis tasks. Since biomedical ontologies are continuously updated dependent artifacts can become outdated and need to undergo evolution as well. Hence there is a need for largely automated approaches to keep ontology-based mappings up-to-date in the presence of evolving ontologies. In this article, we survey current approaches and novel directions in the context of ontology and mapping evolution. We will discuss requirements for mapping adaptation and provide a comprehensive overview on existing approaches. We will further identify open challenges and outline ideas for future developments.

Indexed as

Biomedical annotationBiomedical ontologyMapping adaptationMapping evolutionOntology-based mappingOntology evolution

Identifiers

PMID27642503
PMCPMC5018063

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.