Evidence map›Paper›PMID 29329592›Full record

ReviewJournal of biomedical semantics2018

The eXtensible ontology development (XOD) principles and tool implementation to support ontology interoperability.

Yongqun He, Zuoshuang Xiang, Jie Zheng, Yu Lin, James A Overton, Edison Ong

Abstract readReview
In one paragraph

Review in Journal of biomedical semantics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 2 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

43 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. VO: The Vaccine Ontology.Scientific data · 2026
    Article
  5. Article
  6. VO: The Vaccine Ontology.bioRxiv : the preprint server for biology · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. MAD-Onto: an ontology design for mobile app development.Frontiers in artificial intelligence · 2025
    Article
  11. Article
  12. Article
  13. GallOnt: An ontology for plant gall phenotypes.Biodiversity data journal · 2024
    Article
  14. Article
  15. The use of foundational ontologies in biomedical research.Journal of biomedical semantics · 2023
    Review
  16. Review
  17. Automated approach for quality assessment of RDF resources.BMC medical informatics and decision making · 2023
    Article
  18. Article
  19. Article
  20. Article
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

6 authors.

Yongqun HeUnit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA. yongqunh@med.umich.edu.ORCID 0000-0001-9189-9661
Zuoshuang XiangUnit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
Jie ZhengDepartment of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Yu LinCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
James A OvertonKnocean Inc., Toronto, ON, Canada.
Edison OngDepartment of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.

Funding

Ontology-based Information Network to Support Vaccine ResearchR01AI081062 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HE, YONGQUN · 2009 to 2012
$1.1M
NIAID NIH HHS R01 AI081062
6 · The paper itself

Abstract

Ontologies are critical to data/metadata and knowledge standardization, sharing, and analysis. With hundreds of biological and biomedical ontologies developed, it has become critical to ensure ontology interoperability and the usage of interoperable ontologies for standardized data representation and integration. The suite of web-based Ontoanimal tools (e.g., Ontofox, Ontorat, and Ontobee) support different aspects of extensible ontology development. By summarizing the common features of Ontoanimal and other similar tools, we identified and proposed an "eXtensible Ontology Development" (XOD) strategy and its associated four principles. These XOD principles reuse existing terms and semantic relations from reliable ontologies, develop and apply well-established ontology design patterns (ODPs), and involve community efforts to support new ontology development, promoting standardized and interoperable data and knowledge representation and integration. The adoption of the XOD strategy, together with robust XOD tool development, will greatly support ontology interoperability and robust ontology applications to support data to be Findable, Accessible, Interoperable and Reusable (i.e., FAIR).

Indexed as

Biological OntologiesSemanticsSoftwareAnd ontology design patterneXtensible ontology developmentInteroperabilityOntoanimal toolsOntobeeOntofoxOntologyOntoratSemantic alignmentSoftware

Identifiers

PMID29329592
PMCPMC5765662

What Socratic 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 Socratic graph.