Evidence map›Paper›PMID 27345947›Full record

ArticleJournal of biomedical informatics2016

A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies.

Christopher Ochs, James Geller, Yehoshua Perl, Mark A Musen

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Big knowledge visualization of the COVID-19 CIDO ontology evolution.BMC medical informatics and decision making · 2023
    Article
  2. Article
  3. Article
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  5. Article
  6. Missing lateral relationships in top-level concepts of an ontology.BMC medical informatics and decision making · 2020
    Article
  7. Web-based Interactive Visualization of Non-Lattice Subgraphs (WINS) in SNOMED CT.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. An empirical analysis of ontology reuse in BioPortal.Journal of biomedical informatics · 2017
    Article
  16. Article
  17. Article
  18. Introducing the Big Knowledge to Use (BK2U) challenge.Annals of the New York Academy of Sciences · 2017
    Review
  19. Taxonomy-Based Approaches to Quality Assurance of Ontologies.Journal of healthcare engineering · 2017
    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

4 authors.

Christopher OchsComputer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA. Electronic address: cro3@njit.edu.
James GellerComputer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Yehoshua PerlComputer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Mark A MusenStanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA 94305, USA.

Funding

A family-based framework of quality assurance for biomedical ontologiesR01CA190779 · NCI · NEW JERSEY INSTITUTE OF TECHNOLOGY · PI PERL, YEHOSHUA · 2015 to 2017
$1.8M
NCI NIH HHS R01 CA190779
6 · The paper itself

Abstract

Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial-area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial-area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF), a unified framework and software system for deriving, visualizing, and exploring partial-area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g., OWL and SNOMED CT's relational format). A Protégé plugin for deriving "live partial-area taxonomies" is demonstrated.

Indexed as

Biological OntologiesSoftwareQuality Assurance, Health CareStatistics as TopicSystematized Nomenclature of MedicineAbstraction network derivationOntology explorationOntology summarizationOntology toolsVisualization of ontology content

Identifiers

PMID27345947
PMCPMC4987206

What OpenQuestion holds

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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.