Evidence map›Paper›PMID 24551360›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2013

A family-based framework for supporting quality assurance of biomedical ontologies in BioPortal.

Zhe He, Christopher Ochs, Ankur Agrawal, Yehoshua Perl, Dimitris Zeginis, Konstantinos Tarabanis, Gai Elhanan, Michael Halper, Natasha Noy, James Geller

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Missing lateral relationships in top-level concepts of an ontology.BMC medical informatics and decision making · 2020
    Article
  2. Article
  3. Review
  4. Article
  5. An empirical analysis of ontology reuse in BioPortal.Journal of biomedical informatics · 2017
    Article
  6. Article
  7. Introducing the Big Knowledge to Use (BK2U) challenge.Annals of the New York Academy of Sciences · 2017
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. A tribal abstraction network for SNOMED CT target hierarchies without attribute relationships.Journal of the American Medical Informatics Association : JAMIA · 2015
    Article
  13. Review
  14. Sculpting the UMLS Refined Semantic Network.Online journal of public health informatics · 2014
    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

10 authors.

Zhe HeNew Jersey Institute of Technology, Newark, NJ;
Christopher OchsNew Jersey Institute of Technology, Newark, NJ;
Ankur AgrawalManhattan College, Riverdale, NY;
Yehoshua PerlNew Jersey Institute of Technology, Newark, NJ;
Dimitris ZeginisUniversity of Macedonia, Thessaloniki, Greece;
Konstantinos TarabanisUniversity of Macedonia, Thessaloniki, Greece;
Gai ElhananHalfpenny Technologies, Blue Bell, PA;
Michael HalperNew Jersey Institute of Technology, Newark, NJ;
Natasha NoyStanford University, Stanford, CA.
James GellerNew Jersey Institute of Technology, Newark, NJ;

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BioPortal contains over 300 ontologies, for which quality assurance (QA) is critical. Abstraction networks (ANs), compact summarizations of ontology structure and content, have been used in such QA efforts, typically in a "one-off" manner for a single ontology. Ontologies can be characterized-independently of knowledge-content focus-from a structural standpoint leading to the formulation of ontology families. A family is defined as a set of ontologies satisfying some overarching condition regarding their structural features. Seven such families, comprising 186 ontologies, are identified. To increase efficiency, a new family-based QA framework is introduced in which an automated, uniform AN derivation technique and accompanying semi-automated, uniform QA regimen are applicable to the ontologies of a given family. Specifically, across an entire family, the QA efforts exploit family-wide AN features in the characterization of sets of classes that are more likely to harbor errors. The approach is demonstrated on the Cancer Chemoprevention BioPortal ontology.

Indexed as

Biological OntologiesQuality Assurance, Health CareAbstracting and IndexingAntineoplastic AgentsHumansNeoplasmsProgramming LanguagesAntineoplastic Agents

Identifiers

PMID24551360
PMCPMC3900201

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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.