Evidence map›Paper›PMID 23304341›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012

Deriving an abstraction network to support quality assurance in OCRe.

Christopher Ochs, Ankur Agrawal, Yehoshua Perl, Michael Halper, Samson W Tu, Simona Carini, Ida Sim, Natasha Noy, Mark Musen, James Geller

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012. 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. Article
  2. Article
  3. Review
  4. Article
  5. Introducing the Big Knowledge to Use (BK2U) challenge.Annals of the New York Academy of Sciences · 2017
    Review
  6. Article
  7. Article
  8. Modelling Medications for Public Health Research.Online journal of public health informatics · 2016
    Article
  9. Article
  10. Review
  11. 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.

Christopher OchsNew Jersey Institute of Technology, Newark, NJ, USA.
Ankur Agrawal
Yehoshua Perl
Michael Halper
Samson W Tu
Simona Carini
Ida Sim
Natasha Noy
Mark Musen
James Geller

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An abstraction network is an auxiliary network of nodes and links that provides a compact, high-level view of an ontology. Such a view lends support to ontology orientation, comprehension, and quality-assurance efforts. A methodology is presented for deriving a kind of abstraction network, called a partial-area taxonomy, for the Ontology of Clinical Research (OCRe). OCRe was selected as a representative of ontologies implemented using the Web Ontology Language (OWL) based on shared domains. The derivation of the partial-area taxonomy for the Entity hierarchy of OCRe is described. Utilizing the visualization of the content and structure of the hierarchy provided by the taxonomy, the Entity hierarchy is audited, and several errors and inconsistencies in OCRe's modeling of its domain are exposed. After appropriate corrections are made to OCRe, a new partial-area taxonomy is derived. The generalizability of the paradigm of the derivation methodology to various families of biomedical ontologies is discussed.

Indexed as

Vocabulary, ControlledBiomedical ResearchMedical Informatics

Identifiers

PMID23304341
PMCPMC3540580

What OpenQuestion holds

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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.