Evidence map›Paper›PMID 19154797›Full record

ArticleJournal of biomedical informatics2009

The caBIG terminology review process.

James J Cimino, Terry F Hayamizu, Olivier Bodenreider, Brian Davis, Grace A Stafford, Martin Ringwald

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Enabling international adoption of LOINC through translation.Journal of biomedical informatics · 2012
    Article
  5. Article
  6. The PhenX Toolkit: get the most from your measures.American journal of epidemiology · 2011
    Article
  7. Building a biomedical cyberinfrastructure for collaborative research.American journal of preventive medicine · 2011
    Article
  8. Exposing the cancer genome atlas as a SPARQL endpoint.Journal of biomedical informatics · 2010
    Article
  9. Article
  10. Knowledge-based data analysis comes of age.Briefings in bioinformatics · 2010
    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.

James J CiminoNational Institutes of Health, Laboratory for Informatics Development, Clinical Center, Room 6-2551, 10 Center Drive, Bethesda, MD 20892, USA. ciminoj@mail.nih.gov
Terry F Hayamizu
Olivier Bodenreider
Brian Davis
Grace A Stafford
Martin Ringwald

Funding

Intramural NIH HHS Z99 CL999999Intramural NIH HHS Z99 LM999999PHS HHS GS-35F-0306J
6 · The paper itself

Abstract

The National Cancer Institute (NCI) is developing an integrated biomedical informatics infrastructure, the cancer Biomedical Informatics Grid (caBIG), to support collaboration within the cancer research community. A key part of the caBIG architecture is the establishment of terminology standards for representing data. In order to evaluate the suitability of existing controlled terminologies, the caBIG Vocabulary and Data Elements Workspace (VCDE WS) working group has developed a set of criteria that serve to assess a terminology's structure, content, documentation, and editorial process. This paper describes the evolution of these criteria and the results of their use in evaluating four standard terminologies: the Gene Ontology (GO), the NCI Thesaurus (NCIt), the Common Terminology for Adverse Events (known as CTCAE), and the laboratory portion of the Logical Objects, Identifiers, Names and Codes (LOINC). The resulting caBIG criteria are presented as a matrix that may be applicable to any terminology standardization effort.

Indexed as

Medical InformaticsTerminology as TopicNational Institutes of Health (U.S.)United States

Identifiers

PMID19154797
PMCPMC2729758

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.