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Dead simple OWL design patterns

Overview of attention for article published in Journal of Biomedical Semantics, June 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)

Mentioned by

twitter
9 tweeters

Citations

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24 Dimensions

Readers on

mendeley
29 Mendeley
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2 CiteULike
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Title
Dead simple OWL design patterns
Published in
Journal of Biomedical Semantics, June 2017
DOI 10.1186/s13326-017-0126-0
Pubmed ID
Authors

David Osumi-Sutherland, Melanie Courtot, James P. Balhoff, Christopher Mungall

Abstract

Bio-ontologies typically require multiple axes of classification to support the needs of their users. Development of such ontologies can only be made scalable and sustainable by the use of inference to automate classification via consistent patterns of axiomatization. Many bio-ontologies originating in OBO or OWL follow this approach. These patterns need to be documented in a form that requires minimal expertise to understand and edit and that can be validated and applied using any of the various programmatic approaches to working with OWL ontologies. Here we describe a system, Dead Simple OWL Design Patterns (DOS-DPs), which fulfills these requirements, illustrating the system with examples from the Gene Ontology. The rapid adoption of DOS-DPs by multiple ontology development projects illustrates both the ease-of use and the pressing need for the simple design pattern system we have developed.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 28 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 31%
Student > Ph. D. Student 6 21%
Student > Doctoral Student 4 14%
Student > Bachelor 2 7%
Student > Master 1 3%
Other 3 10%
Unknown 4 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 38%
Computer Science 9 31%
Biochemistry, Genetics and Molecular Biology 2 7%
Medicine and Dentistry 2 7%
Engineering 1 3%
Other 0 0%
Unknown 4 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 September 2021.
All research outputs
#4,037,730
of 20,501,648 outputs
Outputs from Journal of Biomedical Semantics
#70
of 347 outputs
Outputs of similar age
#72,439
of 286,976 outputs
Outputs of similar age from Journal of Biomedical Semantics
#1
of 1 outputs
Altmetric has tracked 20,501,648 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 347 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 79% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 286,976 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them