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A UML profile for the OBO relation ontology

Overview of attention for article published in BMC Genomics, October 2012
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Title
A UML profile for the OBO relation ontology
Published in
BMC Genomics, October 2012
DOI 10.1186/1471-2164-13-s5-s3
Pubmed ID
Authors

Gabriela DA Guardia, Ricardo ZN Vêncio, Cléver RG de Farias

Abstract

Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 4%
Germany 1 4%
Brazil 1 4%
Unknown 24 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 30%
Researcher 5 19%
Other 2 7%
Student > Master 2 7%
Professor 1 4%
Other 3 11%
Unknown 6 22%
Readers by discipline Count As %
Computer Science 12 44%
Biochemistry, Genetics and Molecular Biology 3 11%
Agricultural and Biological Sciences 3 11%
Medicine and Dentistry 1 4%
Unknown 8 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 January 2013.
All research outputs
#15,260,208
of 22,691,736 outputs
Outputs from BMC Genomics
#6,661
of 10,617 outputs
Outputs of similar age
#110,347
of 176,084 outputs
Outputs of similar age from BMC Genomics
#89
of 137 outputs
Altmetric has tracked 22,691,736 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,617 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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 176,084 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 137 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.