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Using AberOWL for fast and scalable reasoning over BioPortal ontologies

Overview of attention for article published in Journal of Biomedical Semantics, August 2016
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Title
Using AberOWL for fast and scalable reasoning over BioPortal ontologies
Published in
Journal of Biomedical Semantics, August 2016
DOI 10.1186/s13326-016-0090-0
Pubmed ID
Authors

Luke Slater, Georgios V. Gkoutos, Paul N. Schofield, Robert Hoehndorf

Abstract

Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most other tools utilizing ontologies, either provide access to ontologies without use of automated reasoning, or limit the number of ontologies for which automated reasoning-based access is provided. We apply the AberOWL infrastructure to provide automated reasoning-based access to all accessible and consistent ontologies in BioPortal (368 ontologies). We perform an extensive performance evaluation to determine query times, both for queries of different complexity and for queries that are performed in parallel over the ontologies. We demonstrate that, with the exception of a few ontologies, even complex and parallel queries can now be answered in milliseconds, therefore allowing automated reasoning to be used on a large scale, to run in parallel, and with rapid response times.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 22%
Student > Ph. D. Student 4 22%
Researcher 3 17%
Student > Doctoral Student 1 6%
Other 1 6%
Other 3 17%
Unknown 2 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 33%
Computer Science 5 28%
Engineering 2 11%
Biochemistry, Genetics and Molecular Biology 1 6%
Business, Management and Accounting 1 6%
Other 0 0%
Unknown 3 17%
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 10 August 2016.
All research outputs
#18,467,278
of 22,882,389 outputs
Outputs from Journal of Biomedical Semantics
#299
of 364 outputs
Outputs of similar age
#281,515
of 364,241 outputs
Outputs of similar age from Journal of Biomedical Semantics
#7
of 8 outputs
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So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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