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Capturing domain knowledge from multiple sources: the rare bone disorders use case

Overview of attention for article published in Journal of Biomedical Semantics, April 2015
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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 (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
12 Mendeley
Title
Capturing domain knowledge from multiple sources: the rare bone disorders use case
Published in
Journal of Biomedical Semantics, April 2015
DOI 10.1186/s13326-015-0008-2
Pubmed ID
Authors

Tudor Groza, Tania Tudorache, Peter N Robinson, Andreas Zankl

Abstract

Lately, ontologies have become a fundamental building block in the process of formalising and storing complex biomedical information. The community-driven ontology curation process, however, ignores the possibility of multiple communities building, in parallel, conceptualisations of the same domain, and thus providing slightly different perspectives on the same knowledge. The individual nature of this effort leads to the need of a mechanism to enable us to create an overarching and comprehensive overview of the different perspectives on the domain knowledge. We introduce an approach that enables the loose integration of knowledge emerging from diverse sources under a single coherent interoperable resource. To accurately track the original knowledge statements, we record the provenance at very granular levels. We exemplify the approach in the rare bone disorders domain by proposing the Rare Bone Disorders Ontology (RBDO). Using RBDO, researchers are able to answer queries, such as: "What phenotypes describe a particular disorder and are common to all sources?" or to understand similarities between disorders based on divergent groupings (classifications) provided by the underlying sources. RBDO is available at http://purl.org/skeletome/rbdo. In order to support lightweight query and integration, the knowledge captured by RBDO has also been made available as a SPARQL Endpoint at http://bio-lark.org/se_skeldys.html.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 8%
Unknown 11 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 17%
Professor > Associate Professor 2 17%
Student > Master 2 17%
Researcher 2 17%
Student > Bachelor 1 8%
Other 3 25%
Readers by discipline Count As %
Engineering 3 25%
Computer Science 3 25%
Agricultural and Biological Sciences 2 17%
Medicine and Dentistry 2 17%
Social Sciences 1 8%
Other 1 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 26 May 2015.
All research outputs
#1,004,251
of 6,240,226 outputs
Outputs from Journal of Biomedical Semantics
#57
of 240 outputs
Outputs of similar age
#38,618
of 156,708 outputs
Outputs of similar age from Journal of Biomedical Semantics
#4
of 18 outputs
Altmetric has tracked 6,240,226 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 240 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 76% 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 156,708 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.