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RDF2Graph a tool to recover, understand and validate the ontology of an RDF resource

Overview of attention for article published in Journal of Biomedical Semantics, October 2015
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  • Good Attention Score compared to outputs of the same age (69th percentile)

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Citations

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39 Mendeley
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Title
RDF2Graph a tool to recover, understand and validate the ontology of an RDF resource
Published in
Journal of Biomedical Semantics, October 2015
DOI 10.1186/s13326-015-0038-9
Pubmed ID
Authors

Jesse CJ van Dam, Jasper J Koehorst, Peter J Schaap, Vitor AP Martins dos Santos, Maria Suarez-Diez

Abstract

Semantic web technologies have a tremendous potential for the integration of heterogeneous data sets. Therefore, an increasing number of widely used biological resources are becoming available in the RDF data model. There are however, no tools available that provide structural overviews of these resources. Such structural overviews are essential to efficiently query these resources and to assess their structural integrity and design, thereby strengthening their use and potential. Here we present RDF2Graph, a tool that automatically recovers the structure of an RDF resource. The generated overview allows to create complex queries on these resources and to structurally validate newly created resources. RDF2Graph facilitates the creation of complex queries thereby enabling access to knowledge stored across multiple RDF resources. RDF2Graph facilitates creation of high quality resources and resource descriptions, which in turn increases usability of the semantic web technologies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 5%
United States 2 5%
Norway 1 3%
Japan 1 3%
Netherlands 1 3%
Unknown 32 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 36%
Professor > Associate Professor 4 10%
Student > Master 4 10%
Student > Ph. D. Student 4 10%
Student > Doctoral Student 2 5%
Other 5 13%
Unknown 6 15%
Readers by discipline Count As %
Computer Science 12 31%
Agricultural and Biological Sciences 10 26%
Biochemistry, Genetics and Molecular Biology 6 15%
Medicine and Dentistry 2 5%
Environmental Science 1 3%
Other 2 5%
Unknown 6 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 June 2019.
All research outputs
#6,799,964
of 22,830,751 outputs
Outputs from Journal of Biomedical Semantics
#128
of 364 outputs
Outputs of similar age
#84,992
of 283,600 outputs
Outputs of similar age from Journal of Biomedical Semantics
#2
of 3 outputs
Altmetric has tracked 22,830,751 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one has gotten more attention than average, scoring higher than 64% 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 283,600 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 69% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.