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The ChEMBL database as linked open data

Overview of attention for article published in Journal of Cheminformatics, May 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#11 of 570)
  • High Attention Score compared to outputs of the same age (97th percentile)

Mentioned by

blogs
3 blogs
twitter
34 tweeters
patent
1 patent
peer_reviews
1 peer review site
googleplus
3 Google+ users

Citations

dimensions_citation
66 Dimensions

Readers on

mendeley
123 Mendeley
citeulike
5 CiteULike
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Title
The ChEMBL database as linked open data
Published in
Journal of Cheminformatics, May 2013
DOI 10.1186/1758-2946-5-23
Pubmed ID
Authors

Egon L Willighagen, Andra Waagmeester, Ola Spjuth, Peter Ansell, Antony J Williams, Valery Tkachenko, Janna Hastings, Bin Chen, David J Wild

Abstract

Making data available as Linked Data using Resource Description Framework (RDF) promotes integration with other web resources. RDF documents can natively link to related data, and others can link back using Uniform Resource Identifiers (URIs). RDF makes the data machine-readable and uses extensible vocabularies for additional information, making it easier to scale up inference and data analysis.

Twitter Demographics

The data shown below were collected from the profiles of 34 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 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Brazil 5 4%
Germany 3 2%
Japan 2 2%
Netherlands 2 2%
United Kingdom 1 <1%
Ecuador 1 <1%
Canada 1 <1%
China 1 <1%
Other 2 2%
Unknown 100 81%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 24%
Researcher 27 22%
Student > Master 16 13%
Professor > Associate Professor 11 9%
Student > Bachelor 10 8%
Other 28 23%
Unknown 2 2%
Readers by discipline Count As %
Computer Science 32 26%
Chemistry 27 22%
Agricultural and Biological Sciences 24 20%
Pharmacology, Toxicology and Pharmaceutical Science 9 7%
Biochemistry, Genetics and Molecular Biology 7 6%
Other 18 15%
Unknown 6 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 49. 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 09 October 2019.
All research outputs
#382,442
of 14,104,168 outputs
Outputs from Journal of Cheminformatics
#11
of 570 outputs
Outputs of similar age
#3,990
of 151,147 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 1 outputs
Altmetric has tracked 14,104,168 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 570 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has done particularly well, scoring higher than 98% 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 151,147 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% 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