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The semantic architecture of the World-Wide Molecular Matrix (WWMM)

Overview of attention for article published in Journal of Cheminformatics, October 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)

Mentioned by

blogs
1 blog
twitter
1 tweeter

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
30 Mendeley
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Title
The semantic architecture of the World-Wide Molecular Matrix (WWMM)
Published in
Journal of Cheminformatics, October 2011
DOI 10.1186/1758-2946-3-42
Pubmed ID
Authors

Peter Murray-Rust, Sam E Adams, Jim Downing, Joe A Townsend, Yong Zhang

Abstract

The World-Wide Molecular Matrix (WWMM) is a ten year project to create a peer-to-peer (P2P) system for the publication and collection of chemical objects, including over 250, 000 molecules. It has now been instantiated in a number of repositories which include data encoded in Chemical Markup Language (CML) and linked by URIs and RDF. The technical specification and implementation is now complete. We discuss the types of architecture required to implement nodes in the WWMM and consider the social issues involved in adoption.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 3%
United States 1 3%
Germany 1 3%
Canada 1 3%
Unknown 26 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 27%
Student > Ph. D. Student 5 17%
Professor 4 13%
Student > Master 3 10%
Other 3 10%
Other 6 20%
Unknown 1 3%
Readers by discipline Count As %
Chemistry 12 40%
Computer Science 6 20%
Agricultural and Biological Sciences 5 17%
Engineering 2 7%
Environmental Science 2 7%
Other 2 7%
Unknown 1 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 15 November 2011.
All research outputs
#1,808,818
of 12,434,464 outputs
Outputs from Journal of Cheminformatics
#202
of 494 outputs
Outputs of similar age
#14,454
of 96,497 outputs
Outputs of similar age from Journal of Cheminformatics
#11
of 13 outputs
Altmetric has tracked 12,434,464 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 494 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one has gotten more attention than average, scoring higher than 58% 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 96,497 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 85% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.