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CMLLite: a design philosophy for CML

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 (84th percentile)

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1 blog
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2 X users

Citations

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9 Dimensions

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26 Mendeley
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Title
CMLLite: a design philosophy for CML
Published in
Journal of Cheminformatics, October 2011
DOI 10.1186/1758-2946-3-39
Pubmed ID
Authors

Joe A Townsend, Peter Murray-Rust

Abstract

CMLLite is a collection of definitions and processes which provide strong and flexible validation for a document in Chemical Markup Language (CML). It consists of an updated CML schema (schema3), conventions specifying rules in both human and machine-understandable forms and a validator available both online and offline to check conformance. This article explores the rationale behind the changes which have been made to the schema, explains how conventions interact and how they are designed, formulated, implemented and tested, and gives an overview of the validation service.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 4%
Germany 1 4%
Canada 1 4%
Unknown 23 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 31%
Other 6 23%
Student > Bachelor 3 12%
Student > Ph. D. Student 2 8%
Student > Master 1 4%
Other 3 12%
Unknown 3 12%
Readers by discipline Count As %
Chemistry 10 38%
Engineering 4 15%
Computer Science 3 12%
Agricultural and Biological Sciences 2 8%
Mathematics 1 4%
Other 3 12%
Unknown 3 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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
#3,652,982
of 22,653,392 outputs
Outputs from Journal of Cheminformatics
#361
of 825 outputs
Outputs of similar age
#20,887
of 136,361 outputs
Outputs of similar age from Journal of Cheminformatics
#17
of 21 outputs
Altmetric has tracked 22,653,392 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 825 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has gotten more attention than average, scoring higher than 56% 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 136,361 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 84% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.