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A metadata-driven approach to data repository design

Overview of attention for article published in Journal of Cheminformatics, January 2017
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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 (89th percentile)

Mentioned by

blogs
1 blog
twitter
13 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
60 Mendeley
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Title
A metadata-driven approach to data repository design
Published in
Journal of Cheminformatics, January 2017
DOI 10.1186/s13321-017-0190-6
Pubmed ID
Authors

Matthew J. Harvey, Andrew McLean, Henry S. Rzepa

Abstract

The design and use of a metadata-driven data repository for research data management is described. Metadata is collected automatically during the submission process whenever possible and is registered with DataCite in accordance with their current metadata schema, in exchange for a persistent digital object identifier. Two examples of data preview are illustrated, including the demonstration of a method for integration with commercial software that confers rich domain-specific data analytics without introducing customisation into the repository itself.

Twitter Demographics

The data shown below were collected from the profiles of 13 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 2 3%
United Kingdom 1 2%
Brazil 1 2%
Unknown 56 93%

Demographic breakdown

Readers by professional status Count As %
Librarian 11 18%
Researcher 10 17%
Student > Master 8 13%
Other 7 12%
Student > Doctoral Student 4 7%
Other 14 23%
Unknown 6 10%
Readers by discipline Count As %
Computer Science 14 23%
Social Sciences 10 17%
Agricultural and Biological Sciences 6 10%
Arts and Humanities 4 7%
Engineering 4 7%
Other 13 22%
Unknown 9 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 19 March 2018.
All research outputs
#1,213,220
of 15,843,093 outputs
Outputs from Journal of Cheminformatics
#118
of 624 outputs
Outputs of similar age
#37,497
of 358,415 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 1 outputs
Altmetric has tracked 15,843,093 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 624 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has done well, scoring higher than 81% 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 358,415 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 89% 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