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Attention Score in Context
Title |
An open annotation ontology for science on web 3.0
|
---|---|
Published in |
Journal of Biomedical Semantics, May 2011
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DOI | 10.1186/2041-1480-2-s2-s4 |
Pubmed ID | |
Authors |
Paolo Ciccarese, Marco Ocana, Leyla Jael Garcia Castro, Sudeshna Das, Tim Clark |
Abstract |
There have been a number of recent efforts (e.g. BioCatalogue, BioMoby) to systematically catalogue bioinformatics tools, services and datasets. These efforts rely on manual curation, making it difficult to cope with the huge influx of various electronic resources that have been provided by the bioinformatics community. We present a text mining approach that utilises the literature to automatically extract descriptions and semantically profile bioinformatics resources to make them available for resource discovery and exploration through semantic networks that contain related resources. |
X Demographics
The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 6% |
United States | 1 | 6% |
Netherlands | 1 | 6% |
Unknown | 15 | 83% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 16 | 89% |
Scientists | 2 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 12 | 7% |
Germany | 4 | 2% |
Spain | 4 | 2% |
United Kingdom | 4 | 2% |
France | 3 | 2% |
Netherlands | 3 | 2% |
Australia | 2 | 1% |
South Africa | 1 | <1% |
Canada | 1 | <1% |
Other | 5 | 3% |
Unknown | 124 | 76% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 37 | 23% |
Student > Ph. D. Student | 25 | 15% |
Student > Master | 23 | 14% |
Student > Bachelor | 15 | 9% |
Professor > Associate Professor | 11 | 7% |
Other | 41 | 25% |
Unknown | 11 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 79 | 48% |
Agricultural and Biological Sciences | 19 | 12% |
Social Sciences | 14 | 9% |
Engineering | 9 | 6% |
Arts and Humanities | 5 | 3% |
Other | 19 | 12% |
Unknown | 18 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 31 October 2016.
All research outputs
#1,744,892
of 23,504,791 outputs
Outputs from Journal of Biomedical Semantics
#15
of 360 outputs
Outputs of similar age
#7,651
of 113,334 outputs
Outputs of similar age from Journal of Biomedical Semantics
#2
of 9 outputs
Altmetric has tracked 23,504,791 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 360 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 96% 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 113,334 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 93% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.