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PAV ontology: provenance, authoring and versioning

Overview of attention for article published in Journal of Biomedical Semantics, January 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#3 of 315)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
3 blogs
twitter
13 tweeters
wikipedia
2 Wikipedia pages
googleplus
2 Google+ users

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
77 Mendeley
citeulike
3 CiteULike
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Title
PAV ontology: provenance, authoring and versioning
Published in
Journal of Biomedical Semantics, January 2013
DOI 10.1186/2041-1480-4-37
Pubmed ID
Authors

Paolo Ciccarese, Stian Soiland-Reyes, Khalid Belhajjame, Alasdair JG Gray, Carole Goble, Tim Clark

Abstract

Provenance is a critical ingredient for establishing trust of published scientific content. This is true whether we are considering a data set, a computational workflow, a peer-reviewed publication or a simple scientific claim with supportive evidence. Existing vocabularies such as Dublin Core Terms (DC Terms) and the W3C Provenance Ontology (PROV-O) are domain-independent and general-purpose and they allow and encourage for extensions to cover more specific needs. In particular, to track authoring and versioning information of web resources, PROV-O provides a basic methodology but not any specific classes and properties for identifying or distinguishing between the various roles assumed by agents manipulating digital artifacts, such as author, contributor and curator.

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 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 3%
Germany 2 3%
Netherlands 2 3%
United Kingdom 2 3%
Poland 1 1%
Mexico 1 1%
Japan 1 1%
United States 1 1%
Austria 1 1%
Other 2 3%
Unknown 62 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 27%
Student > Master 12 16%
Student > Ph. D. Student 12 16%
Student > Bachelor 10 13%
Professor > Associate Professor 5 6%
Other 17 22%
Readers by discipline Count As %
Computer Science 40 52%
Agricultural and Biological Sciences 16 21%
Unspecified 6 8%
Engineering 5 6%
Social Sciences 3 4%
Other 7 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 28 January 2019.
All research outputs
#443,668
of 12,460,170 outputs
Outputs from Journal of Biomedical Semantics
#3
of 315 outputs
Outputs of similar age
#8,723
of 230,582 outputs
Outputs of similar age from Journal of Biomedical Semantics
#1
of 30 outputs
Altmetric has tracked 12,460,170 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 315 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done particularly well, scoring higher than 99% 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 230,582 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 96% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.