↓ Skip to main content

Semantic querying of relational data for clinical intelligence: a semantic web services-based approach

Overview of attention for article published in Journal of Biomedical Semantics, March 2013
Altmetric Badge

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 (80th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
5 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
48 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Semantic querying of relational data for clinical intelligence: a semantic web services-based approach
Published in
Journal of Biomedical Semantics, March 2013
DOI 10.1186/2041-1480-4-9
Pubmed ID
Authors

Alexandre Riazanov, Artjom Klein, Arash Shaban-Nejad, Gregory W Rose, Alan J Forster, David L Buckeridge, Christopher JO Baker

Abstract

Clinical Intelligence, as a research and engineering discipline, is dedicated to the development of tools for data analysis for the purposes of clinical research, surveillance, and effective health care management. Self-service ad hoc querying of clinical data is one desirable type of functionality. Since most of the data are currently stored in relational or similar form, ad hoc querying is problematic as it requires specialised technical skills and the knowledge of particular data schemas.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Germany 2 4%
Brazil 2 4%
France 1 2%
Netherlands 1 2%
Spain 1 2%
Portugal 1 2%
Unknown 38 79%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 29%
Student > Master 9 19%
Other 6 13%
Student > Ph. D. Student 5 10%
Professor 4 8%
Other 10 21%
Readers by discipline Count As %
Computer Science 23 48%
Agricultural and Biological Sciences 7 15%
Engineering 3 6%
Medicine and Dentistry 3 6%
Nursing and Health Professions 2 4%
Other 7 15%
Unknown 3 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 17 December 2015.
All research outputs
#3,033,384
of 15,742,614 outputs
Outputs from Journal of Biomedical Semantics
#69
of 345 outputs
Outputs of similar age
#30,190
of 155,065 outputs
Outputs of similar age from Journal of Biomedical Semantics
#3
of 8 outputs
Altmetric has tracked 15,742,614 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 345 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 80% 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 155,065 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 80% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.