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X Demographics
Mendeley readers
Attention Score in Context
| 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. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 50% |
| United Kingdom | 1 | 25% |
| Canada | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 4% |
| Brazil | 2 | 4% |
| United States | 2 | 4% |
| France | 1 | 2% |
| Portugal | 1 | 2% |
| Spain | 1 | 2% |
| Netherlands | 1 | 2% |
| Unknown | 42 | 81% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 29% |
| Student > Master | 9 | 17% |
| Other | 6 | 12% |
| Student > Ph. D. Student | 5 | 10% |
| Student > Doctoral Student | 4 | 8% |
| Other | 10 | 19% |
| Unknown | 3 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 24 | 46% |
| Agricultural and Biological Sciences | 7 | 13% |
| Engineering | 3 | 6% |
| Medicine and Dentistry | 3 | 6% |
| Nursing and Health Professions | 2 | 4% |
| Other | 7 | 13% |
| Unknown | 6 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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
#6,134,040
of 24,885,505 outputs
Outputs from Journal of Biomedical Semantics
#82
of 365 outputs
Outputs of similar age
#47,411
of 200,815 outputs
Outputs of similar age from Journal of Biomedical Semantics
#4
of 5 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 365 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 77% 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 200,815 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 76% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.