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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Improving ontologies by automatic reasoning and evaluation of logical definitions
|
|---|---|
| Published in |
BMC Bioinformatics, October 2011
|
| DOI | 10.1186/1471-2105-12-418 |
| Pubmed ID | |
| Authors |
Sebastian Köhler, Sebastian Bauer, Chris J Mungall, Gabriele Carletti, Cynthia L Smith, Paul Schofield, Georgios V Gkoutos, Peter N Robinson |
| Abstract |
Ontologies are widely used to represent knowledge in biomedicine. Systematic approaches for detecting errors and disagreements are needed for large ontologies with hundreds or thousands of terms and semantic relationships. A recent approach of defining terms using logical definitions is now increasingly being adopted as a method for quality control as well as for facilitating interoperability and data integration. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 5% |
| Brazil | 3 | 4% |
| France | 1 | 1% |
| Germany | 1 | 1% |
| Ukraine | 1 | 1% |
| United Kingdom | 1 | 1% |
| Spain | 1 | 1% |
| Argentina | 1 | 1% |
| Unknown | 65 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 23% |
| Student > Ph. D. Student | 16 | 21% |
| Student > Master | 8 | 10% |
| Student > Bachelor | 6 | 8% |
| Student > Doctoral Student | 6 | 8% |
| Other | 17 | 22% |
| Unknown | 7 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 26 | 33% |
| Agricultural and Biological Sciences | 26 | 33% |
| Engineering | 6 | 8% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Medicine and Dentistry | 3 | 4% |
| Other | 6 | 8% |
| Unknown | 8 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 29 March 2023.
All research outputs
#3,406,315
of 23,504,791 outputs
Outputs from BMC Bioinformatics
#1,237
of 7,400 outputs
Outputs of similar age
#18,719
of 142,031 outputs
Outputs of similar age from BMC Bioinformatics
#19
of 102 outputs
Altmetric has tracked 23,504,791 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 82% 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 142,031 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 85% of its contemporaries.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.