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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Semantic modelling of common data elements for rare disease registries, and a prototype workflow for their deployment over registry data
|
|---|---|
| Published in |
Journal of Biomedical Semantics, March 2022
|
| DOI | 10.1186/s13326-022-00264-6 |
| Pubmed ID | |
| Authors |
Rajaram Kaliyaperumal, Mark D. Wilkinson, Pablo Alarcón Moreno, Nirupama Benis, Ronald Cornet, Bruna dos Santos Vieira, Michel Dumontier, César Henrique Bernabé, Annika Jacobsen, Clémence M. A. Le Cornec, Mario Prieto Godoy, Núria Queralt-Rosinach, Leo J. Schultze Kool, Morris A. Swertz, Philip van Damme, K. Joeri van der Velde, Nawel Lalout, Shuxin Zhang, Marco Roos |
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 % |
|---|---|---|
| Netherlands | 2 | 50% |
| Unknown | 2 | 50% |
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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 22% |
| Student > Master | 4 | 17% |
| Student > Bachelor | 2 | 9% |
| Researcher | 2 | 9% |
| Other | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 9 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 22% |
| Biochemistry, Genetics and Molecular Biology | 3 | 13% |
| Agricultural and Biological Sciences | 2 | 9% |
| Social Sciences | 2 | 9% |
| Medicine and Dentistry | 2 | 9% |
| Other | 1 | 4% |
| Unknown | 8 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 March 2022.
All research outputs
#13,118,605
of 23,460,553 outputs
Outputs from Journal of Biomedical Semantics
#173
of 360 outputs
Outputs of similar age
#170,680
of 443,827 outputs
Outputs of similar age from Journal of Biomedical Semantics
#2
of 2 outputs
Altmetric has tracked 23,460,553 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 360 research outputs from this source. They receive a mean Attention Score of 4.6. This one has gotten more attention than average, scoring higher than 51% 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 443,827 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.