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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain
|
|---|---|
| Published in |
BMC Bioinformatics, June 2013
|
| DOI | 10.1186/1471-2105-14-191 |
| Pubmed ID | |
| Authors |
Andreas Holzinger, Mario Zupan |
| Abstract |
Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. |
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 | 3 | 75% |
| Unknown | 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 2% |
| Netherlands | 1 | 2% |
| Austria | 1 | 2% |
| Unknown | 43 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 22% |
| Student > Ph. D. Student | 9 | 20% |
| Researcher | 5 | 11% |
| Student > Bachelor | 5 | 11% |
| Professor > Associate Professor | 4 | 9% |
| Other | 11 | 24% |
| Unknown | 2 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 26% |
| Medicine and Dentistry | 10 | 22% |
| Agricultural and Biological Sciences | 5 | 11% |
| Engineering | 4 | 9% |
| Social Sciences | 2 | 4% |
| Other | 10 | 22% |
| Unknown | 3 | 7% |
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 07 February 2014.
All research outputs
#13,185,484
of 23,590,588 outputs
Outputs from BMC Bioinformatics
#3,689
of 7,400 outputs
Outputs of similar age
#99,820
of 198,240 outputs
Outputs of similar age from BMC Bioinformatics
#47
of 97 outputs
Altmetric has tracked 23,590,588 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 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 is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 198,240 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 97 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.