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X Demographics
Mendeley readers
Attention Score in Context
| Title |
e!DAL - a framework to store, share and publish research data
|
|---|---|
| Published in |
BMC Bioinformatics, June 2014
|
| DOI | 10.1186/1471-2105-15-214 |
| Pubmed ID | |
| Authors |
Daniel Arend, Matthias Lange, Jinbo Chen, Christian Colmsee, Steffen Flemming, Denny Hecht, Uwe Scholz |
| Abstract |
The life-science community faces a major challenge in handling "big data", highlighting the need for high quality infrastructures capable of sharing and publishing research data. Data preservation, analysis, and publication are the three pillars in the "big data life cycle". The infrastructures currently available for managing and publishing data are often designed to meet domain-specific or project-specific requirements, resulting in the repeated development of proprietary solutions and lower quality data publication and preservation overall. |
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 % |
|---|---|---|
| Mexico | 1 | 25% |
| France | 1 | 25% |
| 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 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 2% |
| Japan | 2 | 2% |
| United Kingdom | 1 | <1% |
| Netherlands | 1 | <1% |
| Canada | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 102 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 24 | 22% |
| Student > Ph. D. Student | 22 | 20% |
| Student > Master | 13 | 12% |
| Librarian | 6 | 5% |
| Student > Postgraduate | 6 | 5% |
| Other | 24 | 22% |
| Unknown | 15 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 34 | 31% |
| Agricultural and Biological Sciences | 24 | 22% |
| Social Sciences | 18 | 16% |
| Biochemistry, Genetics and Molecular Biology | 5 | 5% |
| Engineering | 3 | 3% |
| Other | 6 | 5% |
| Unknown | 20 | 18% |
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 07 December 2018.
All research outputs
#5,439,925
of 22,757,541 outputs
Outputs from BMC Bioinformatics
#1,949
of 7,272 outputs
Outputs of similar age
#50,897
of 228,106 outputs
Outputs of similar age from BMC Bioinformatics
#37
of 152 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,272 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 gotten more attention than average, scoring higher than 72% 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 228,106 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 77% of its contemporaries.
We're also able to compare this research output to 152 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.