| Title |
Toward interoperable bioscience data
|
|---|---|
| Published in |
Nature Genetics, January 2012
|
| DOI | 10.1038/ng.1054 |
| Pubmed ID | |
| Authors |
Susanna-Assunta Sansone, Philippe Rocca-Serra, Dawn Field, Eamonn Maguire, Chris Taylor, Oliver Hofmann, Hong Fang, Steffen Neumann, Weida Tong, Linda Amaral-Zettler, Kimberly Begley, Tim Booth, Lydie Bougueleret, Gully Burns, Brad Chapman, Tim Clark, Lee-Ann Coleman, Jay Copeland, Sudeshna Das, Antoine de Daruvar, Paula de Matos, Ian Dix, Scott Edmunds, Chris T Evelo, Mark J Forster, Pascale Gaudet, Jack Gilbert, Carole Goble, Julian L Griffin, Daniel Jacob, Jos Kleinjans, Lee Harland, Kenneth Haug, Henning Hermjakob, Shannan J Ho Sui, Alain Laederach, Shaoguang Liang, Stephen Marshall, Annette McGrath, Emily Merrill, Dorothy Reilly, Magali Roux, Caroline E Shamu, Catherine A Shang, Christoph Steinbeck, Anne Trefethen, Bryn Williams-Jones, Katherine Wolstencroft, Ioannis Xenarios, Winston Hide |
| Abstract |
To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision. |
X Demographics
The data shown below were collected from the profiles of 49 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 | 10 | 20% |
| Germany | 4 | 8% |
| France | 3 | 6% |
| China | 2 | 4% |
| Hong Kong | 2 | 4% |
| United Kingdom | 2 | 4% |
| Switzerland | 1 | 2% |
| Spain | 1 | 2% |
| Japan | 1 | 2% |
| Other | 4 | 8% |
| Unknown | 19 | 39% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 26 | 53% |
| Scientists | 20 | 41% |
| Science communicators (journalists, bloggers, editors) | 2 | 4% |
| Unknown | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 572 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 36 | 6% |
| United Kingdom | 13 | 2% |
| Germany | 9 | 2% |
| Netherlands | 7 | 1% |
| Canada | 4 | <1% |
| Spain | 4 | <1% |
| Sweden | 4 | <1% |
| France | 3 | <1% |
| Brazil | 3 | <1% |
| Other | 20 | 3% |
| Unknown | 469 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 169 | 30% |
| Student > Ph. D. Student | 122 | 21% |
| Other | 55 | 10% |
| Student > Master | 39 | 7% |
| Professor > Associate Professor | 28 | 5% |
| Other | 95 | 17% |
| Unknown | 64 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 200 | 35% |
| Computer Science | 107 | 19% |
| Biochemistry, Genetics and Molecular Biology | 51 | 9% |
| Medicine and Dentistry | 26 | 5% |
| Chemistry | 18 | 3% |
| Other | 89 | 16% |
| Unknown | 81 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 122. 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 11 August 2023.
All research outputs
#347,269
of 26,017,215 outputs
Outputs from Nature Genetics
#658
of 7,655 outputs
Outputs of similar age
#1,833
of 258,530 outputs
Outputs of similar age from Nature Genetics
#2
of 86 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,655 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.8. This one has done particularly well, scoring higher than 91% 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 258,530 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 86 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.