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Attention Score in Context
| Title |
The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows
|
|---|---|
| Published in |
Journal of Biomedical Semantics, August 2010
|
| DOI | 10.1186/2041-1480-1-8 |
| Pubmed ID | |
| Authors |
Toshiaki Katayama, Kazuharu Arakawa, Mitsuteru Nakao, Keiichiro Ono, Kiyoko F Aoki-Kinoshita, Yasunori Yamamoto, Atsuko Yamaguchi, Shuichi Kawashima, Hong-Woo Chun, Jan Aerts, Bruno Aranda, Lord Hendrix Barboza, Raoul JP Bonnal, Richard Bruskiewich, Jan C Bryne, José M Fernández, Akira Funahashi, Paul MK Gordon, Naohisa Goto, Andreas Groscurth, Alex Gutteridge, Richard Holland, Yoshinobu Kano, Edward A Kawas, Arnaud Kerhornou, Eri Kibukawa, Akira R Kinjo, Michael Kuhn, Hilmar Lapp, Heikki Lehvaslaiho, Hiroyuki Nakamura, Yasukazu Nakamura, Tatsuya Nishizawa, Chikashi Nobata, Tamotsu Noguchi, Thomas M Oinn, Shinobu Okamoto, Stuart Owen, Evangelos Pafilis, Matthew Pocock, Pjotr Prins, René Ranzinger, Florian Reisinger, Lukasz Salwinski, Mark Schreiber, Martin Senger, Yasumasa Shigemoto, Daron M Standley, Hideaki Sugawara, Toshiyuki Tashiro, Oswaldo Trelles, Rutger A Vos, Mark D Wilkinson, William York, Christian M Zmasek, Kiyoshi Asai, Toshihisa Takagi |
| Abstract |
Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However, various incompatibilities among database resources and analysis services make it difficult to connect and integrate these into interoperable workflows. To resolve this situation, we invited domain specialists from web service providers, client software developers, Open Bio* projects, the BioMoby project and researchers of emerging areas where a standard exchange data format is not well established, for an intensive collaboration entitled the BioHackathon 2008. The meeting was hosted by the Database Center for Life Science (DBCLS) and Computational Biology Research Center (CBRC) and was held in Tokyo from February 11th to 15th, 2008. In this report we highlight the work accomplished and the common issues arisen from this event, including the standardization of data exchange formats and services in the emerging fields of glycoinformatics, biological interaction networks, text mining, and phyloinformatics. In addition, common shared object development based on BioSQL, as well as technical challenges in large data management, asynchronous services, and security are discussed. Consequently, we improved interoperability of web services in several fields, however, further cooperation among major database centers and continued collaborative efforts between service providers and software developers are still necessary for an effective advance in bioinformatics web service technologies. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 10 | 10% |
| Japan | 8 | 8% |
| United Kingdom | 3 | 3% |
| Spain | 2 | 2% |
| Germany | 2 | 2% |
| Indonesia | 1 | 1% |
| Sweden | 1 | 1% |
| Australia | 1 | 1% |
| Norway | 1 | 1% |
| Other | 4 | 4% |
| Unknown | 66 | 67% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 34 | 34% |
| Student > Ph. D. Student | 13 | 13% |
| Student > Master | 11 | 11% |
| Professor > Associate Professor | 10 | 10% |
| Other | 8 | 8% |
| Other | 14 | 14% |
| Unknown | 9 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 36 | 36% |
| Computer Science | 27 | 27% |
| Biochemistry, Genetics and Molecular Biology | 10 | 10% |
| Medicine and Dentistry | 10 | 10% |
| Engineering | 4 | 4% |
| Other | 1 | 1% |
| Unknown | 11 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 25 March 2016.
All research outputs
#2,645,215
of 25,371,288 outputs
Outputs from Journal of Biomedical Semantics
#34
of 368 outputs
Outputs of similar age
#9,831
of 104,253 outputs
Outputs of similar age from Journal of Biomedical Semantics
#1
of 1 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 90% 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 104,253 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 90% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them