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The 3rd DBCLS BioHackathon: improving life science data integration with Semantic Web technologies

Overview of attention for article published in Journal of Biomedical Semantics, January 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#31 of 312)
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

twitter
17 tweeters
googleplus
1 Google+ user

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
90 Mendeley
citeulike
5 CiteULike
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Title
The 3rd DBCLS BioHackathon: improving life science data integration with Semantic Web technologies
Published in
Journal of Biomedical Semantics, January 2013
DOI 10.1186/2041-1480-4-6
Pubmed ID
Authors

Toshiaki Katayama, Mark D Wilkinson, Gos Micklem, Shuichi Kawashima, Atsuko Yamaguchi, Mitsuteru Nakao, Yasunori Yamamoto, Shinobu Okamoto, Kenta Oouchida, Hong-Woo Chun, Jan Aerts, Hammad Afzal, Erick Antezana, Kazuharu Arakawa, Bruno Aranda, Francois Belleau, Jerven Bolleman, Raoul JP Bonnal, Brad Chapman, Peter JA Cock, Tore Eriksson, Paul MK Gordon, Naohisa Goto, Kazuhiro Hayashi, Heiko Horn, Ryosuke Ishiwata, Eli Kaminuma, Arek Kasprzyk, Hideya Kawaji, Nobuhiro Kido, Young Joo Kim, Akira R Kinjo, Fumikazu Konishi, Kyung-Hoon Kwon, Alberto Labarga, Anna-Lena Lamprecht, Yu Lin, Pierre Lindenbaum, Luke McCarthy, Hideyuki Morita, Katsuhiko Murakami, Koji Nagao, Kozo Nishida, Kunihiro Nishimura, Tatsuya Nishizawa, Soichi Ogishima, Keiichiro Ono, Kazuki Oshita, Keun-Joon Park, Pjotr Prins, Taro L Saito, Matthias Samwald, Venkata P Satagopam, Yasumasa Shigemoto, Richard Smith, Andrea Splendiani, Hideaki Sugawara, James Taylor, Rutger A Vos, David Withers, Chisato Yamasaki, Christian M Zmasek, Shoko Kawamoto, Kosaku Okubo, Kiyoshi Asai, Toshihisa Takagi

Abstract

BioHackathon 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and accessibility of life science research data on the Web by bringing together representatives from public databases, analytical tool providers, and cyber-infrastructure researchers to jointly tackle important challenges in the area of in silico biological research.

Twitter Demographics

The data shown below were collected from the profiles of 17 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 4 4%
United States 4 4%
Netherlands 3 3%
United Kingdom 2 2%
Egypt 1 1%
Mexico 1 1%
Canada 1 1%
Brazil 1 1%
Luxembourg 1 1%
Other 0 0%
Unknown 72 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 34%
Student > Ph. D. Student 15 17%
Student > Master 11 12%
Professor > Associate Professor 9 10%
Other 7 8%
Other 15 17%
Unknown 2 2%
Readers by discipline Count As %
Computer Science 33 37%
Agricultural and Biological Sciences 25 28%
Biochemistry, Genetics and Molecular Biology 5 6%
Engineering 5 6%
Social Sciences 3 3%
Other 12 13%
Unknown 7 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 16 January 2014.
All research outputs
#1,003,918
of 12,013,724 outputs
Outputs from Journal of Biomedical Semantics
#31
of 312 outputs
Outputs of similar age
#31,105
of 302,845 outputs
Outputs of similar age from Journal of Biomedical Semantics
#1
of 11 outputs
Altmetric has tracked 12,013,724 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 312 research outputs from this source. They receive a mean Attention Score of 4.4. 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 302,845 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 89% of its contemporaries.
We're also able to compare this research output to 11 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 90% of its contemporaries.