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Building Linked Open Data towards integration of biomedical scientific literature with DBpedia

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

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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7 X users
googleplus
1 Google+ user

Readers on

mendeley
42 Mendeley
citeulike
1 CiteULike
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Title
Building Linked Open Data towards integration of biomedical scientific literature with DBpedia
Published in
Journal of Biomedical Semantics, March 2013
DOI 10.1186/2041-1480-4-8
Pubmed ID
Authors

Yasunori Yamamoto, Atsuko Yamaguchi, Akinori Yonezawa

Abstract

There is a growing need for efficient and integrated access to databases provided by diverse institutions. Using a linked data design pattern allows the diverse data on the Internet to be linked effectively and accessed efficiently by computers. Previously, we developed the Allie database, which stores pairs of abbreviations and long forms (LFs, or expanded forms) used in the life sciences. LFs define the semantics of abbreviations, and Allie provides a Web-based search service for researchers to look up the LF of an unfamiliar abbreviation. This service encounters two problems. First, it does not display each LF's definition, which could help the user to disambiguate and learn the abbreviations more easily. Furthermore, there are too many LFs for us to prepare a full dictionary from scratch. On the other hand, DBpedia has made the contents of Wikipedia available in the Resource Description Framework (RDF), which is expected to contain a significant number of entries corresponding to LFs. Therefore, linking the Allie LFs to DBpedia entries may present a solution to the Allie's problems. This requires a method that is capable of matching large numbers of string pairs within a reasonable period of time because Allie and DBpedia are frequently updated.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 5%
Netherlands 1 2%
Germany 1 2%
Belgium 1 2%
Japan 1 2%
Unknown 36 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 24%
Student > Master 8 19%
Student > Ph. D. Student 7 17%
Student > Doctoral Student 4 10%
Other 3 7%
Other 6 14%
Unknown 4 10%
Readers by discipline Count As %
Computer Science 18 43%
Agricultural and Biological Sciences 9 21%
Medicine and Dentistry 5 12%
Social Sciences 2 5%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 2 5%
Unknown 5 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 10 May 2013.
All research outputs
#5,299,933
of 25,373,627 outputs
Outputs from Journal of Biomedical Semantics
#74
of 368 outputs
Outputs of similar age
#42,968
of 208,876 outputs
Outputs of similar age from Journal of Biomedical Semantics
#4
of 8 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 79th 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 well, scoring higher than 79% 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 208,876 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 79% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.