Evidence map›Paper›PMID 25973165›Full record

ReviewJournal of biomedical semantics2015

Implementation of linked data in the life sciences at BioHackathon 2011.

Kiyoko F Aoki-Kinoshita, Akira R Kinjo, Mizuki Morita, Yoshinobu Igarashi, Yi-An Chen, Yasumasa Shigemoto, Takatomo Fujisawa, Yukie Akune, Takeo Katoda, Anna Kokubu and 6 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of biomedical semantics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. DNA Data Bank of Japan: 30th anniversary.Nucleic acids research · 2018
    Article
  8. DNA Data Bank of Japan.Nucleic acids research · 2017
    Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Kiyoko F Aoki-KinoshitaDepartment of Bioinformatics, Faculty of Engineering, Soka University, 1-236 Tangi-machi, Hachioji, Tokyo, 192-8577 Japan.
Akira R KinjoLaboratory of Protein Informatics, Laboratory of Protein Databases, and Protein Data Bank Japan, Research Center for Structural and Functional Proteomics, Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871 Japan.
Mizuki MoritaCenter for Knowledge Structuring, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.
Yoshinobu IgarashiNational Institute of Biomedical Innovation, 7-6-8 Asagi Saito, Ibaraki-City, Osaka, 567-0085 Japan.
Yi-An ChenNational Institute of Biomedical Innovation, 7-6-8 Asagi Saito, Ibaraki-City, Osaka, 567-0085 Japan.
Yasumasa ShigemotoDNA Data Bank of Japan, National Institute of Genetics, Yata 1111, Mishima, Shizuoka, 411-8540 Japan.
Takatomo FujisawaDNA Data Bank of Japan, National Institute of Genetics, Yata 1111, Mishima, Shizuoka, 411-8540 Japan.
Yukie AkuneDepartment of Bioinformatics, Faculty of Engineering, Soka University, 1-236 Tangi-machi, Hachioji, Tokyo, 192-8577 Japan.
Takeo KatodaDepartment of Bioinformatics, Faculty of Engineering, Soka University, 1-236 Tangi-machi, Hachioji, Tokyo, 192-8577 Japan.
Anna KokubuDepartment of Bioinformatics, Faculty of Engineering, Soka University, 1-236 Tangi-machi, Hachioji, Tokyo, 192-8577 Japan.
Takaaki MoriDepartment of Bioinformatics, Faculty of Engineering, Soka University, 1-236 Tangi-machi, Hachioji, Tokyo, 192-8577 Japan.
Mitsuteru NakaoNext Generation Systems Core Function Unit, Eisai Product Creation Systems, Eisai Co., Ltd, Tsukuba, Ibaraki, Japan.
Shuichi KawashimaDatabase Center for Life Science, Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa-shi, Chiba, 277-0871 Japan.
Shinobu OkamotoDatabase Center for Life Science, Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa-shi, Chiba, 277-0871 Japan.
Toshiaki KatayamaDatabase Center for Life Science, Research Organization of Information and Systems, 178-4-4 Wakashiba, Kashiwa-shi, Chiba, 277-0871 Japan.
Soichi OgishimaDepartment of Bioclinical informatics, Tohoku Medical Megabank Organization, Tohoku University, Seiryo-cho 4-1, Aoba-ku, Sendai-shi Miyagi, 980-8575 Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLinked Data has gained some attention recently in the life sciences as an effective way to provide and share data. As a part of the Semantic Web, data are linked so that a person or machine can explore the web of data. Resource Description Framework (RDF) is the standard means of implementing Linked Data. In the process of generating RDF data, not only are data simply linked to one another, the links themselves are characterized by ontologies, thereby allowing the types of links to be distinguished. Although there is a high labor cost to define an ontology for data providers, the merit lies in the higher level of interoperability with data analysis and visualization software. This increase in interoperability facilitates the multi-faceted retrieval of data, and the appropriate data can be quickly extracted and visualized. Such retrieval is usually performed using the SPARQL (SPARQL Protocol and RDF Query Language) query language, which is used to query RDF data stores. For the database provider, such interoperability will surely lead to an increase in the number of users.

resultsThis manuscript describes the experiences and discussions shared among participants of the week-long BioHackathon 2011 who went through the development of RDF representations of their own data and developed specific RDF and SPARQL use cases. Advice regarding considerations to take when developing RDF representations of their data are provided for bioinformaticians considering making data available and interoperable.

conclusionsParticipants of the BioHackathon 2011 were able to produce RDF representations of their data and gain a better understanding of the requirements for producing such data in a period of just five days. We summarize the work accomplished with the hope that it will be useful for researchers involved in developing laboratory databases or data analysis, and those who are considering such technologies as RDF and Linked Data.

Indexed as

Alzheimer’s diseaseData integrationDDBJFaceted search interfaceGlycobiologyPDBjSemantic Web

Identifiers

PMID25973165
PMCPMC4429360

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.