4 results on '"Anna Kokubu"'
Search Results
2. Implementation of linked data in the life sciences at BioHackathon 2011
- Author
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Yukie Akune, Akira R. Kinjo, Toshiaki Katayama, Mizuki Morita, Takaaki Mori, Soichi Ogishima, Yoshinobu Igarashi, Takeo Katoda, Takatomo Fujisawa, Shuichi Kawashima, Mitsuteru Nakao, Anna Kokubu, Yasumasa Shigemoto, Kiyoko F. Aoki-Kinoshita, Shinobu Okamoto, and Yi An Chen
- Subjects
Computer Networks and Communications ,Computer science ,RDF Schema ,Glycobiology ,Health Informatics ,Review ,RDF/XML ,World Wide Web ,PDBj ,SPARQL ,RDF ,computer.programming_language ,Semantic Web ,DDBJ ,Information retrieval ,computer.file_format ,Linked data ,Semantic interoperability ,Computer Science Applications ,Simple Knowledge Organization System ,Data integration ,computer ,Alzheimer’s disease ,Information Systems ,RDF query language ,Faceted search interface - Abstract
Background Linked 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. Results This 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. Conclusions Participants 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.
- Published
- 2015
3. BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains
- Author
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Toshiaki Katayama, Yoshinobu Igarashi, Peter J. A. Cock, Raoul J. P. Bonnal, Yue Wang, Katsuhiko Murakami, Matúš Kalaš, Jan Aerts, Mark Wilkinson, Yoshinobu Kano, Erick Antezana, Yasunori Yamamoto, Yusuke Komiyama, Michel Dumontier, Maori Ito, Shuichi Kawashima, Kiyoko F. Aoki-Kinoshita, Hidemasa Bono, Anna Kokubu, Patricia L. Whetzel, Shujiro Okuda, Shin Kawano, Kazuharu Arakawa, K. Bretonnel Cohen, Toshihisa Takagi, Hiroyo Nishide, Shu Tadaka, Jin-Dong Kim, Pjotr Prins, Andrea Splendiani, Thomas Lütteke, Hiroshi Mori, Naohisa Goto, Soichi Ogishima, Riu Yamashita, Wataru Iwasaki, Francesco Strozzi, Hisashi Narimatsu, Joachim Baran, Yasunobu Okamura, Hidetoshi Itaya, Hiromasa Ono, Alexandru Constantin, Hirokazu Chiba, Philip V. Toukach, Issaku Yamada, Bruno Aranda, Philippe Rocca-Serra, Atsuko Yamaguchi, Shinobu Okamoto, Toyofumi Fujiwara, William S. York, Taehong Kim, Matthew Campbell, Pier Luigi Buttigieg, Yi An Chen, Susanna Sansone, Takatomo Fujisawa, Rutger A. Vos, Mitsuteru Nakao, Masaaki Kotera, Yukie Akune, Sung Ho Shin, Johan Nystrom-Persson, Ikuo Uchiyama, Geraint Duck, Takaaki Mori, Nicki H. Packer, Masahito Umezaki, Robert Hoehndorf, Kazuki Oshita, Rene Ranzinger, Shoko Kawamoto, Chisato Yamasaki, M. Scott Marshall, Takeo Katoda, Yosuke Nishimura, Hilmar Lapp, Jerven Bolleman, Christian M. Zmasek, Hiromichi Sawaki, Camille Laibe, Hongyan Wu, Simon Kocbek, and Mizuki Morita
- Subjects
Computer science ,Semantic interoperability ,integration ,Review ,glycomics ,0302 clinical medicine ,Semantic computing ,collection ,Semantic analytics ,Semantic Web Stack ,Visualization ,0303 health sciences ,SISTA ,EPS-2 ,Ontology ,biology ,Data models ,Computer Science Applications ,normalization ,web services ,BioHackathon ,Data integration ,Information Systems ,Computer Networks and Communications ,Bioinformatics ,Health Informatics ,bioinformatics web services ,Social Semantic Web ,World Wide Web ,03 medical and health sciences ,Databases ,Upper ontology ,metabolic pathways ,gene ,Laboratorium voor Nematologie ,030304 developmental biology ,Semantic Web ,Web services ,genome analysis environment ,business.industry ,software ,Data science ,Semantic grid ,Knowledge representation ,Semantic technology ,sequences ,Data sharing ,Laboratory of Nematology ,business ,030217 neurology & neurosurgery - Abstract
The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed. ispartof: Journal of Biomedical Semantics vol:5 issue:5 pages:1-13 ispartof: location:England status: published
- Published
- 2014
4. Implementation of linked data in the life sciences at BioHackathon 2011.
- Author
-
Aoki-Kinoshita, Kiyoko F., Kinjo, Akira R., Mizuki Morita, Yoshinobu Igarashi, Yi-an Chen, Yasumasa Shigemoto, Takatomo Fujisawa, Yukie Akune, Takeo Katoda, Anna Kokubu, Takaaki Mori, Mitsuteru Nakao, Shuichi Kawashima, Shinobu Okamoto, Toshiaki Katayama, and Soichi Ogishima
- Subjects
LIFE sciences ,LINKED data (Semantic Web) ,BIOINFORMATICS ,RDF (Document markup language) ,QUERY languages (Computer science) - Abstract
Background: Linked 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. Results: This 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. Conclusions: Participants 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. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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