Kai Lenz

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Database integration of a wide variety of life-science data is an important issue for comprehensive data analysis. Since Semantic Web technologies, such as Resource Description Framework (RDF), are expected to provide efficient data integration technologies, many life-science databases are published in RDF with SPARQL Protocol and RDF Query Language(More)
We introduce a database platform called 'RIKEN Meta Data-base' that provides information on RIKEN's various life-science databases to help researchers around the world make full use of RIKEN's research results. Since RIKEN procures various and large life-sciences datasets through the genomes and phenomes of various species, including datasets for sequence(More)
" Bio-resources " , commonly used biological materials for experimental studies such as mouse strains, cell lines and microbe culture collections are crucial fundamentals to provide reproducibility and reliability of data in life science. To provide advanced infrastructure of life science, wider-dissemination, quality control and standardization of(More)
The Life Science Database Archive (LSDB Archive, https://dbarchive.biosciencedbc.jp/) is a service to collect, preserve and provide databases generated by life-science researchers in Japan. As of September 2015, the LSDB Archive includes 103 databases and all the databases can be downloadable with appropriate licenses and metadata. Although a simple keyword(More)
Metadata publication in accordance with the semantic web as a database is a trend for providing and integrating various life-science data. These metadata are published as SPARQL endpoints, a standard-ised API for RDF datasets. As life-science data are very widely diverse and described using various ontologies and data classes, writing an efficient SPARQL(More)
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