RIKEN MetaDatabase: A Database Platform for Health Care and Life Sciences as a Microcosm of Linked Open Data Cloud

RIKEN MetaDatabase: A Database Platform for Health Care and Life Sciences as a Microcosm of Linked Open Data Cloud

Norio Kobayashi (Advanced Center for Computing and Communication (ACCC), BioResource Center, RIKEN CLST-JEOL Collaboration Center, RIKEN, Japan), Satoshi Kume (RIKEN Center for Life Science Technologies, RIKEN CLST-JEOL Collaboration Center, RIKEN Compass to Healthy Life Research Complex Program, RIKEN, Japan), Kai Lenz (Advanced Center for Computing and Communication (ACCC), RIKEN, Japan) and Hiroshi Masuya (BioResource Center, Advanced Center for Computing and Communication (ACCC), RIKEN, Japan)
Copyright: © 2018 |Pages: 25
DOI: 10.4018/IJSWIS.2018010106
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Abstract

Recently, the number and heterogeneity of life science datasets published on the Web have increased significantly. However, biomedical scientists face numerous serious difficulties finding, using and publishing useful databases. To address these issues, the authors developed a Resource Description Framework-based database platform, called the RIKEN MetaDatabase (http://metadb.riken.jp), that allows biologists to develop, publish and integrate multiple databases easily. The platform manages the metadata of both research and individual data described using standardised vocabularies and ontologies, and has a simple browser-based graphical user interface to view data including tabular and graphical forms. The platform was released in April 2015, and 113 databases, including mammalian, plant, bioresource and image databases, with 26 ontologies have been published using this platform as of January 2017. This paper describes the technical knowledge obtained through the development and operation of the RIKEN MetaDatabase to accelerate life science data distribution.
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2. Requirement Specifications For The Life Science Database Platform

In the development of the RIKEN MetaDatabase, the authors were requested to expand data utilisation while lowering the cost of operation. In order to realise these requests, we recognised that both cloud-based life science databases and data integration functions were necessary. The details will be discussed below.

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