title: Semantic Web technologies for the big data in life sciences.
abstract: The life sciences field is entering an era of big data with the breakthroughs of science and technology. More and more big data-related projects and activities are being performed in the world. Life sciences data generated by new technologies are continuing to grow in not only size but also variety and complexity, with great speed. To ensure that big data has a major influence in the life sciences, comprehensive data analysis across multiple data sources and even across disciplines is indispensable. The increasing volume of data and the heterogeneous, complex varieties of data are two principal issues mainly discussed in life science informatics. The ever-evolving next-generation Web, characterized as the Semantic Web, is an extension of the current Web, aiming to provide information for not only humans but also computers to semantically process large-scale data. The paper presents a survey of big data in life sciences, big data related projects and Semantic Web technologies. The paper introduces the main Semantic Web technologies and their current situation, and provides a detailed analysis of how Semantic Web technologies address the heterogeneous variety of life sciences big data. The paper helps to understand the role of Semantic Web technologies in the big data era and how they provide a promising solution for the big data in life sciences.
authors.affiliation: Database Center for Life Science, Research Organization of Information and Systems.
authors.forename: Hongyan
authors.initials: H
authors.lastname: Wu
authors.forename: Atsuko
authors.initials: A
authors.lastname: Yamaguchi
mesh_terms: D001690:Biological Science Disciplines; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D033181:Information Dissemination / Q000379:methods*; D016247:Information Storage and Retrieval; D020407:Internet; D012660:Semantics