Improving discovery in the life sciences using semantic Web technologies and linked data: design principles for life sciences knowledge organization systems

Abstract

The data deluge in biology resulting from wide adoption of highthroughput technologies, coupled with the increasing reliance on web technologies for knowledge organization, sharing and discovery, has created unprecedented opportunities, and challenges, for knowledge engineering in Life Sciences domains. The Semantic Web technologies correspond to a set of standards and best practices for improving data sharing and interoperability on the Web that can greatly advance research in data-driven sciences such as translational medicine and systems biology. Current Semantic Web approaches for addressing those challenges have either relied on automatically formatting biological data sources as RDF (Resource Description Framework), the lingua franca of the Semantic Web, or in the development of bio-{)ntologies. Albeit the significant integrative advances that those represent, wide adoption of Semantic Web technologies by the communities acquiring and modeling experimental biological data has remained suboptimal.(...)