Big data poses a great challenge for the life sciences. To
address the heterogeneous variety of life scientific big
data, a series of Semantic Web technologies provides
a promising solution. RDF, SPARQL, triple store
and ontology facilitate the integration and analysis of
heterogeneous multi-disciplinary data. Linked data turns
the Web into a giant global database. Triple store in the
cloud takes full advantage of cloud services to address
the exponential growth of biological data. Although still
in its infancy, the whole scientific community is making
efforts to develop new technologies and tools to ensure
that big data is accessible, analyzable and applicable to
the field of life sciences.