Bringing Chemical Data onto the Semantic Web

Present chemical data storage methodologies place many restrictions on the use of the stored data. The
absence of sufficient high-quality metadata prevents intelligent computer access to the data without human
intervention. This creates barriers to the automation of data mining in activities such as quantitative structure−activity relationship modelling. The application of Semantic Web technologies to chemical data is shown to
reduce these limitations. The use of unique identifiers and relationships (represented as uniform resource
identifiers, URIs, and resource description framework, RDF) held in a triplestore provides for greater detail
and flexibility in the sharing and storage of molecular structures and properties.