The scientific electronic publishing model has hitherto been an Internet based delivery of electronic articles that are essentially replicas of their paper counterparts. They contain little in the way of added semantics that may better expose the science, assist the peer review process and facilitate follow on collaborations, even though the enabling technologies have been around for some time and are mature. This thesis will examine the evolution of chemical electronic publishing over the past 15 years. It will illustrate, which the help of two frameworks, how publishers should be exploiting technologies to improve the semantics of chemical journal articles, namely their value added features and relationships with other chemical resources on the Web. The first framework is an early exemplar of structured and scalable electronic publishing where a Web content management system and a molecular database are integrated. It employs a test bed of articles from several RSC journals and supporting molecular coordinate and connectivity information. The value of converting 3D molecular expressions in chemical file formats, such as the MOL file, into more generic 3D graphics formats, such as Web3D, is assessed. This exemplar highlights the use of metadata management for bidirectional hyperlink maintenance in electronic publishing. The second framework repurposes this metadata management concept into a Semantic Web application called SemanticEye. SemanticEye demonstrates how relationships between chemical electronic articles and other chemical resources are established. It adapts the successful semantic model used for digital music metadata management by popular applications such as iTunes. Globally unique identifiers enable relationships to be established between articles and other resources on the Web and SemanticEye implements two: the Document Object Identifier (DOI) for articles and the IUPAC International Chemical Identifier (InChI) for molecules. SemanticEye’s potential as a framework for seeding collaborations between researchers, who have hitherto never met, is explored using FOAF, the friend-of-a-friend Semantic Web standard for social networks.