SemanticEye: A Semantic Web Application to Rationalize and Enhance Chemical Electronic Publishing

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Abstract
SemanticEye, an ontology with associated tools, improves the classification and open accessibility of chemical information in electronic publishing. In a manner analogous to digital music management, RDF metadata encoded as Adobe XMP can be extracted from a variety of document formats, such as PDF, and managed in an RDF repository called Sesame. Users upload electronic documents containing XMP to a central server by “dropping” them into WebDAV folders. The documents can then be navigated in a Web browser via their metadata, and multiple documents containing identical metadata can then be aggregated. SemanticEye does not actually store any documents. By including unique identifiers within the XMP, such as the DOI, associated documents can be retrieved from the Web with the help of resolving agents. The power of this metadata driven approach is illustrated by including, within the XMP, InChI identifiers for molecular structures and finding relationships between articles based on their InChIs. SemanticEye will become increasingly more comprehensive as usage becomes more widespread. Furthermore, following the Semantic Web architecture enables the reuse of open software tools, provides a “semantically intuitive” alternative to search engines, and fosters a greater sense of trust in Web-based scientific information.