Presented at: 9th Extended Semantic Web Conference (ESWC2012)
The Mathematics Subject Classification (MSC), maintained by the American Mathematical Society’s Mathematical Reviews (MR) and FIZ Karlsruhe’s Zentralblatt für Mathematik (Zbl), is a scheme for classifying publications in mathematics according to their subjects. While it is widely used, its traditional, idiosyncratic conceptualization and representation requires custom implementations of search, query and annotation support. This did not encourage people to create and explore connections of mathematics to subjects of related domains (e.g. science), and it made the scheme hard to maintain. We have reimplemented the current version of MSC2010 as a Linked Open Dataset using SKOS and are turning it into the new MSC authority. This paper explains the motivation, and details our design considerations and how we realized them in the implementation. We present in-the-field use cases and show how to scale existing solutions to take full advantage of the now complete LOD set. We conclude with a roadmap for bootstrapping the presence of mathematical and mathematics-based science, technology, and engineering knowledge on the Web of Data, where it has been noticeably underrepresented so far, starting from MSC/SKOS as a seed. We point out how e-science applications can take advantage of that.
Keywords: Digital Libraries, Linked Open Data, Mathematics, SKOS, Subject Classification Scheme
Resource URI on the dog food server: http://data.semanticweb.org/conference/eswc/2012/paper/research/249
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