Using BMEcat Catalogs as a Lever for Product Master Data on the Semantic Web

  • Alex Stolz
  • Benedicto Rodriguez-Castro
  • Martin Hepp
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7882)


To date, the automatic exchange of product information between business partners in a value chain is typically done using Business-to-Business (B2B) catalog standards such as EDIFACT, cXML, or BMEcat. At the same time, the Web of Data, in particular the GoodRelations vocabulary, offers the necessary means to publish highly-structured product data in a machine-readable format. The advantage of the publication of rich product descriptions can be manifold, including better integration and exchange of information between Web applications, high-quality data along the various stages of the value chain, or the opportunity to support more precise and more effective searches. In this paper, we (1) stress the importance of rich product master data for e-commerce on the Semantic Web, and (2) present a tool to convert BMEcat XML data sources into an RDF-based data model anchored in the GoodRelations vocabulary. The benefits of our proposal are tested using product data collected from a set of 2500+ online retailers of varying sizes and domains.


Product Model Unit Code Online Shop Online Retailer Product Instance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alex Stolz
    • 1
  • Benedicto Rodriguez-Castro
    • 1
  • Martin Hepp
    • 1
  1. 1.E-Business and Web Science Research GroupUniversität der Bundeswehr MünchenNeubibergGermany

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