Generating GoodRelations from BMEcat Catalog Data

BMEcat is a rich XML standard for exchanging product features, prices, images, etc. in B2B settings. If you are a manufacturer of commodities, the best way to .…


If we manage to reduce the barrier for manufacturers, retailers, PIM/SaaS providers to lift their datasheets and/or offers onto the Web of Linked Data, they can easily enhance the visibility of their products and are well prepared for imminent e-commerce tools. In addition, positive network externalities can be exploited because other market participants like Web shops and search engines can take advantage of those data for the provision of more detailed product descriptions in their catalogs and search results, respectively. This, again, will emphasize the product's strengths and increase the demand.



To achieve the goals described above we developed a portable command-line script that basically converts a product catalog available in standard BMEcat XML format to its GoodRelations counterpart. The tool is capable to handle both BMEcat 1.2 and BMEcat 2005 file formats. However, BMEcat 2005 is favorable due to undergone improvements compared to prior versions, for example the introduction of multi-language support. BMEcat2GoodRelations is mainly intended for large or medium-sized enterprises. The only requirement we put on them is to support one variant of the BMEcat format (e.g. obtained from PIM systems), which applies to a high ratio of B2B-capable companies on the market. The resulting output of the tool is intended for a quick and efficient publication of highly structured offers at Web scale.

Project page: <>


Alex Stolz, Bene Rodriguez-Castro and Martin Hepp: Using BMEcat Catalogs as a Lever for Product Master Data on the Semantic Web, in: Proceedings of the 10th Extended Semantic Web Conference (ESWC 2013), May 26-30, 2013, Montpellier, France.


BMEcat2GoodRelations is available under the terms of the GNU Lesser General Public License. The work on this project has been supported by the German Federal Ministry of Research (BMBF) by a grant under the KMU Innovativ program as part of the Intelligent Match project (FKZ 01IS10022B).