The new iris data: modular data generators

  • Authors:
  • Iris Adä;Michael R. Berthold

  • Affiliations:
  • Nycomed Chair for Bioinformatics and Information Mining, Konstanz, Germany;Nycomed Chair for Bioinformatics and Information Mining, Konstanz, Germany

  • Venue:
  • Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
  • Year:
  • 2010

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Abstract

In this paper we introduce a modular, highly flexible, open-source environment for data generation. Using an existing graphical data flow tool, the user can combine various types of modules for numeric and categorical data generators. Additional functionality is added via the data processing framework in which the generator modules are embedded. The resulting data flows can be used to document, deploy, and reuse the resulting data generators. We describe the overall environment and individual modules and demonstrate how they can be used for the generation of a sample, complex customer/product database with corresponding shopping basket data, including various artifacts and outliers.