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Towards Data Science Design Patterns

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Advances in Intelligent Data Analysis XXI (IDA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13876))

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Abstract

We propose data flow diagrams to model data science design patterns and demonstrate, using a number of explanatory patterns, how they can be used to explain and document data science best practices, aid data science education, and enable validation of data science processes.

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References

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Acknowledgments

Many other people were involved in earlier discussions around design patterns. We are particularly thankful to Dirk Streeb, Clara Biedermann, and Ahmad Varasteh who were part of the first brainstorming session in May 2022.

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Authors and Affiliations

  1. KNIME, Zurich, Switzerland

    Michael R. Berthold

  2. KNIME, Austin, USA

    Dashiell Brookhart & Satoru Hayasaka

  3. KNIME, Konstanz, Germany

    Schalk Gerber & Maarit Widmann

  4. Konstanz University, Konstanz, Germany

    Michael R. Berthold

Authors
  1. Michael R. Berthold
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  2. Dashiell Brookhart
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  3. Schalk Gerber
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  4. Satoru Hayasaka
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  5. Maarit Widmann
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Corresponding author

Correspondence to Michael R. Berthold .

Editor information

Editors and Affiliations

  1. Université de Caen Normandie, Caen, France

    Bruno Crémilleux

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Sibylle Hess

  3. UCLouvain, Louvain-la-Neuve, Belgium

    Siegfried Nijssen

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Berthold, M.R., Brookhart, D., Gerber, S., Hayasaka, S., Widmann, M. (2023). Towards Data Science Design Patterns. In: Crémilleux, B., Hess, S., Nijssen, S. (eds) Advances in Intelligent Data Analysis XXI. IDA 2023. Lecture Notes in Computer Science, vol 13876. Springer, Cham. https://doi.org/10.1007/978-3-031-30047-9_5

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  • DOI: https://doi.org/10.1007/978-3-031-30047-9_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-30046-2

  • Online ISBN: 978-3-031-30047-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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