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Auflistung nach Schlagwort "Data Preparation"

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  • Konferenzbeitrag
    Privacy Aware Processing
    (INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Eleks, Marian; Rebstadt, Jonas; Kortum, Henrik; Thomas, Oliver
    In many machine learning (ML) applications, the provision of data and the training as well as the analysis of machine learning systems are performed by distinct actors, a data owner and a data consumer. To protect sensitive information in these ML-scenarios, privacy aware machine learning (PAML) methods are often applied to the data before sharing. Based on the type of PAML methods used, data understanding and preparation as defined in the CRISP-DM model become more difficult if not impossible. To enable these steps, we propose a method to share a variety of uncritical information with the data consumer who is then able to define the necessary processing steps on a meta-level. These are then applied to the data in the data owners local trusted environment before the PAML-methods whereupon the prepared and protected data is shared.
  • Textdokument
    Report on the Correction of Erroneous Geometry Data in Land Reuse Projects
    (INFORMATIK 2021, 2021) Annanias, Yves; Wahsner, Marc; Scheuermann, Gerik; Wiegreffe, Daniel
    Land Reuse processes are large planning and decision-making processes based on a large amount of geographic data. Therefore, it is essential that this data is as accurate as possible. However, errors can occur during the creation of the data and not all of them are directly noticeable. We report here what errors we have encountered while working with this geographic data, what problems they can cause, and how we have fixed them. Since the correction can be very time-consuming with the enormous amount of data, we have focused on an automatic correction. Not all of this data can be corrected this way, for the rest, we briefly indicate a procedure to support and simplify the manual correction.