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Hans-Jörg Schulz

Progressive Parameter Space Visualization for Task-Driven SAX Configuration

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review


As time series datasets are growing in size, data reduction approaches like PAA and SAX are used to keep them storable and analyzable. Yet, finding the right trade-off between data reduction and remaining utility of the data is a challenging problem. So far, it is either done in a user-driven way and offloaded to the analyst, or it is determined in a purely data-driven, automated way. None of these approaches take the analytic task to be performed on the reduced data into account. Hence, we propose a task-driven parametrization of PAA and SAX through a parameter space visualization that shows the difference of progressively running a given analytic computation on the original and on the reduced data for a representative set of data samples. We illustrate our approach in the context of climate analysis on weather data and exoplanet detection on light curve data.
Original languageEnglish
Title of host publicationProceedings of the 11th International EuroVis Workshop on Visual Analytics (EuroVA'20)
EditorsK. Vrotsou, C. Turkay
Number of pages5
Place of publicationGeneve
PublisherEuropean Association for Computer Graphics
Publication year2020
ISBN (Electronic)9783038681168
Publication statusPublished - 2020
EventInternational EuroVis Workshop on Visual Analytics - Online, Norrköping, Sweden
Duration: 25 May 202025 May 2020


ConferenceInternational EuroVis Workshop on Visual Analytics

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ID: 189351320