TY - CONF TI - Progressive Parameter Space Visualization for Task-Driven SAX Configuration AU - Loeschcke, Sebastian Bugge AU - Hogräfer, Marius AU - Schulz, Hans-Jörg T2 - 11th International EuroVis Workshop on Visual Analytics (EuroVA) A2 - Turkay, Cagatay A2 - Vrotsou, Katerina AB - 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. C3 - Proceedings of the 11th International EuroVis Workshop on Visual Analytics (EuroVA'20) DA - 2020/// PY - 2020 DO - 10.2312/eurova.20201085 SP - 43 EP - 47 PB - Eurographics Association SN - 978-3-03868-116-8 ER -