Progressive Parameter Space Visualization for Task-Driven SAX Configuration

TY - GEN

T1 - Progressive Parameter Space Visualization for Task-Driven SAX Configuration

AU - Loeschcke, Sebastian Bugge

AU - Hogräfer, Marius

AU - Schulz, Hans-Jörg

PY - 2020

Y1 - 2020

N2 - 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.

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.

UR - https://www.scopus.com/pages/publications/85107786076

U2 - 10.2312/eurova.20201085

DO - 10.2312/eurova.20201085

M3 - Article in proceedings

SP - 43

EP - 47

BT - EuroVA 2020 - EuroVis Workshop on Visual Analytics

A2 - Vrotsou, K.

A2 - Turkay, C.

PB - European Association for Computer Graphics

CY - Geneve

T2 - International EuroVis Workshop on Visual Analytics

Y2 - 25 May 2020 through 25 May 2020

ER -