Visual Support for Rastering of Unequally Spaced Time Series

Authors: 
Allan Hanbury
Allan Hanbury
Allan Hanbury
Allan Hanbury
Type: 
Speech with proceedings
Proceedings: 
Proceedings of the 10th International Symposium on Visual Information Communication and Interaction
Publisher: 
ACM International Conference Proceeding Series
Pages: 
53 - 57
Year: 
2017
ISBN: 
ISBN: 978-1-4503-5292-5
Abstract: 
Preprocessing is a mandatory first step to make data usable for analysis. While in time series analysis many established methods require data that are sampled in regular time intervals, in practice sensors may sample data at varying interval lengths. Time series rastering is the process of aggregating unequally spaced time series into equal interval lengths. In this paper we discuss critical aspects in the context of time series rastering, and we present a visual design which supports the parametrization of the rastering transformation, communicates the introduced uncertainties and quality issues, and facilitates the comparison of alternative rastering outcomes to achieve optimal results.
TU Focus: 
Computational Science and Engineering
Reference: 

C. Bors, M. Bögl, T. Gschwandtner, S. Miksch:
"Visual Support for Rastering of Unequally Spaced Time Series";
Vortrag: 10th International Symposium on Visual Information Communication and Interaction, Bangkok (eingeladen); 14.08.2017 - 16.08.2017; in: "Proceedings of the 10th International Symposium on Visual Information Communication and Interaction", R. Biuk-Aghai, J. Li, S. Takahashi (Hrg.); ACM International Conference Proceeding Series, ACM New York, NY, USA (2017), ISBN: 978-1-4503-5292-5; S. 53 - 57.

Zusätzliche Informationen

Last changed: 
28.08.2017 09:34:26
Accepted: 
Accepted
TU Id: 
260983
Invited: 
Department Focus: 
Media Informatics and Visual Computing
Author List: 
C. Bors, M. Bögl, T. Gschwandtner, S. Miksch
Abstract German: