Exploring Time-Series Through Force-Directed Timelines

• Published in: Proceedings / International Conference on Information Visualisation pp. 328 - 335
• Main Authors: Cruz, Antonio, Arrais, Joel P., Machado, Penousal
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2020
• Subjects: Data visualization; Dynamics; Interactive systems; Layout; Time series analysis; Transforms; Visualization
• ISSN: 2375-0138
• DOI: 10.1109/IV51561.2020.00061

Temporal datasets are a product of many scientific disciplines and analyzing the events that they describe may help provide valuable insight into their respective research subjects and help move towards solutions to existing problems. Time-series analysis is still an open problem which prompts new solutions, particularly the discovery of patterns across complex temporal networks. Visualization has proven to be a valuable tool in the analysis of such datasets, with the emergence of new models such as Time Curves, which distorts timelines to position time points based on their similarity, creating visualizations that highlight behavior patterns. In this paper, we further explore time-series functionally and aesthetically by revising the dynamic Time Curves models in CroP, a visualization tool with coordinated multiple views. Firstly, we propose the additional of new visual elements and interactive functions, coordinated with a network visualization to help discover and understand temporal patterns across complex datasets. Secondly, we visually explore time-series through Time Paths, a parameter-based force-directed layout that can dynamically transform the original model to either highlight small data variations or reduce visual noise in favor of overall patterns.