TiMoVA - Visual Analytics for Model Selection in Time Series Analysis

Abstract

Model selection in time series analysis is a challenging task for domain experts in many application areas such as epidemiology, economy, or environmental sciences. The methodology used for this task demands a close combination of human judgement and automated computation. However, statistical software tools do not adequately support this combination through interactive visual interfaces. We propose a Visual Analytics process to guide domain experts in this task. For this purpose, we developed the TiMoVA prototype that implements this process based on user stories and iterative expert feedback on user experience. The prototype is evaluated by usage scenarios with an example dataset from epidemiology and interviews with two external domain experts in statistics. The insights from the experts feedback and the usage scenarios show that TiMoVA can support domain experts in model selection tasks through interactive visual interfaces with short feedback cycles.

 

Video

The video briefly motivates and introduces TiMoVA followed by two usage scenarios, where we apply TiMoVA on an example dataset.

Video introduction with audio narration.

Best viewed with VLC media player.

 

Publications:

 

Screenshot

TiMoVA Overview

TiMoVA Overview

 

Visual Guidance for Seasonal Model Components

TiMoVA Overview

 

Visualizing the Model Transitions

TiMoVA Overview


TiMoVA Overview