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Pep Up Your Time Machine: Recommendations for the Design of Information Visualizations of Time-Dependent Data

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Handbook of Human Centric Visualization

Abstract

Representing time-dependent data plays an important role in information visualization. Time presents specific challenges for the representation of data because time is a complex and highly abstract concept. Basically, there are two ways to support reasoning about time: time can be represented by space, and time can also be represented by time (animation). From the point of view of the users, both forms of representation have their strengths and weaknesses which we will illustrate in this chapter. In recent years, a large number of visualizations has been developed to solve the problem of representing time-dependent data. Nevertheless, it is still not clear which types of visualizations support the cognitive processes of the users. It is necessary to investigate the interactions of real users with visualizations to clarify this issue. The following chapter will give an overview of empirical evaluations and recommendations for the design of visualizations for time-dependent data.

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Acknowledgements

This work is conducted in the context of the CVAST – Centre of Visual Analytics Science and Technology project. It is funded by the Austrian Federal Ministry of Economy, Family and Youth in the exceptional Laura Bassi Centres of Excellence initiative and also within the EXPAND – EXploratory Visualization of PAtent Network Dynamics project, supported by the program FIT-IT/BMVIT of the Federal Ministry of Transport, Innovation and Technology, Austria (Project number: 2883373).

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  1. Vienna University of Technology, Institute for Design and Assessment of Technology, Vienna, Austria

    Simone Kriglstein & Margit Pohl

  2. Danube University Krems, Krems an der Donau, Austria

    Michael Smuc

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    Weidong Huang

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Kriglstein, S., Pohl, M., Smuc, M. (2014). Pep Up Your Time Machine: Recommendations for the Design of Information Visualizations of Time-Dependent Data. In: Huang, W. (eds) Handbook of Human Centric Visualization. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7485-2_8

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