[Zurück]

A. Scheidl, R. Leite, S. Miksch:
"VisMiFlow: Visual Analytics to Support Citizen Migration Understanding Over Time and Space";
Vortrag: Eurographics Proceedings, Zürich, Switzerland; 14.06.2021 - 18.06.2021; in: "EuroVis 2021 - Short Papers", M. Agus, C. Garth, A. Kerren (Hrg.); The Eurographics Association, Geneve, Switzerland (2021), ISBN: 978-3-03868-143-4; S. 1 - 5.

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Multivariate networks are complex data structures, which are ubiquitous in many application domains. Driven by a real-world
problem, namely the movement behavior of citizens in Vienna, we designed and implemented a Visual Analytics (VA) approach to
ease citizen behavior analyses over time and space. We used a dataset of citizens´ movement behavior to, from, or within Vienna
from 2007 to 2018, provided by Vienna´s city. To tackle the complexity of time, space, and other moving people´s attributes, we
follow a data-user-tasks design approach to support urban developers. We qualitatively evaluated our VA approach with five
experts coming from the field of VA and one non-expert. The evaluation illustrated the importance of task-specific visualization
and interaction techniques to support users´ decision-making and insights. We elaborate on our findings and suggest potential
future works to the field.

Viusal Analytics, Visualization, Time, Space

http://dx.doi.org/10.2312/evs.20211056

https://publik.tuwien.ac.at/files/publik_302493.pdf