Flowstrates++: An Approach to Visualize Multi-Dimensional OD Data

Nicolas Fuchs, Pierre Vanhulst, Raphaël Tuor, Denis Lalanne

2024

Abstract

Is it possible to visualize complex Origin-Destination (OD) data along with relevant spatio-temporal data? In this paper, we tackle this issue by presenting Flowstrates++, an augmented version of Flowstrates which aims to visualize additional time-series datasets linked with OD data. On top of Flowstrates’ heatmap, we designed a second heatmap for spatio-temporal data, synchronized on the temporal axis, as well as other dataset comparison features. Two versions of Flowstrates++ have been designed and implemented: Switch, that displays one external dataset at a time, and Combi (for ”combined”), that displays two external datasets at the same time. We aimed to assess to which extent both variants spur users into making multidimensional findings. To achieve this goal, we evaluated both variants with ninety participants: ten were pilot users in live remote sessions, and eighty were provided by Prolific.co, a crowd-sourcing platform. In a within-groups study, these participants were asked to take relevant annotations about the data on both variants, and to evaluate them through a survey. We then classified the annotations using a framework whose validity was evaluated with an Intercoder Agreement and Fleiss’ Kappa. We found that the Combi variant yielded consistently better results, both in terms of number of produced multidimensional annotations, and in terms of appreciation of the participants. Yet regardless of the variant, our solution allows users to highlight potential correlations between time-series data and temporal OD data.

Paper Citation

in Harvard Style

Fuchs N., Vanhulst P., Tuor R. and Lalanne D. (2024). Flowstrates++: An Approach to Visualize Multi-Dimensional OD Data. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP; ISBN 978-989-758-679-8, SciTePress, pages 625-636. DOI: 10.5220/0012252300003660

in Bibtex Style

@conference{ivapp24,
author={Nicolas Fuchs and Pierre Vanhulst and Raphaël Tuor and Denis Lalanne},
title={Flowstrates++: An Approach to Visualize Multi-Dimensional OD Data},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP},
year={2024},
pages={625-636},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012252300003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP
TI - Flowstrates++: An Approach to Visualize Multi-Dimensional OD Data
SN - 978-989-758-679-8
AU - Fuchs N.
AU - Vanhulst P.
AU - Tuor R.
AU - Lalanne D.
PY - 2024
SP - 625
EP - 636
DO - 10.5220/0012252300003660
PB - SciTePress