Experimenting and improving perception of 3D rotation-based transitions between 2D visualizations
INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part IV
Utilisation d'outils de visual data mining pour l'exploration d'un ensemble de règles d'association
23rd French Speaking Conference on Human-Computer Interaction
Graph Bundling by Kernel Density Estimation
Computer Graphics Forum
Visual comparison for information visualization
Information Visualization - Special issue on State of the Field and New Research Directions
TraceViz: "brushing" for location based services
MobileHCI '12 Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services
Evaluation of the visibility of vessel movement features in trajectory visualizations
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Proceedings of the 30th European Conference on Cognitive Ergonomics
Transmogrification: causal manipulation of visualizations
Proceedings of the 26th annual ACM symposium on User interface software and technology
Assessing and improving 3D rotation transition in dense visualizations
BCS-HCI '13 Proceedings of the 27th International BCS Human Computer Interaction Conference
Visualizing interchange patterns in massive movement data
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
TrajectoryLenses - a set-based filtering and exploration technique for long-term trajectory data
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
Hi-index | 0.00 |
When displaying thousands of aircraft trajectories on a screen, the visualization is spoiled by a tangle of trails. The visual analysis is therefore difficult, especially if a specific class of trajectories in an erroneous dataset has to be studied. We designed FromDaDy, a trajectory visualization tool that tackles the difficulties of exploring the visualization of multiple trails. This multidimensional data exploration is based on scatterplots, brushing, pick and drop, juxtaposed views and rapid visual design. Users can organize the workspace composed of multiple juxtaposed views. They can define the visual configuration of the views by connecting data dimensions from the dataset to Bertin’s visual variables. They can then brush trajectories, and with a pick and drop operation they can spread the brushed information across views. They can then repeat these interactions, until they extract a set of relevant data, thus formulating complex queries. Through two real-world scenarios, we show how FromDaDy supports iterative queries and the extraction of trajectories in a dataset that contains up to 5 million data.