Graph-typed data is ubiquitous, from logistical or transportation networks, through social or correspondence networks, all the way to more abstract biochemical interaction networks. Each such application domain brings with it unique analytical goals, metadata, canonical representations, as well as types of vertices and edges. Routine, automated analyses of such data, while important, can often not fully support the kind of decision-making or data exploration necessary for more complex and/or larger networks. Here, it is through (interactive) visualization that we can support domain experts in their exploratory and (semi-) confirmatory research endeavors. On the one hand, we can build custom, tailor-made interactive, visual dashboards which directly address the needs and support the analysis of our domain expert collaborators. On the other, we can look at more foundational questions about how to best represent graph-typed data or better understand the factors which negatively/positively affect comprehension.


8 Publications found:
Image Bib Reference Publication Type
Henry EhlersORCID iD, Diana MarinORCID iD, Hsiang-Yun WuORCID iD, Renata RaidouORCID iD
Visualizing Group Structure in Compound Graphs: The Current State, Lessons Learned, and Outstanding Opportunities
In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1, HUCAPP and IVAPP, pages 697-708. March 2024.
Conference Paper
Henry EhlersORCID iD, Anaïs Villedieu, Renata RaidouORCID iD, Hsiang-Yun WuORCID iD
Improving readability of static, straight-line graph drawings: A first look at edge crossing resolution through iterative vertex splitting
COMPUTERS & GRAPHICS-UK, 116:448-463, November 2023.
Journal Paper (without talk)
Johannes Sorger, Alessio Arleo, Peter Kán, Wolfgang Knecht, Manuela WaldnerORCID iD
Egocentric Network Exploration for Immersive Analytics
Computer Graphics Forum, 40:241-252, October 2021. [the paper] [video] [online egocentric network]
Journal Paper with Conference Talk
Dynamic BicFlows with nested time series visualization per cluster per set. Manuela WaldnerORCID iD, Daniel Steinböck, Eduard GröllerORCID iD
Interactive exploration of large time-dependent bipartite graphs
Journal of Computer Languages, 57, April 2020. [paper]
Journal Paper (without talk)
Johannes Sorger, Manuela WaldnerORCID iD, Wolfgang Knecht, Alessio Arleo
Immersive Analytics of Large Dynamic Networks via Overview and Detail Navigation
In 2nd International Conference on Artificial Intelligence & Virtual Reality, pages 144-151. December 2019.
[video] [arxiv preprint]
Conference Paper
BiCFlows showing visualization authors and their key words Daniel Steinböck, Eduard GröllerORCID iD, Manuela WaldnerORCID iD
Casual Visual Exploration of Large Bipartite Graphs Using Hierarchical Aggregation and Filtering
In International Symposium on Big Data Visual and Immersive Analytics. October 2018.
Conference Paper
Density-based compact Euler Diagram Michael Mazurek, Manuela WaldnerORCID iD
Visualizing Expanded Query Results
Computer Graphics Forum:87-98, June 2018. [paper] [video]
Journal Paper with Conference Talk
Manuela WaldnerORCID iD, Stefan BrucknerORCID iD, Ivan ViolaORCID iD
Graphical Histories of Information Foraging
In Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational , pages 295-304. October 2014.
Conference Paper
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