Project: Continuous-time graph drawing using WebGL
Description
Typical dynamic network layout technique assume the time axis to be discrete, in order to simplify the problem and adapt techniques and technologies from the static graph drawing literature. This however has several drawbacks. If the network presents natural timeslices this technique works remarkably well: if we have a network of tennis players, and every match happens on every Thursday, we can easily split time and group events in a weekly manner without loss of precision. But what if, instead, you have a network of WhatsApp calls, that can happen at any point in time?
This topic is also known as Event-based Graph Drawing. In this context, the graph dynamics are represented as events with time durations for nodes, edges, and their attributes. Recent research (see Recommended Readings below) focused on computing a layout for these networks that would leverage these characteristics of the data, and in terms of layout quality there has been a significant improvement. However, these methods are slower and more complex, making it more difficult to apply these methods to large graphs.
In this project, the candidate investigates alternative implementations of the event-based graph layout family of algorithms, evaluating the existing approaches and building over them a drawing framework using new technologies that leverage the computing power of modern video hardware.
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Recommended Readings:
Holme, Petter, and Jari Saramäki. "Temporal networks." Physics reports 519.3 (2012): 97-125.
Simonetto, Paolo, Daniel Archambault, and Stephen Kobourov. "Event-based dynamic graph visualisation." IEEE Transactions on Visualization and Computer Graphics 26.7 (2018): 2373-2386. Arleo, Alessio, Silvia Miksch, and Daniel Archambault. "Event‐based dynamic graph drawing without the agonizing pain." Computer Graphics Forum. Vol. 41. No. 6. 2022.
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Details
- Supervisor
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Alessio Arleo
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