Graph drawing is concerned with the geometric representation of graphs in the plane and constitutes the algorithmic core of network visualization. Graph drawing is motivated by applications where it is crucial to visually analyze, explore, and interact with relational datasets. Examples of such application areas include data science, social sciences, Web computing, information systems, biology, geography, business intelligence, information security and software engineering. The research area graph drawing combines aspects of algorithmics, graph theory, computational geometry, and visualization.
In this course we define common aesthetic quality criteria and layout styles in graph drawing. Subsequently, we study the corresponding optimization problems from a formal, algorithmic perspective. We cover some of the most fundamental graph drawing algorithms, ranging from general-purpose algorithms to specific algorithms for certain graph classes (e.g., trees and planar graphs). The algorithms use known algorithm design principles such as divide-and-conquer, incremental constructions, and network flow models. The course covers both practical and theoretical aspects of graph drawing.
Due to an increase of the ECTS points the VU Graph Drawing Algorithms will take place with the new TISS ID 192.141 from 2023S.
In addition to the weekly lectures there is an accompanying exercise part, in which students can choose to either work on a practical programming project in a group of 2-3 students and present the results at the end of the course (incl. the option to participate in the annual graph drawing contest), or to read and understand a recent theoretical research paper and present it to the class at the end of the term.
ECTS-Breakdown
20 h lecture attendance
24 h follow-up of lecture material and exam preparation
30 h programming project or preparation of theory paper presentation
1 h oral exam
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75 h total
Teaching Mode
Currently the course is planned to be held in presence. In case the current situation ot the COVID regulations of TU Wien prohibit this, we will switch to distance teaching. Video recordings of previous terms are available, but course material may change. The exam will cover the course material of the current term.
Required: solid basic knowledge in algorithms and data structures, particularly graph algorithms (e.g. 186.813, 186.815, 186.866)
Optional: advanced knowledge in algorithmics (e.g. 186.814, 186.122) and basic knowledge in visualization (e.g. 186.827, 186.833, 188.305)