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.

# The first lecture takes place on March 12, 2024.

# The introduction to the mandatory exercise part takes place on March 19, 2024.

# 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 and no longer as 192.053.

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

25 h lecture attendance

25 h follow-up of lecture material and exam preparation

62 h programming project or theory paper work

0,5 h oral exam

------

112,5 h total

### Teaching Mode

Currently the course is planned to be held in presence.

### Lecture Dates

We will have about 15 lecture units taking place in the reserved time slots on Tue or Thu; the actual dates will be announces in the first lecture and here on this page.

Required: solid basic knowledge in algorithms and data structures, particularly graph algorithms (e.g. 186.866)

Optional: advanced knowledge in algorithmics (e.g. 186.814, 192.133, 192.018) and basic knowledge in visualization (e.g. 186.827, 186.833, 188.305)