TU Wien:Bio-Medical Visualization and Visual Analytics VU (Raidou)
Daten[Bearbeiten | Quelltext bearbeiten]
| Vortragende | Silvia Miksch• Renata Georgia Raidou• Natkamon Tovanich• Mert Eyüp Usul |
|---|---|
| ECTS | 6,0 |
| Letzte Abhaltung | 2025W |
| Sprache | English |
| Mattermost | bio-medical-visualization-and-visual-analytics • Register • Mattermost-Infos |
| Links | tiss:193186 |
Inhalt[Bearbeiten | Quelltext bearbeiten]
The topics in this course are mainly about visualization and visual analytics (as denoted by the title)
Ablauf[Bearbeiten | Quelltext bearbeiten]
The course consists of weekly lectures covering the topics, mainly through examples of scientific works and a general overview over the theoretical concepts.
The practical part is split into individual and group (of 3) exercises. The group project is to be presented at the end.
The course ends with an exam about the lecture content.
Benötigte/Empfehlenswerte Vorkenntnisse[Bearbeiten | Quelltext bearbeiten]
- Python knowledge could be beneficial
- General visualization knowledge (VU Visualisierung)
Vortrag[Bearbeiten | Quelltext bearbeiten]
The lectures were not recorded.
They were held by two different lecturers, each with a different style of presenting.
Übungen[Bearbeiten | Quelltext bearbeiten]
Individual exercises: Different assignments in python and one in cytoscape (a network visualization tool). They are comparatively straight forward and have sensible grading. If you did all the tasks in the assignment you get mostly full points.
Group exercises: The project was about selecting a biomedical dataset, cleaning it and then devising a visualization dashboard to represent the information inside the data.
Prüfung, Benotung[Bearbeiten | Quelltext bearbeiten]
The exam was a multiple choice test (no open questions). It is very hard to prepare for the exam, since the slides provided are insanely long and not very good learning material. The difficulty is ok, however many questions ask about specific research works, where you have to remember the concepts inside a paper given only the name of the author and the year it was published.
Dauer der Zeugnisausstellung[Bearbeiten | Quelltext bearbeiten]
2025W; 27.01.2026; 28.01.2026; 1 day
Zeitaufwand[Bearbeiten | Quelltext bearbeiten]
The individual exercises take about a day each to complete. Take enough time for them, as they seem less work than they actually are.
The group projects are a lot of work, depending also on the dataset. Expect to spend about 30-40 Hours collectively for the whole project.
Unterlagen[Bearbeiten | Quelltext bearbeiten]
As stated in the exams section, the slides are kind of hard to read by themselves, they are not really meant as reading material.
The materials for the exercise parts are extensive and helpful.
Tipps[Bearbeiten | Quelltext bearbeiten]
- Always remember the data-users-tasks triangle
Highlights / Lob[Bearbeiten | Quelltext bearbeiten]
The general organization of the course was very good.
Verbesserungsvorschläge / Kritik[Bearbeiten | Quelltext bearbeiten]
The exam questions were kind of strange and arbitrary. Very specific questions about papers that do not really test the understanding but more the by hard learning of names.