Open Topics

Supervisor: Daniel Pahr

Not everyone has access to 3D printing, but physical data representations have existed since the beginning of mankind itself! Can we find fabrication methods that are feasible and accessible to a broad audience? What data are they suited for?

Contact: Daniel Pahr

Supervisor: Daniel Pahr

Automation is a chance for physicalization to come to life! Arduino, Raspberry Pi and many more systems offer cheap and feasible ways to create small interactive devices. What kinds of sensors and motors can find applications to engage people with data representations?

Cont…

Supervisor: Daniel Pahr

Elastic materials allow us to control the behavior of normally solid 3D printed objects. Volume data, i.e. scalar fields, as can be transformed into more or less faithful representations of the original object with creative fabrication pipelines. For multidimensional data…

Supervisor: Daniel Pahr

Digital fabrication methods allow us to produce physical objects on demand, but with this process, additional challenges ensue. If we create complex objects they need to be aligned, and overhangs need to be dealt with in creative ways. How can we use a medium like 3D…

Supervisor: Torsten Möller, Laura Koesten, Antonia Saske

Visual literacy, the ability to interpret visual information, can be measured with dedicated tests. Students have completed such a test in the VIS course over the past 6-8 semesters. This project aims to analyze the collected results, examine…

Supervisor: Laura Koesten, Regina Schuster

How do people perceive and interpret climate change visualizations? This project explores how individuals perceive and interpret data visualizations on climate change, based on data collected through an existing online survey. In this survey, participants…

Supervisor: Torsten Möller, Thomas Torsney-Weir

In order to understand simulations, machine learning algorithms, and geometric objects we need to interact with them. This is difficult to perform with something like a mouse which only has 2 axes of movement. Multitouch interfaces let us develop…

Supervisor: Torsten Möller, Laura Koesten

This project investigates the differences between objective and subjective evaluations of data visualizations, focusing on understanding and perceived understanding. You will conduct a study in which participants view a series of data visualizations and…

Supervisors: Torsten Möller, Aleks Doknic, Tomáš Murár 

In this project you will use the Design Study framework to develop an interface to enable art history scholars to better explore the development and usage of scientific methods for the evaluation of art objects. The database contains…

Supervisor: Torsten Möller, Laura Koesten

In forced-choice experiments, a participant is presented with several alternatives in a study in which stimuli are presented. The participant is forced to choose one stimulus over another (or over multiple) and cannot provide a neutral/custom response. 
This…

Supervisor: Torsten Möller

With Anscombe's Quartet [1] it was demonstrated quite figuratively that summary statistics can be very misleading or, at least, hard to interpret. Just recently, this example has become quite playful with the Dinozaur Dozen [2]. However, there are a number of statistical…

Supervisor: Torsten Möller

Chatbots are becoming more prevalent and are actively used by many companies. They offer a voice or text interface to interact with a computer. An example of a chatbot is amazon’s alexa, which can tell the time when asked.
The goal of this project is to find new possible…

Supervisor: Laura Koesten

This project focuses on improving the Self-Assessment Manikin (SAM) by integrating nuanced methods to capture emotional dimensions such as dominance, arousal, and valence. We aim to design a new representation of an emotion scale using:

• Glyph-based representations:…

Supervisor: Torsten Möller, Daniel Pahr, Aleksandar Doknic

Visualizations of multi-dimensional surfaces often involve dimensionality reductions such as low-dimensional projection. Such projections lead to a loss of geometry information and create new axes that are difficult to interpret. Cartesian…

Supervisor: Torsten Möller, Thomas Torsney-Weir

This is primarily a programming project. Slicing methods are a novel way of visualizing multi-dimensional data. However, there is no publicly-available library for R or Python that makes it easy to use these visualization techniques. The goal of these…

Supervisor: Torsten Möller

The challenge is easy to describe: Come up with an algorithm that takes as input N (the number of samples) and D (the dimension) and output a scale factor s and a rotation angle alpha (D-1 angles) that would fit exactly N samples of a Cartesian lattice in the unit box…

Supervisor: Torsten Möller, Thomas Torsney-Weir

Can visualization beat traditional (offline) optimization problems? The goal of this project is to see how well visually guided optimization can compete with traditional optimization algorithms. Students will develop a visualization system to find…

Supervisor: Wilfried Gansterer, Torsten Möller

The main objective is to design and implement a good and efficient way of visually investigating the resilience of deep neural networks against silent data corruption (bit flips) based on given empirical measurements. There are many possible causes for…

Supervisor: Torsten Möller

We have a collection of 100,000 different neural networks from the Tensorflow Playground. The core goal of this project is to create a visual interface to understand some of the basic properties of neural networks. Enabling a user to explore should help answer questions…

Supervisor: Torsten Möller, Christoph Thiem, Judith Staudner

Within the AIROW (artificial intelligence in rowing) project (https://airow.univie.ac.at/) we are collaborating with sports scientists, the Austrian Rowing Federation, and other Data Scientists to collect, curate, and analyse data from…