Selected Student Projects

Here, you can find projects developed by students working with us, for example as part of a Bachelor and Master thesis or during a course work project.

Thesis Projects

Course Projects

2020

  • Visualizing Citation Graphs Mathias Ravn Tversted, Kasper Overgaard Mortensen, Kristoffer Strube Græm

    Our project was about identifying and visualizing the chains of citations that exist between research papers in the field of Computer Science.

  • Visualizing Wildfires in the US Jesper Riemer, David Steinmann

    Our project aims to show the differences between fires depending on what caused the fires. Differences in frequency, size, location and time of year can all be seen in a single interactive visualization. In particular, we focused on comparing human generated fires with lightning generated fires.

  • Spotify Music Visualization Mathias Lønborg Friis, Gustav Andersson Gammelgaard

    Our project was about presenting Spotify's weekly top 200 song charts for a time span of 4 years across 60 countries. By extracting 'audio features' from Spotify's API, we could visualize patterns and trends in music around the world.

  • Road Accidents in the US and the UK Daniel Tøttrup, Stinus Skovgaard Lykke

    This project focuses on getting an informed and better understanding of the traffic data available to the public from the National Highway Traffic Administration and the United Kingdom Department for Transport from 2005-2015. To visualize this data, we decided to implement a dynamic trellis plot do give as much power to the user as possible. The user can select what parameter that will determine the x and y axis of the trellis plot, what vehicle type to highlight, whether the size of an accident should be visualized and what accidents in a year range within 2005-2015 should be visualized. Furthermore, the user can select a group of accidents with box selections and a more detailed bar chart will appear.

  • Interactive Bayesian Network Models Ulrika Klammt

    In my project I developed an interactive visualization of a Bayesian Network model explaining the relation between credit approval likelihood and the applicant’s characteristics. The tool is based on open source web technologies and the statistical developer environment R. I integrated bar plots as detailed plots within the bigger graph structure showing the conditional probabilities.

  • Visualizing Soccer Player Stats Jakob Stricker Nielsen, Morten Visti Leal

    The goal with the project was to make a scouting tool for soccer scouts and management in football clubs that allows them to make their player assessment process faster. The tool uses data from the English Premier League and combines two different plots that enables the user to find the right player.

  • Water Flow in Aarhus Magnus Jensen, Frederik Sams, Nichlas Vingtoft,

    We have worked to visualize complex time series data of water flow in Aarhus, with data curtesy of Aarhus Vand. We have made an application there allows Aarhus Vand to explore and combine patterns of water usage measured from different locations around Aarhus. We have used Horizon Graphs to visualize flow, and applied interactive methods to compare usage and find patterns.

2019

  • Expanding your portfolio with Sneakers Casper Hogenboom

    Are you looking for an alternative way to enrich your portfolio? Step into the world of the sneaker business, and plan out your technical strategies. In this project, a dataset from the website StockX is explored to give an insight into what time it is best to buy or sell.

  • High-Dimensionality Data Exploration to Reveal Features Underlying Disease Skyler Roth

    Some disease predictors are inaccurate in distinguishing a pre-disease population. Unsupervised learning allows for clustering of medical data without need of a disease predictor. This tool allows for analysis of high dimensional patient data and exploration of patient grouping into diseased, at-risk, and healthy populations as derived from unsupervised methods. These methods can be altered quickly, providing rapid analysis of the clusters and insight into novel biomarkers underlying disease.

  • Facebook Messages Steffen Strunge Mathiesen

    Facebook Messenger makes it easy to send and receive messages between your friends, and you can create group chats to keep in touch with many people at once. But Facebook does not provide a way of searching for patterns or trends in your messaging data. In this project, I create a visualisation of my own Facebook Messenger data that allows for overview and details on demand by filtering the data set and finding trends based on contact, timeframe, conversation type, month, weekday or hour.

  • Language Correlation in Open Source Jesper Brink Andersen, Mikkel Bak Bertelsen, Mikkel Hørby Schou

    This visualization helps to explore how different languages are connected to each other on Github. This is done by having a matrix representation showing the deviation from the expected value, and a chord diagram visualising the amount of connections between each language. We make a connection between language A and language B, if a user on Github has a repo with A and another repo with B.

  • What's going on in German Government? Niklas Müller, Nils Simon

    This project aims to shed light into the matters of the German Bundestag by presenting the voting outcome for each parliament session since 2007 in a visually analyzable way. It allows comparing the voting behavior of the parties against each other and over time.

  • Displacing Germany: A Look at Trans-Atlantic Slave Trade Harshit Mahapatra, Tomas Mota, Maximilian Scheid

    Around 10 million people were abducted from Africa and shipped to the Americas between the years 1510 to 1860 as part of the transatlantic slave trade. This amounted to one percent of the world's total population in 1800. Today, the same would be analogous to displacing entire country of Germany. Our project is an attempt to visualise the involved voyages both on an aggregate and detailed level to shed some light on the human element of the egregious events of the past.