With the internet, massively heterogeneous data sources need to be understood and classified to provide suitable services to users such as content observation, data exploration, e-commerce, or adaptive learning environments. The key to providing these services is applying machine learning (ML) in order to generate structures via clustering and classification. Due to the intricate processes involved in ML, visual tools are needed to support designing and evaluating the ML pipelines. The glyphboard is a comprehensive tool that facilitates the analysis and design of ML-based clustering algorithms using multiple visualization features such as semantic zoom, glyphs, and histograms.


Related Publications

Mandy Keck, Dietrich Kammer, Thomas Gründer, Thomas Thom, Martin Kleinsteuber, Alexander Maasch, Rainer Groh: Towards Glyph-based Visualizations for Big Data Clustering . Proceedings of the 10th International Symposium on Visual Information Communication and Interaction, VINCI '17 ACM, New York, NY, USA, 2017, ISBN: 978-1-4503-5292-5.

Dietrich Kammer, Mandy Keck, Mathias Müller, Thomas Gründer, Rainer Groh: Exploring Big Data Landscapes with Elastic Displays. Mensch und Computer 2017 – Workshopband. Regensburg: Gesellschaft für Informatik e.V., Oldenbourg Verlag, Regensburg, Germany, 2017.

Dietrich Kammer, Mandy Keck, Thomas Gründer, Rainer Groh: Big Data Landscapes: Improving the Visualization of Machine Learning-based Clustering Algorithms. AVI '18 Proceedings of the 2018 International Conference on Advanced Visual Interfaces, (66), ACM, New York, NY, USA, 2018.


This research has been supported by the European Union and the Free State Saxony through the European Regional Development Fund (ERDF). The concept was developed in the project VANDA that has been conducted in cooperation of the Chair of Media Design -Technische Universität in Dresden, deecoob GmbH from Dresden, Mercateo Services GmbH from Leipzig and chemmedia AG from Chemnitz, Germany.