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.
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.