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Visualization of data

As the volume and complexity of data increases it becomes very difficult for users to effectively explore large-scale datasets. A possible solution for this problem is visualization. Visualization is a graphical representation of data. Its main purpose is to convey information clearly and efficiently through graphical means. Visualizing large amounts of data allows us to see patterns that may otherwise remain hidden and it allows us also to quickly grasp and process large amounts of data that would otherwise require a lot of time to study. Possible faults in the underlying data may be spotted easier.

Increasingly important aspects of visualization are dynamics of representation and interactivity. The parameters of visualization can be changed on demand and particular small scale features of the visualization can be explored in more detail. On this basis we can form new queries on the datasets.

Visualizations are used in many fields (e.g. medical visualizations, education, crime mapping, geovisualizations, data-mining, financial data analysis and market studies etc.) and employ different visualization techniques (e.g. charts, graphs, cluster diagrams, volume rendering etc.), but just any arbitrary visualization might not be useful and inappropriate visualizations may even lead to flawed conclusions. In some cases a lot of effort is put into a visualization that has no added value.


Virtual Environment for Interactive Network Analysis

In recent years networks became extremely popular since they represent a powerful tool for representation and analysis of complex systems, i.e., systems that consist of a large number of elements and dynamic interactions among them. One of the key problems when dealing with large networks is how to represent them in an intuitive way that is simplistic on one hand, and, on the other hand, facilitates efficient network investigation and analysis. We currently work on Virtual Environment for Interactive Network Analysis, which puts the user in an augmented reality 3D network and allows him to browse, explore and familiarize with the network. Besides efficient navigation with gestures, the system will provide different methods for analyzing network properties and dynamics, and support semantic enrichment from arbitrary structured source.

Visualization of Music

One of the fields where visualization can be used to enhance comprehension is music. We visualized music in a 3d space using colours for visualizing harmonies. The visualization runs in real-time from input MIDI tone stream and can be interactively observed. More details can be found in Klemenc et al (2011).


Figure 1: Visualization of harmony in music using colours.