The availability of large data sources provides new opportunities for understanding patterns and behaviors of modern society. The information from these sources requires effective visualization methods to extract meaningful information from the data and facilitate the interpretation of very complex phenomena.

The objective of the course is to present an overview of basic methods and visualization techniques for effective presentation of information from different sources: structured data (relational hierarchies, trees), relational data (social networks), temporal data, spatial data and data space-time. We will present and discuss several case study scenarios with the existing methods and tools.

Syllabus

- Visual Metaphors for Information
* Hierarchical and structured data
* Relazional and graph-based data
* Temporal Data
* Spatial data
* Spatio-temporal data
* Unstructured information (text)
- Methods and Tools
* Overview of existing visual analytics environments
- Visual Analytics Process
* Definition of a Knowledge Discovery process
* Framework for VA
* Visual exploration and analytics of data
* Case studies