Refreshments will be served.
Taking the true needs and goals of users into consideration can greatly simplify the visualizations and lead to effective and efficient visual analytics approaches. In this talk, two visual analytics systems developed following this guideline will be presented. The first system, EventRiver, allows users to interactively explore temporally evolving document collections. It was designed, developed, and evaluated around the goal of supporting users in browsing, searching, tracking, and investigating real life events motivating the text generation. The second system, PIWI, visualizes large graphs without clutter. Motivated by the needs of analyzing real-world networks based on their community structure, PIWI closely integrates visualizations with automatic community detection. A set of uncluttered, intuitive visualizations and interactions based on communities are proposed to support tasks such as community-community relationship analysis, community-attribute relationship analysis, and scalable node selection according to complex structural feature and node attribute criteria.