Even though interaction is an important part of information visualization (Infovis), it has garnered a relatively low level of attention from the Infovis community. A few frameworks and taxonomies of Infovis interaction techniques exist, but they typically focus on low-level operations and do not address the variety of benefits interaction provides. After conducting an extensive review of Infovis systems and their interactive capabilities, we propose seven general categories of interaction techniques widely used in Infovis: 1) Select, 2) Explore, 3) Reconfigure, 4) Encode, 5) Abstract/Elaborate, 6) Filter, and 7) Connect. These categories are organized around a user's intent while interacting with a system rather than the low-level interaction techniques provided by a system. The categories can act as a framework to help discuss and evaluate interaction techniques and hopefully lay an initial foundation toward a deeper understanding and a science of interaction.

While intelligence analysis has been a primary target domain for visual analytics system development, relatively little user and task analysis has been conducted within this area. Our research community's understanding of the work processes and practices of intelligence analysts is not deep enough to adequately address their needs. Without a better understanding of the analysts and their problems, we cannot build visual analytics systems that integrate well with their work processes and truly provide benefit to them. In order to close this knowledge gap, we conducted a longitudinal, observational field study of intelligence analysts in training within the intelligence program at Mercyhurst College. We observed three teams of analysts, each working on an intelligence problem for a 10-week period. Based on the findings of the study, we describe and characterize processes and methods of intelligence analysis that we observed, make clarifications regarding the processes and practices, and suggest design implications for visual analytics systems for intelligence analysis.

We have explored design opportunities to enrich the tourism experience of people at the Georgia Aquarium by providing a context of photos and by motivating people to be active creators of content to share their experiences with others. We designed a system named RevisiTour to enable visitors to reorganize photos taken from tour sites and share the photos with others. A visitor's path and timestamp are recorded on a badge with a sensor throughout a trip. After the trip, the visitor can access a website where s/he uploads photos, synchronizes them with the path, and shares the photos with others. We report on how the system was designed, developed, and refined. After developing a prototype, we evaluated a mock-up of the system with actual visitors in the Georgia Aquarium. The analysis and design implications show the possibility of user-generated content systems for tour sites.

No abstract

No abstract