Toward a Deeper Understanding of the Role of Interaction in Information Visualization

Abstract

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.

The personal cockpit

“…Further, these operations should be coordinated across multiple views. For instance, using a technique known as brushing [231] causes a selection made in one view to be reflected through visual feedback (e.g. highlights) across related items on all views.…”

“…To the left is a preview window that provides detailed information about the hotels, and to the right is a filter control panel, where users can specify desired attributes (in this case, cost, star-rating and guest review scores). The windows are interlinked [231] such that selecting a specific hotel on the map causes details about that hotel to appear on the preview pane. Likewise, adjusting the filter controls reduces or increases the number of hotels shown on the map.…”

On the Challenges and Opportunities in Visualization for Machine Learning and Knowledge Extraction: A Research Agenda

“…However, interaction is a costly operation and experts are often in need of approaches that provide them reliable solutions quickly and accurately [22]. In order to develop effective human-in-the-loop systems [23], there is a need to strike the right balance between computation and human initiative.…”

From Tree to Map: Using Cognitive Learning Theory to Suggest Alternative Ways to Visualize Macroevolution

“…Meaningful interaction is not necessarily enabled by interactivity per se, but by specific types of interactivity. In order to facilitate meaningful interaction, the type of interactivity should be appropriate to the task that the user is trying to accomplish (Yi et al 2007). For example, if a viewer is interested in the specific details about one point in a data display, it would be more appropriate for her to select and elaborate on that one data point, rather than generate a web of associations between that data point and others.…”