Caleydoplex - Collaborative Information Exploration

Critical decisions involving a lot of data are rarely made by a single person, but are rather discussed and evaluated by a team of experts. Examples are doctors deciding for treatment of severe illness, emergency services having to react to ongoing crises, or engineers collaborating to make technical decisions concerning expensive products. These activities can be assisted by information visualization tools. However, traditional information visualization rarely considers the collaborative nature of data analysis tasks. The foundation of our research proposal is the extension of a multiple view visualization system to a multi-display environment. Multiple view visualization shows data in different representations and thereby accommodates for different knowledge backgrounds and user preferences. Multi-display environments turn unused wall and table spaces into interactive surfaces using off-the-shelf projection technology and integrate private workstations smoothly into this shared interactive workspace. Our research aim is the design and creation of a co-located collaborative information visualization workspace dealing with two principal challenges: display space management and collaborative interaction techniques. Intelligent display space management adopts information visualizations and placement of views automatically to the physical display properties and supports the users interacting with the environment. Combined with visual linking of related data entities distributed across the environment, it will help to establish a common knowledge ground. Collaborative interaction techniques are required to organize such a rich, but potentially complex environment. We will investigate high-level activity support for typical tasks in shared information workspaces, personalized actions, and how users can maintain awareness of each other`s activities. The proposed research benefits from two ongoing projects at Graz University of Technology: Deskotheque delivers the basic technology necessary for collaborative work in multi-display environments, while Caleydo, a visualization project from the biomedical domain, provides an excellent use case, including the necessary experts willing to collaborate in studies. Using these frameworks, we plan to conduct several usability studies, with prototypes of different levels of sophistication.

As the amount of information available is increasing faster than ever before, a single person using a regular desktop computer with a single monitor is often not capable to efficiently analyze the data, its relationships, and its crosslinks. In the field of biomedicine, for example, an ever increasing wealth of data promises improved diagnostics and treatment, yet an individual scientist using traditional tools might not be able to utilize all the available data to optimally diagnose and treat a patient. While automatic methods can be of tremendous value, there are certain problems that require human judgement, and human judgement should be based on the relevant data. One approach to tackle the increasingly large and heterogeneous data is through visualization on large and multiple displays. A concurrent trend is the deeper specialization of experts. We observe that, due to the complexity of the subject areas, experts need to consult each other on a regular basis to make holistic judgements. In a modern, informationdriven analysis, there is a clear need for methods that support collaborative data analysis. First, we introduced new ways of assisting users in analyzing and navigating large amounts of data. For example, we introduce methods that automatically show data that is related to a user selection. We demonstrated the usefulness of these methods by providing our tools to domain experts, who were able to identify interesting findings faster and with fewer mistakes. Second, to improve the workflow of users working with largescale display environments, we developed and evaluated several methods for arranging and navigating to content on displays of different sizes and form factors. The reduced amount of time needed to search for information and to arrange the windows allowed users to concentrate on the actual task of getting the information that is required in their analysis. Finally, we investigated how the workflow can be improved, if multiple people are working together in a setting with multiple and largescale displays on the same goal at the same location. A tool for automatically placing windows of multiple users without interfering with each other allows them to efficiently work in collaboration on the common goal. The methods developed in the course of this project will influence the way experts jointly analyze large and complex data, both on conventional and largescale display devices.