The CVAST at Vienna University of Technology, Faculty of Informatics, conducts research and provides teaching in Visualization (Information Visualization & Visual Analytics).

CVAST conducts research and provides teaching in Visualization (Information Visualization, Visual Analytics). We are concerned with computer-tools, methods, and concepts that support humans in coping with complex information spaces. We strive to make complex information structures more comprehensible, facilitate new insights, and enable process of information and knowledge discovery. At this, human abilities as well as users' needs and tasks are central issues to assist in situations where complex decisions need to be made. Data and information are a broad field – we focus particularly on the temporal, spatial and spatial-temporal dimensions.

Visualization (Information Visualization & Visual Analytics)

On the one hand, a huge amount of highly structured and unstructured data and information is available in working situations and the daily life, which need to be interpreted for further decision making. On the other hand, different kinds of data and information analysis methods have been developed to gain more insights (information and knowledge gains). We investigate interactive visual and automatic methods which support the interactive exploration process in order to gain new insights. At this, we do not primarily aim to design “beautiful pictures”, but to develop visual and automatic representations and methods to explore multidimensional information spaces, which support the shaping of hypotheses facilitated by various forms of user interactions.

Plan Management & Process Engineering

Plans, workflows, and processes are omnipresent. Computer-assisted methods could ease the handling of these. On the one hand, we develop methods to support the design of such plans and actions. On the other hand, we investigate methods to execute, adapt, and maintain these. The starting point of our research is a time-oriented, intention-based plan representation language. However, such languages are very complex and hardly accessible by the user. To overcome that situation, we study visual methods to communicate such plans (for example, metaphor graphic-based visualizations) and structure as well as model such plans in an (semi-)automatic way (for example, information extraction methods).

Bridging the Gap between Theory and Practice

Theoretical methods alone can only partly support the knowledge discovery process. Therefore, we examine the usability and applicability of our methods and apply them in the medical domain. One of our main foci is medical therapy planning: clinical guidelines and protocols aim to support medical staff in their daily routine. Currently, guidelines and protocols are available in the form of textual documents only. However, if clinical guidelines are embedded within clinical decision support systems and integrated within the workflow of clinicians’ work habits and patient management, they could ease clinicians’ practices. Thus, they have to be presented in a structured format that can be used by clinical decision support systems. Moreover, the life cycle of such guidelines needs to be taken into account to support the concept of “living guidelines”. Other application areas are Digital Humanities, Financial Markets, Business Intelligence, Market Analysis, as well as other disciplines of Natural, Social, and Economic Sciences.