Heidrun Schumann spends much of her time researching Visualization, Data visualization, Information visualization, Visual analytics and Human–computer interaction. Her Visualization study incorporates themes from Variety, Theoretical computer science, Data science and Taxonomy. The Data visualization study combines topics in areas such as Graphical user interface, Computer vision and Geographic information system.
Her research in Information visualization intersects with topics in Creative visualization and Event. Her Interactive visual analysis study in the realm of Visual analytics interacts with subjects such as Lens. Her work in Human–computer interaction tackles topics such as Multimedia which are related to areas like User interface and Interaction Styles.
Her primary areas of investigation include Visualization, Visual analytics, Artificial intelligence, Human–computer interaction and Information visualization. Her research investigates the connection between Visualization and topics such as Theoretical computer science that intersect with issues in Graph drawing. Her work investigates the relationship between Visual analytics and topics such as Data science that intersect with problems in Field.
Her Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Optical coherence tomography, Computer vision and Pattern recognition. As a part of the same scientific family, Heidrun Schumann mostly works in the field of Human–computer interaction, focusing on Multimedia and, on occasion, Mobile device and Presentation. The various areas that Heidrun Schumann examines in her Information visualization study include Interactive visualization and Scientific visualization.
Heidrun Schumann mostly deals with Visual analytics, Visualization, Artificial intelligence, Human–computer interaction and Optical coherence tomography. Her research integrates issues of Interactive visualization, Information visualization, Software engineering and Data science in her study of Visual analytics. As part of one scientific family, Heidrun Schumann deals mainly with the area of Data science, narrowing it down to issues related to the Field, and often Principal.
Her 3d terrain and Data visualization study in the realm of Visualization connects with subjects such as Workflow. She works mostly in the field of Data visualization, limiting it down to topics relating to Data exchange and, in certain cases, Data modeling. Heidrun Schumann interconnects Computer vision and Pattern recognition in the investigation of issues within Artificial intelligence.
Her scientific interests lie mostly in Visual analytics, Visualization, Human–computer interaction, Workflow and Pattern recognition. Visual analytics and Data science are commonly linked in her work. Heidrun Schumann has included themes like Field and Iterative and incremental development in her Data science study.
Her Visualization study frequently links to other fields, such as Information needs. Her Human–computer interaction research is multidisciplinary, incorporating elements of Interactive visualization, Pipeline, Information visualization and Conceptual model. Her Pattern recognition research integrates issues from Interface and Artificial intelligence.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Visualization of Time-Oriented Data
Wolfgang Aigner;Silvia Miksch;Heidrun Schumann;Christian Tominski.
(2011)
Space, time and visual analytics
Gennady Andrienko;Natalia Andrienko;Urska Demsar;Doris Dransch.
International Journal of Geographical Information Science (2010)
Visualizing time-oriented data-A systematic view
Wolfgang Aigner;Silvia Miksch;Wolfgang Müller;Heidrun Schumann.
Computers & Graphics (2007)
Visualisierung: Grundlagen und allgemeine Methoden
Heidrun Schumann;Wolfgang Müller.
(2000)
Visual Methods for Analyzing Time-Oriented Data
W. Aigner;S. Miksch;W. Muller;H. Schumann.
IEEE Transactions on Visualization and Computer Graphics (2008)
Stacking-Based Visualization of Trajectory Attribute Data
C. Tominski;H. Schumann;G. Andrienko;N. Andrienko.
IEEE Transactions on Visualization and Computer Graphics (2012)
Visualization for modeling and simulation: visualization methods for time-dependent data - an overview
Wolfgang Müller;Heidrun Schumann.
winter simulation conference (2003)
3D information visualization for time dependent data on maps
C. Tominski;P. Schulze-Wollgast;H. Schumann.
Ninth International Conference on Information Visualisation (IV'05) (2005)
Axes-based visualizations with radial layouts
Christian Tominski;James Abello;Heidrun Schumann.
acm symposium on applied computing (2004)
The Visualization of Uncertain Data: Methods and Problems.
Henning Griethe;Heidrun Schumann.
SimVis (2006)
Profile was last updated on December 6th, 2021.
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Fraunhofer Society
TU Wien
Fraunhofer Institute for Intelligent Analysis and Information Systems
TU Dresden
University of Twente
City, University of London
Graz University of Technology
Otto-von-Guericke University Magdeburg
University of Konstanz
University of Bonn
Fraunhofer Institute for Intelligent Analysis and Information Systems
Publications: 44
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