Dominik Sacha

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Visual analytics enables us to analyze huge information spaces in order to support complex decision making and data exploration. Humans play a central role in generating knowledge from the snippets of evidence emerging from visual data analysis. Although prior research provides frameworks that generalize this process, their scope is often narrowly focused(More)
Visual analytics supports humans in generating knowledge from large and often complex datasets. Evidence is collected, collated and cross-linked with our existing knowledge. In the process, a myriad of analytical and visualisation techniques are employed to generate a visual representation of the data. These often introduce their own uncertainties, in(More)
Soccer is one the most popular sports today and also very interesting from an scientific point of view. We present a system for analyzing high-frequency position-based soccer data at various levels of detail, allowing to interactively explore and analyze for movement features and game events. Our Visual Analytics method covers single-player, multi-player(More)
Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful in exploratory data analysis, they need to be adapted to human needs and domain-specific problems, ideally, interactively, and on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating DR(More)
When exploring large spatial datasets, zooming and panning interactions often lead to the loss of contextual overview. Existing overview-plus-detail approaches allow users to view context while inspecting details, but they often suffer from distortion or overplotting. In this paper, we present an off-screen visualization method called Ambient Grids that(More)
Visual analytics combines human and machine abilities to generate new knowledge from data. Within this process, uncertainty often plays an important role in hindering the sensemaking process and analysis tasks. On the machine side, uncertainty builds up from the data source level to the visual output. On the human side, these uncertainties often result in(More)
The visualization of syntactic analyses may be challenging due to the number of readings, the size and detail of the structures, and the interrelations between levels of linguistic description. We present a range of interactive visualization techniques applied to complex syntactic analyses in INESS, an online infrastructure for parsing and the annotation(More)
We present a tangible approach for exploring and comparing multi-dimensional data points collaboratively by combining Sifteo Cubes with glyph visualizations. Various interaction techniques like touching, shaking, moving or rotating the displays support the user in the analysis. Context dependent glyph-like visualization techniques make best use of the(More)
We present an innovative visualization technique for the analysis of historical data. We illustrate our method with respect to a diachronic case study involving V1 word order in Icelandic. A number of interacting factors have been proposed by linguists as being determinative of matrix declarative V1. The significance of these factors in contributing to(More)