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Hadlak, Steffen; Schumann, Heidrun; Schulz, Hans-Jörg

A Survey of Multi-faceted Graph Visualization


Eurographics Conference on Visualization (EuroVis) 2015 - STARs

Eurographics Conference on Visualization (EuroVis) <17, 2015, Cagliari, Sardinia, Italy>

Graph visualization is an important field in information visualization that is centered on the graphical display of graph-structured data. Yet real world data is rarely just graph-structured, but instead exhibits multiple facets, such as multivariate attributes, or spatial and temporal frames of reference. In an effort to display different facets of a graph, such a wealth of visualization techniques has been developed in the past that current surveys focus on a single additional facet only in order to enumerate and classify them. This report builds on existing graph visualization surveys for the four common facets of partitions, attributes, time, and space. It contributes a generic high-level categorization of faceted graph visualization that subsumes the existing classifications, which can be understood as facet-specific refinements of the resulting categories. Furthermore, it extends beyond existing surveys by applying the same categorization to graph visualizations with multiple facets. For each of the introduced categories and considered facets, this overview provides visualization examples to illustrate instances of their realization.

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Alm, Rebekka; Aehnelt, Mario; Hadlak, Steffen; Urban, Bodo

Annotated Domain Ontologies for the Visualization of Heterogeneous Manufacturing Data


Human Interface and the Management of Information. Proceedings Part I

International Conference on Human Interface and the Management of Information (HIMI) <2015, Los Angeles, CA, USA>

Manufacturing processes such as monitoring and controlling typically confront the user with a variety of heterogeneous data sources and systems. The cognitive efforts to summarize and combine the data from these different sources affect the user's efficiency. Our goal is to support the user in his work task by integrating the data and presenting them in a more perceivable way. Hence, we introduce an approach in which different data sources are integrated in an annotated semantic knowledge base: our domain ontology. Based on this ontology, contextually relevant data for a specific work task is selected and embedded into a meta-visualization providing an overview of the data based on the user's mental model. Two systems finally exemplify the usage of our approach.

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Schulz, Hans-Jörg; Hadlak, Steffen

Preset-based Generation and Exploration of Visualization Designs


Journal of Visual Languages & Computing

Generating the "right" visual representation for the data and task at hand remains a standing challenge in visualization research and practice. A variety of different approaches to produce visual representations have been proposed in the past, including such noteworthy instances as visualization by example and visualization by analogy. With this paper, we add a new twist to creating visual representations by proposing away to construct new visualization designs by blending together a number of existing visual representations, called presets. We embed this novel blending approach in suitable visual interfaces, such as a gridded canvas to be used by the casual user in the style of a palette for mixing colors, or a range of sliders to be used by the expert user in the style of a studio mixer for audio tracks. These can be employed for rapid prototyping of a specific visual representation, as well as to explore the overall design space of visual representations captured by our approach. We showcase our preset-based blending and its interfaces with examples of the design of 2D tree visualizations and product plots.

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Alm, Rebekka; Hadlak, Steffen

Towards Integration and Management of Contextualized Information in the Manufacturing Environment by Digital Annotations


Proceedings of the International Summer School on Visual Computing 2015

International Summer School on Visual Computing <1, 2015, Rostock, Germany>

Advanced manufacturing promises an evolution of industrial production processes by increasing flexibility and specialization of work tasks to deal with mass customization. To maintain a high quality and efficiency despite this increasing customization or even improve them, intelligent assistance systems are required supporting the workers. This paper describes how to integrate digital information in a manufacturing environment, where workers use assistance systems to access task related information. To explain requirements and constraints of assistance Systems, a survey was conducted. Based on the results of this survey, a conceptual approach is specified that focuses on quick and easy access to relevant information via a tablet. To provide manufacturing workers with relevant information, a method is presented to measure information relevance based on an ontology. A demonstrative scenario describes the application of the conceptual approach.

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Hadlak, Steffen; Schumann, Heidrun [Referent]; Urban, Bodo [Referent]; Kerren, Andreas [Referent]

Graph Visualization in Space and Time


Rostock, Univ., Diss., 2014

The visual analysis of graphs plays an important role in many fields and includes a diversity of aspects such as the graphs' structure and associated attributes in their spatial and temporal context. Because of their increasing size, their visualization becomes more and more difficult and necessitates a multitude of different visualization techniques. This problem becomes even more severe as with a changing analysis focus on the graph, the analyst needs to flexibly switch between different visualizations at any time. This thesis aims at solving these three challenges. First, the handling of the diversity and emerging problems are discussed exemplary for two approaches each providing a multitude of differently suited tree visualizations. Here, a family of point-based tree layouts is introduced that consists of layouts with a similar layout scheme. And an implicit tree visualization design space is derived by identifying common design decisions. For a scalable analysis of large graphs, new reduction approaches are introduced. These approached are based on the one hand on clustering techniques abstracting either the structural or temporal aspect of the graphs. And on the other hand they rely on Degree-of-Interest functions to discern interesting nodes, edges and time points. Finally, to bring the different visualizations together and thus allow a flexible analysis, novel approaches for their combination and synchronization are introduced. These approaches include the in situ visualization that is based on portals to allow a local combination of visualizations and a novel abstract overview of all aspect allowing the synchronization of multiple visualizations.