EuroVisSTAR2014

Permanent URI for this collection

https://diglib7.eg.org/handle/10.2312/7749
Swansea, UK

BibTeX (EuroVisSTAR2014)
@inproceedings{
10.2312:eurovisstar.20141170,

booktitle = {
EuroVis - STARs},

editor = {
R. Borgo and R. Maciejewski and I. Viola
},
title = {{
Visualizing Sets and Set-typed Data: State-of-the-Art and Future Challenges}},

author = {
Alsallakh, Bilal
 and 
Micallef, Luana
 and 
Aigner, Wolfgang
 and 
Hauser, Helwig
 and 
Miksch, Silvia
 and 
Rodgers, Peter
},
year = {
2014},

publisher = {
The Eurographics Association},


ISBN = {-},

DOI = {
10.2312/eurovisstar.20141170}

}
@inproceedings{
10.2312:eurovisstar.20141172,

booktitle = {
EuroVis - STARs},

editor = {
R. Borgo and R. Maciejewski and I. Viola
},
title = {{
A Survey on Interactive Lenses in Visualization}},

author = {
Tominski, Christian
 and 
Gladisch, Stefan
 and 
Kister, Ulrike
 and 
Dachselt, Raimund
 and 
Schumann, Heidrun
},
year = {
2014},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-028-4},

DOI = {
10.2312/eurovisstar.20141172}

}
@inproceedings{
10.2312:eurovisstar.20141171,

booktitle = {
EuroVis - STARs},

editor = {
R. Borgo and R. Maciejewski and I. Viola
},
title = {{
A Review of Temporal Data Visualizations Based on Space-Time Cube Operations}},

author = {
Bach, B.
 and 
Dragicevic, P.
 and 
Archambault, D.
 and 
Hurter, C.
 and 
Carpendale, S.
},
year = {
2014},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-028-4},

DOI = {
10.2312/eurovisstar.20141171}

}
@inproceedings{
10.2312:eurovisstar.20141173,

booktitle = {
EuroVis - STARs},

editor = {
R. Borgo and R. Maciejewski and I. Viola
},
title = {{
State-of-the-Art of Visualization for Eye Tracking Data}},

author = {
Blascheck, T.
 and 
Kurzhals, K.
 and 
Raschke, M.
 and 
Burch, M.
 and 
Weiskopf, D.
 and 
Ertl, T.
},
year = {
2014},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-028-4},

DOI = {
10.2312/eurovisstar.20141173}

}
@inproceedings{
10.2312:eurovisstar.20141175,

booktitle = {
EuroVis - STARs},

editor = {
R. Borgo and R. Maciejewski and I. Viola
},
title = {{
A Survey of GPU-Based Large-Scale Volume Visualization}},

author = {
Beyer, Johanna
 and 
Hadwiger, Markus
 and 
Pfister, Hanspeter
},
year = {
2014},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-028-4},

DOI = {
10.2312/eurovisstar.20141175}

}
@inproceedings{
10.2312:eurovisstar.20141174,

booktitle = {
EuroVis - STARs},

editor = {
R. Borgo and R. Maciejewski and I. Viola
},
title = {{
The State of the Art in Visualizing Dynamic Graphs}},

author = {
Beck, Fabian
 and 
Burch, Michael
 and 
Diehl, Stephan
 and 
Weiskopf, Daniel
},
year = {
2014},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-028-4},

DOI = {
10.2312/eurovisstar.20141174}

}
@inproceedings{
10.2312:eurovisstar.20141177,

booktitle = {
EuroVis - STARs},

editor = {
R. Borgo and R. Maciejewski and I. Viola
},
title = {{
State of the Art of Performance Visualization}},

author = {
Isaacs, Katherine E.
 and 
Giménez, Alfredo
 and 
Jusufi, Ilir
 and 
Gamblin, Todd
 and 
Bhatele, Abhinav
 and 
Schulz, Martin
 and 
Hamann, Bernd
 and 
Bremer, Peer-Timo
},
year = {
2014},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-028-4},

DOI = {
10.2312/eurovisstar.20141177}

}
@inproceedings{
10.2312:eurovisstar.20141176,

booktitle = {
EuroVis - STARs},

editor = {
R. Borgo and R. Maciejewski and I. Viola
},
title = {{
State-of-the-Art Report of Visual Analysis for Event Detection in Text Data Streams}},

author = {
Wanner, F.
 and 
Stoffel, A.
 and 
Jäckle, D.
 and 
Kwon, B. C.
 and 
Weiler, A.
 and 
Keim, D. A.
},
year = {
2014},

publisher = {
The Eurographics Association},


ISBN = {978-3-03868-028-4},

DOI = {
10.2312/eurovisstar.20141176}

}

Browse

Recent Submissions

Now showing 1 - 8 of 8
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    Visualizing Sets and Set-typed Data: State-of-the-Art and Future Challenges
    (The Eurographics Association, 2014) Alsallakh, Bilal; Micallef, Luana; Aigner, Wolfgang; Hauser, Helwig; Miksch, Silvia; Rodgers, Peter; R. Borgo and R. Maciejewski and I. Viola
    A variety of data analysis problems can be modelled by defining multiple sets over a collection of elements and analyzing the relations between these sets. Despite their simple concept, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-theart techniques for visualizing different kinds of set relations. We classify these techniques into 7 main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address with these challenges.
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    A Survey on Interactive Lenses in Visualization
    (The Eurographics Association, 2014) Tominski, Christian; Gladisch, Stefan; Kister, Ulrike; Dachselt, Raimund; Schumann, Heidrun; R. Borgo and R. Maciejewski and I. Viola
    Since their introduction in the early nineties, Magic Lenses have attracted much interest. Especially in the realm of visualization, the elegance of using a virtual interactive lens to provide an alternative visual representation of a selected part of the data is highly valued. In this report, we survey the literature on interactive lenses in the context of visualization. Our survey (1) takes a look at how lenses are defined and what properties characterize them, (2) reviews existing lenses for different types of data and tasks, and (3) illustrates the technologies employed to display lenses and to interact with them. Based on our review, we identify challenges and unsolved problems to be addressed in future research.
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    A Review of Temporal Data Visualizations Based on Space-Time Cube Operations
    (The Eurographics Association, 2014) Bach, B.; Dragicevic, P.; Archambault, D.; Hurter, C.; Carpendale, S.; R. Borgo and R. Maciejewski and I. Viola
    We review a range of temporal data visualization techniques through a new lens, by describing them as series of operations performed on a conceptual space-time cube. These operations include extracting subparts of a space-time cube, flattening it across space or time, or transforming the cube's geometry or content. We introduce a taxonomy of elementary space-time cube operations, and explain how they can be combined to turn a three-dimensional space-time cube into an easily-readable two-dimensional visualization. Our model captures most visualizations showing two or more data dimensions in addition to time, such as geotemporal visualizations, dynamic networks, time-evolving scatterplots, or videos. We finally review interactive systems that support a range of operations. By introducing this conceptual framework we hope to facilitate the description, criticism and comparison of existing temporal data visualizations, as well as encourage the exploration of new techniques and systems.
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    State-of-the-Art of Visualization for Eye Tracking Data
    (The Eurographics Association, 2014) Blascheck, T.; Kurzhals, K.; Raschke, M.; Burch, M.; Weiskopf, D.; Ertl, T.; R. Borgo and R. Maciejewski and I. Viola
    Eye tracking technology is becoming easier and cheaper to use, resulting in its increasing application to numerous fields of research. The data collected during an eye tracking experiment can be analyzed by statistical methods and/or with visualization techniques. Visualizations can reveal characteristics of fixations, saccades, and scanpath structures. In this survey, we present an overview of visualization techniques for eye tracking data and describe their functionality. We classify the visualization techniques using nine categories. The categories are based on properties of eye tracking data, including aspects of the stimuli and the viewer, and on properties of the visualization techniques. The classification of about 90 publications including technical as well as application papers with modifications of common visualization techniques are described in more detail. We finally present possible directions for further research in the field of eye tracking data visualization.
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    A Survey of GPU-Based Large-Scale Volume Visualization
    (The Eurographics Association, 2014) Beyer, Johanna; Hadwiger, Markus; Pfister, Hanspeter; R. Borgo and R. Maciejewski and I. Viola
    This survey gives an overview of the current state of the art in GPU techniques for interactive large-scale volume visualization. Modern techniques in this field have brought about a sea change in how interactive visualization and analysis of giga-, tera-, and petabytes of volume data can be enabled on GPUs. In addition to combining the parallel processing power of GPUs with out-of-core methods and data streaming, a major enabler for interactivity is making both the computational and the visualization effort proportional to the amount and resolution of data that is actually visible on screen, i.e., ''output-sensitive'' algorithms and system designs. This leads to recent outputsensitive approaches that are ''ray-guided,'' ''visualization-driven,'' or ''display-aware.'' In this survey, we focus on these characteristics and propose a new categorization of GPU-based large-scale volume visualization techniques based on the notions of actual output-resolution visibility and the current working set of volume bricks-the current subset of data that is minimally required to produce an output image of the desired display resolution. For our purposes here, we view parallel (distributed) visualization using clusters as an orthogonal set of techniques that we do not discuss in detail but that can be used in conjunction with what we discuss in this survey.
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    The State of the Art in Visualizing Dynamic Graphs
    (The Eurographics Association, 2014) Beck, Fabian; Burch, Michael; Diehl, Stephan; Weiskopf, Daniel; R. Borgo and R. Maciejewski and I. Viola
    Dynamic graph visualization focuses on the challenge of representing the evolution of relationships between entities in readable, scalable, and effective diagrams. This work surveys the growing number of approaches in this discipline. We derive a hierarchical taxonomy of techniques by systematically categorizing and tagging publications. While static graph visualizations are often divided into node-link and matrix representations, we identify the representation of time as the major distinguishing feature for dynamic graph visualizations: either graphs are represented as animated diagrams or as static charts based on a timeline. Evaluations of animated approaches focus on dynamic stability for preserving the viewer's mental map or, in general, compare animated diagrams to timeline-based ones. Finally, we identify and discuss challenges for future research.
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    State of the Art of Performance Visualization
    (The Eurographics Association, 2014) Isaacs, Katherine E.; Giménez, Alfredo; Jusufi, Ilir; Gamblin, Todd; Bhatele, Abhinav; Schulz, Martin; Hamann, Bernd; Bremer, Peer-Timo; R. Borgo and R. Maciejewski and I. Viola
    Performance visualization comprises techniques that aid developers and analysts in improving the time and energy efficiency of their software. In this work, we discuss performance as it relates to visualization and survey existing approaches in performance visualization. We present an overview of what types of performance data can be collected and a categorization of the types of goals that performance visualization techniques can address. We develop a taxonomy for the contexts in which different performance visualizations reside and describe the state of the art research pertaining to each. Finally, we discuss unaddressed and future challenges in performance visualization.
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    State-of-the-Art Report of Visual Analysis for Event Detection in Text Data Streams
    (The Eurographics Association, 2014) Wanner, F.; Stoffel, A.; Jäckle, D.; Kwon, B. C.; Weiler, A.; Keim, D. A.; R. Borgo and R. Maciejewski and I. Viola
    Event detection from text data streams has been a popular research area in the past decade. Recently, the evolution of microblogging and social network services opens up great opportunities for various kinds of knowledge-based intelligence activities which require tracking of real-time events. In a sense, visualizations in combination with analytical processes could be a viable method for such tasks because it can be used to analyze the sheer amounts of text streams. However, data analysts and visualization experts often face grand challenges stemming out of the ill-defined concept of event and various kinds of textual data. As a result, we have few guidelines on how to build successful visual analysis tools that can handle specific event types and diverse textual data sources. Our goal is to take the first step towards answering the question by organizing insights from prior research studies on event detection and visual analysis. In the scope of this report, we summarize the evolution of event detection in combination with visual analysis over the past 14 years and provide an overview of the state-of-the-art methods. Our investigation sheds light on various kinds of research areas that can be the most beneficial to the field of visual text event analytics.