EuroVA11

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/984

Characterizing Visual Analytics in Diagnostic Imaging

[meta data] [files:
001-004.pdf
]
Lundström, C.
; 
Persson, A.

Understanding the Role and Value of Interaction: First Steps

[meta data] [files:
017-020.pdf
]
Aigner, W.

Data Driven Color Mapping

[meta data] [files:
005-008.pdf ,
paper4_supplementaryfile.pdf
]
Eisemann, Martin
; 
Albuquerque, Georgia
; 
Magnor, Marcus

Towards a Concept how the Structure of Time can Support the Visual Analytics Process

[meta data] [files:
009-012.pdf
]
Lammarsch, T.
; 
Aigner, W.
; 
Bertone, A.
; 
Miksch, S.
; 
Rind, A.

SmartStripes - Looking under the Hood of Feature Subset Selection Methods

[meta data] [files:
013-016.pdf
]
May, T.
; 
Davey, J.
; 
Ruppert, T.

Visual Analysis of User Behaviour in Pay-Per-Bid Auctions

[meta data] [files:
025-028.pdf
]
Walker, Rick
; 
Cenydd, Llyr ap
; 
Pop, Serban
; 
Roberts, Jonathan C.

Visual Analysis of Advanced Manufacturing Simulations

[meta data] [files:
029-032.pdf
]
Wörner, M.
; 
Ertl, T.

Visual Comparison of Ranked Result Cumulated Gains

[meta data] [files:
021-024.pdf
]
Ferro, N.
; 
Sabetta, A.
; 
Santucci, G.
; 
Tino, G.
; 
Veltri, F.

A Framework for the Multi-Temporal Analysis of Land Cover Change using Visual Analytics

[meta data] [files:
033-036.pdf
]
Kinkeldey, C.
; 
Schiewe, J.

Interactive Analysis of Object Group Changes over Time

[meta data] [files:
041-044.pdf
]
Bremm, S.
; 
Landesberger, T. von
; 
Andrienko, G.
; 
Andrienko, N.
; 
Schreck, Tobias

Adaptive Interactive Multi-Resolution Computational Steering for Complex Engineering Systems

[meta data] [files:
045-048.pdf
]
Matkovic, K.
; 
Gracanin, D.
; 
Jelovic, M.
; 
Cao, Y.

Exploring Complex Mobile Life through Lightweight Visualizations

[meta data] [files:
037-040.pdf
]
Kim, Tanyoung
; 
Blom, Jan
; 
Stasko, John

Contingency Wheel: Visual Analysis of Large Contingency Tables

[meta data] [files:
053-056.pdf
]
Alsallakh, Bilal
; 
Groeller, Eduard
; 
Miksch, Silvia
; 
Suntinger, Martin

Steerable Clustering for Visual Analysis of Ecosystems

[meta data] [files:
049-052.pdf
]
Ahmed, Zafar
; 
Yost, Patrick
; 
McGovern, Amy
; 
Weaver, Chris

BibTeX (EuroVA11)
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/001-004,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Characterizing Visual Analytics in Diagnostic Imaging}},

author = {
Lundström, C.
 and 
Persson, A.
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/001-004}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/017-020,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Understanding the Role and Value of Interaction: First Steps}},

author = {
Aigner, W.
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/017-020}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/005-008,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Data Driven Color Mapping}},

author = {
Eisemann, Martin
 and 
Albuquerque, Georgia
 and 
Magnor, Marcus
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/005-008}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/009-012,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Towards a Concept how the Structure of Time can Support the Visual Analytics Process}},

author = {
Lammarsch, T.
 and 
Aigner, W.
 and 
Bertone, A.
 and 
Miksch, S.
 and 
Rind, A.
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/009-012}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/013-016,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
SmartStripes - Looking under the Hood of Feature Subset Selection Methods}},

author = {
May, T.
 and 
Davey, J.
 and 
Ruppert, T.
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/013-016}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/025-028,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Visual Analysis of User Behaviour in Pay-Per-Bid Auctions}},

author = {
Walker, Rick
 and 
Cenydd, Llyr ap
 and 
Pop, Serban
 and 
Roberts, Jonathan C.
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/025-028}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/029-032,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Visual Analysis of Advanced Manufacturing Simulations}},

author = {
Wörner, M.
 and 
Ertl, T.
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/029-032}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/021-024,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Visual Comparison of Ranked Result Cumulated Gains}},

author = {
Ferro, N.
 and 
Sabetta, A.
 and 
Santucci, G.
 and 
Tino, G.
 and 
Veltri, F.
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/021-024}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/033-036,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
A Framework for the Multi-Temporal Analysis of Land Cover Change using Visual Analytics}},

author = {
Kinkeldey, C.
 and 
Schiewe, J.
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/033-036}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/041-044,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Interactive Analysis of Object Group Changes over Time}},

author = {
Bremm, S.
 and 
Landesberger, T. von
 and 
Andrienko, G.
 and 
Andrienko, N.
 and 
Schreck, Tobias
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/041-044}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/045-048,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Adaptive Interactive Multi-Resolution Computational Steering for Complex Engineering Systems}},

author = {
Matkovic, K.
 and 
Gracanin, D.
 and 
Jelovic, M.
 and 
Cao, Y.
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/045-048}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/037-040,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Exploring Complex Mobile Life through Lightweight Visualizations}},

author = {
Kim, Tanyoung
 and 
Blom, Jan
 and 
Stasko, John
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/037-040}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/053-056,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Contingency Wheel: Visual Analysis of Large Contingency Tables}},

author = {
Alsallakh, Bilal
 and 
Groeller, Eduard
 and 
Miksch, Silvia
 and 
Suntinger, Martin
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/053-056}

}
@inproceedings{
:10.2312/PE/EuroVAST/EuroVA11/049-052,

booktitle = {
EuroVA 2011: International Workshop on Visual Analytics},

editor = {
Silvia Miksch and Giuseppe Santucci
},
title = {{
Steerable Clustering for Visual Analysis of Ecosystems}},

author = {
Ahmed, Zafar
 and 
Yost, Patrick
 and 
McGovern, Amy
 and 
Weaver, Chris
},
year = {
2011},

publisher = {
The Eurographics Association},


ISBN = {978-3-905673-82-1},

DOI = {
/10.2312/PE/EuroVAST/EuroVA11/049-052}

}

Browse

Recent Submissions

Now showing 1 - 14 of 14
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    Characterizing Visual Analytics in Diagnostic Imaging
    (The Eurographics Association, 2011) Lundström, C.; Persson, A.; Silvia Miksch and Giuseppe Santucci
    Many necessary and desired improvements in healthcare are dependent on progress in medical imaging. As shown in this paper, the challenges targeted by visual analytics (VA) coincide with main challenges for radiologists' diagnostic work. Key prerequisites for VA in this application domain have been identified through analysis of a survey among 22 radiologists at a university hospital. Two major findings are that efficiency is perceived as the most challenging aspect of their diagnostic work and that an exploratory approach is necessary in everyday image review. The presented characterization constitutes a validated input for design of future VA research initiatives within medical imaging.
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    Understanding the Role and Value of Interaction: First Steps
    (The Eurographics Association, 2011) Aigner, W.; Silvia Miksch and Giuseppe Santucci
    Visual Analytics strongly emphasizes the importance of interaction. However, until now, interaction is only sparingly treated as subject matter on its own. How and why interactivity is beneficial to gain insight and make decisions is mostly left in the dark. Due to this lack of initial direction, it seems important to make further attempts in facilitating a deeper understanding of the concept of interactivity. Therefore, different perspectives towards interactivity are discussed and cognitive theories and models are investigated. The main aim of this paper is to broaden the view on interaction and spark further discussion towards a sound theoretical grounding for the field.
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    Data Driven Color Mapping
    (The Eurographics Association, 2011) Eisemann, Martin; Albuquerque, Georgia; Magnor, Marcus; Silvia Miksch and Giuseppe Santucci
    In this paper we present a simple, yet effective method to map data set values of different distributions to a color map in order to reveal interesting structures. We make use of an ordering and a simple projection technique to transform the data set before color mapping. Our transformation yields convincing results for various distributions. It also removes the burden from the user to test several mappings beforehand. A simple angular interpolation technique allows to project the data values of the visualization as desired, interactively.
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    Towards a Concept how the Structure of Time can Support the Visual Analytics Process
    (The Eurographics Association, 2011) Lammarsch, T.; Aigner, W.; Bertone, A.; Miksch, S.; Rind, A.; Silvia Miksch and Giuseppe Santucci
    The primary goal of Visual Analytics (VA) is the close intertwinedness of human reasoning and automated methods. An important task for this goal is formulating a description for such a VA process. We propose the design of a VA process description that uses the inherent structure contained in time-oriented data as a way to improve the integration of human reasoning. This structure can, for example, be seen in the calendar aspect of time being composed of smaller granularities, like years and seasons. Domain experts strongly consider this structure in their reasoning, so VA needs to consider it, too.
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    SmartStripes - Looking under the Hood of Feature Subset Selection Methods
    (The Eurographics Association, 2011) May, T.; Davey, J.; Ruppert, T.; Silvia Miksch and Giuseppe Santucci
    We propose a visualization method for the diagnosis and interactive refinement of automatic techniques for feature subset selection. So-called filter techniques use statistical ranking measures to identify the most useful combination of features for further analysis. Usually a measure is applied to all entities of a data-table. The influence of atypical entities can distort the result, but this distortion may be masked by the statistical aggregation. Clearly, feature and entity subset selection are highly interdependent. Our technique, SmartStripes, intends to make this interdependency visible.
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    Visual Analysis of User Behaviour in Pay-Per-Bid Auctions
    (The Eurographics Association, 2011) Walker, Rick; Cenydd, Llyr ap; Pop, Serban; Roberts, Jonathan C.; Silvia Miksch and Giuseppe Santucci
    In pay-per-bid auctions, placing a bid costs a fee, and only raises the price of the item by a small increment. At the conclusion of the auction, the last bidder wins, and the price paid by the winning bidder is subsidised by the bidding fees paid by unsuccessful bidders. In this short paper, the first publicly available analytics of data from a pay-per-bid website are presented. We present a visual analysis approach using a specific tool developed for the purpose. This dataset represents a difficult challenge because it is huge, it is difficult to evaluate in practice even using auction theory since there exists no mathematically optimal strategy for successful bidding, and non-trivial patterns are sought.
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    Visual Analysis of Advanced Manufacturing Simulations
    (The Eurographics Association, 2011) Wörner, M.; Ertl, T.; Silvia Miksch and Giuseppe Santucci
    Today's manufacturing companies are faced with requests for highly customer-specific products that come in numerous variants but small numbers of units per variant. Therefore, their manufacturing processes need to be flexible and versatile. This opens up opportunities for real-time process planning, yet there is insufficient tool support for process planning that is not done days or weeks in advance. As a result, there is little incentive to collect process data on site. We describe a visual analysis tool that uses advanced manufacturing simulation to evaluate and optimize flexible manufacturing processes.
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    Visual Comparison of Ranked Result Cumulated Gains
    (The Eurographics Association, 2011) Ferro, N.; Sabetta, A.; Santucci, G.; Tino, G.; Veltri, F.; Silvia Miksch and Giuseppe Santucci
    Ranking is fundamental in Information Retrieval (IR) and several measures have been developed over the years to assess the quality of a ranked result list, such as those based on the idea of computing the cumulative gain up to a given ranked position and taking into account multiple relevance levels. These measures allow for comparing the performances of different Information Retrieval System (IRS), giving credit to their ability to retrieve highly relevant documents and to rank them topmost in the result list. However, while this approach is able to assess the differences among two or more retrieval systems, it does not allow to easily understand and inspect the reasons of good or bad performances. To this end, this paper presents a Visual Analytics (VA) environment that allows for visually exploring the ranked retrieval results, pointing out the search failures and providing useful insights for improving the underlying IRS ranking algorithm.
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    A Framework for the Multi-Temporal Analysis of Land Cover Change using Visual Analytics
    (The Eurographics Association, 2011) Kinkeldey, C.; Schiewe, J.; Silvia Miksch and Giuseppe Santucci
    Land cover change analysis serves as a basis for planning processes in a wide range of applications. For this task, the use of remote sensing data has become more popular over the last decades. However, despite much research in the field of change analysis based on remote sensing data, effective and efficient methods are not available yet. In order to get closer to this goal, we propose the application of Visual Analytics to this field combining computational methods with interactive visualization. We expect that the close integration of the user into the change analysis process will lead to more powerful solutions. However, for the design of tools following this approach we see the need for instruments to formalize workflows. For this reason, we are developing a framework that allows for a systematic workflow description. This contribution presents the basic concept of the framework including an exemplary application.
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    Interactive Analysis of Object Group Changes over Time
    (The Eurographics Association, 2011) Bremm, S.; Landesberger, T. von; Andrienko, G.; Andrienko, N.; Schreck, Tobias; Silvia Miksch and Giuseppe Santucci
    The analysis of time-dependent data is an important task in various application domains. Often, the analyzed data objects belong to groups. The group memberships may stem from natural arrangements (e.g., animal herds), or may be constructed during analysis (e.g., by clustering). Group membership may change over time. Therefore, one important analytical aspect is to examine these changes (e.g., which herds change members and when). In this paper, we present a technique for visual analysis of group changes over time. We combine their visualization and automatic analysis. Interactive functions allow for tracking the data changes over time on group, set and individual level. We also consider added and removed objects (e.g., newly born or died animals). For large time series, automatic data analysis selects interesting time points and group changes for detailed examination. We apply our approach on the VAST 2008 challenge data set revealing new insights.
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    Adaptive Interactive Multi-Resolution Computational Steering for Complex Engineering Systems
    (The Eurographics Association, 2011) Matkovic, K.; Gracanin, D.; Jelovic, M.; Cao, Y.; Silvia Miksch and Giuseppe Santucci
    Computational steering integrates modeling, computation, data analysis, visualization, and data input components of a simulation. Since the simulation space is, in general, very large and continuous, selecting discrete simulation points that can reasonably represent the whole simulation space is difficult. We need to interpolate the missing values and cover a continuous region of interest in the simulation space. We describe an approach that, in an iterative manner, allows a domain expert to interactively select data points (design of experiments), approximate the values in a continuous region of the simulation space (regression) and automatically find the best points in that continuous region based on the specified constraints and objectives (optimization), using the regression and aggregated data. Once the objectives are found, the data points in the neighborhood of the objective are generated by the simulation tool thus providing a denser coverage of the regions of interest.
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    Exploring Complex Mobile Life through Lightweight Visualizations
    (The Eurographics Association, 2011) Kim, Tanyoung; Blom, Jan; Stasko, John; Silvia Miksch and Giuseppe Santucci
    Smart phones can be used to collect various types of data from a user spanning call and text message logs to GPS coordinates, and to Bluetooth detection. These data are indicative of behavior across various socio-temporalspatial contexts. For the purpose of inspecting the expected and discovering the unexpected from the data, we developed lightweight visualizations with a low cost. The interactive visualizations are customized with each data analysis task and evolved to support emerging diminutive inquiries during the inspection with themselves. By employing this analytic method at the early phase of data-related research projects, the insights can form a ground for subsequent product development activities focusing on engineering, design and market research.
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    Contingency Wheel: Visual Analysis of Large Contingency Tables
    (The Eurographics Association, 2011) Alsallakh, Bilal; Groeller, Eduard; Miksch, Silvia; Suntinger, Martin; Silvia Miksch and Giuseppe Santucci
    We present the Contingency Wheel, a visual method for finding and analyzing associations in a large nxm contingency table with m less than 100 and n being two to three orders of magnitude larger than m. The method is demonstrated on a large table from the Book-Crossing dataset, which counts the number of ratings each book received from each country. It enables finding books that received a disproportionately high number of ratings from a specific country. It further allows to visually analyze what these books have in common, and with which countries they are also highly associated. Pairs of similar countries can further be identified (in the sense that many books are associated with both countries). Compared with existing visual methods, our approach enables analyzing and gaining insight into larger tables.
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    Steerable Clustering for Visual Analysis of Ecosystems
    (The Eurographics Association, 2011) Ahmed, Zafar; Yost, Patrick; McGovern, Amy; Weaver, Chris; Silvia Miksch and Giuseppe Santucci
    One of the great challenges in the geosciences is understanding ecological systems in order to predict changes and responses in space and time at scales from local to global. Ecologists are starting to recognize the value of analysis methods that go beyond statistics to include data mining, visual representations, and combinations of these in computational tools. However, the tools in use today rarely provide means to perform the kinds of rich multidimensional interaction that hold promise to greatly expand possibilities for effective visual exploration and analysis. As part of a project to develop a cyberCommons for collaborative ecological forecasting, we are developing ways to integrate highly interactive visual analysis techniques with data mining algorithms. We describe here our work in progress on steering mixed-dimensional KD-KMeans clustering using multiple coordinated views. Contributions include more flexible interactive control over clustering inputs and outputs, greater consistency of cluster membership during interaction, and higher performance by caching cluster results as a function of interactive state. We present our current tool that implements these improvements for visual analysis of Terrestrial ECOsystem (TECO) data collected from FLUXNET towers, with feedback on utility from our ecologist collaborators.