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Hans-Jörg Schulz

Model-Driven Design for the Visual Analysis of Heterogeneous Data

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Standard

Model-Driven Design for the Visual Analysis of Heterogeneous Data. / Streit, Marc; Schulz, Hans-Jörg; Lex, Alexander; Schmalstieg, Dieter; Schumann, Heidrun.

In: IEEE Transactions on Visualization and Computer Graphics, Vol. 18, No. 6, 2012, p. 998-1010.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

Streit, M, Schulz, H-J, Lex, A, Schmalstieg, D & Schumann, H 2012, 'Model-Driven Design for the Visual Analysis of Heterogeneous Data', IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 6, pp. 998-1010. https://doi.org/10.1109/TVCG.2011.108

APA

Streit, M., Schulz, H-J., Lex, A., Schmalstieg, D., & Schumann, H. (2012). Model-Driven Design for the Visual Analysis of Heterogeneous Data. IEEE Transactions on Visualization and Computer Graphics, 18(6), 998-1010. https://doi.org/10.1109/TVCG.2011.108

CBE

Streit M, Schulz H-J, Lex A, Schmalstieg D, Schumann H. 2012. Model-Driven Design for the Visual Analysis of Heterogeneous Data. IEEE Transactions on Visualization and Computer Graphics. 18(6):998-1010. https://doi.org/10.1109/TVCG.2011.108

MLA

Streit, Marc et al. "Model-Driven Design for the Visual Analysis of Heterogeneous Data". IEEE Transactions on Visualization and Computer Graphics. 2012, 18(6). 998-1010. https://doi.org/10.1109/TVCG.2011.108

Vancouver

Streit M, Schulz H-J, Lex A, Schmalstieg D, Schumann H. Model-Driven Design for the Visual Analysis of Heterogeneous Data. IEEE Transactions on Visualization and Computer Graphics. 2012;18(6):998-1010. https://doi.org/10.1109/TVCG.2011.108

Author

Streit, Marc ; Schulz, Hans-Jörg ; Lex, Alexander ; Schmalstieg, Dieter ; Schumann, Heidrun. / Model-Driven Design for the Visual Analysis of Heterogeneous Data. In: IEEE Transactions on Visualization and Computer Graphics. 2012 ; Vol. 18, No. 6. pp. 998-1010.

Bibtex

@article{17a5ad71ca544a2aa2ba542bbb8ccb62,
title = "Model-Driven Design for the Visual Analysis of Heterogeneous Data",
abstract = "As heterogeneous data from different sources is being increasingly linked, it becomes difficult for users to understand how the data is connected, to identify what means are suitable to analyze a given data set, or to find out how to proceed for a given analysis task. We target this challenge with a new model-driven design process that effectively co-designs aspects of data, view, analytics and tasks. We achieve this by using the workflow of the analysis task as a trajectory through data, interactive views and analytical processes. The benefits for the analysis session go well beyond the pure selection of appropriate data sets and range from providing orientation or even guidance along a preferred analysis path to a potential overall speed-up, allowing data to be fetched ahead of time. We illustrate the design process for a biomedical use case that aims at determining a treatment plan for cancer patients from the visual analysis of a large, heterogeneous clinical data pool. As an example for how to apply the comprehensive design approach, we present Stackʼn'flip, a sample implementation which tightly integrates visualizations of the actual data with a map of available data sets, views and tasks, thus capturing and communicating the analytical workflow through the required data sets.",
author = "Marc Streit and Hans-J{\"o}rg Schulz and Alexander Lex and Dieter Schmalstieg and Heidrun Schumann",
year = "2012",
doi = "10.1109/TVCG.2011.108",
language = "English",
volume = "18",
pages = "998--1010",
journal = "I E E E Transactions on Visualization and Computer Graphics",
issn = "1077-2626",
publisher = "Institute of Electrical and Electronics Engineers",
number = "6",

}

RIS

TY - JOUR

T1 - Model-Driven Design for the Visual Analysis of Heterogeneous Data

AU - Streit, Marc

AU - Schulz, Hans-Jörg

AU - Lex, Alexander

AU - Schmalstieg, Dieter

AU - Schumann, Heidrun

PY - 2012

Y1 - 2012

N2 - As heterogeneous data from different sources is being increasingly linked, it becomes difficult for users to understand how the data is connected, to identify what means are suitable to analyze a given data set, or to find out how to proceed for a given analysis task. We target this challenge with a new model-driven design process that effectively co-designs aspects of data, view, analytics and tasks. We achieve this by using the workflow of the analysis task as a trajectory through data, interactive views and analytical processes. The benefits for the analysis session go well beyond the pure selection of appropriate data sets and range from providing orientation or even guidance along a preferred analysis path to a potential overall speed-up, allowing data to be fetched ahead of time. We illustrate the design process for a biomedical use case that aims at determining a treatment plan for cancer patients from the visual analysis of a large, heterogeneous clinical data pool. As an example for how to apply the comprehensive design approach, we present Stackʼn'flip, a sample implementation which tightly integrates visualizations of the actual data with a map of available data sets, views and tasks, thus capturing and communicating the analytical workflow through the required data sets.

AB - As heterogeneous data from different sources is being increasingly linked, it becomes difficult for users to understand how the data is connected, to identify what means are suitable to analyze a given data set, or to find out how to proceed for a given analysis task. We target this challenge with a new model-driven design process that effectively co-designs aspects of data, view, analytics and tasks. We achieve this by using the workflow of the analysis task as a trajectory through data, interactive views and analytical processes. The benefits for the analysis session go well beyond the pure selection of appropriate data sets and range from providing orientation or even guidance along a preferred analysis path to a potential overall speed-up, allowing data to be fetched ahead of time. We illustrate the design process for a biomedical use case that aims at determining a treatment plan for cancer patients from the visual analysis of a large, heterogeneous clinical data pool. As an example for how to apply the comprehensive design approach, we present Stackʼn'flip, a sample implementation which tightly integrates visualizations of the actual data with a map of available data sets, views and tasks, thus capturing and communicating the analytical workflow through the required data sets.

U2 - 10.1109/TVCG.2011.108

DO - 10.1109/TVCG.2011.108

M3 - Journal article

C2 - 21690642

VL - 18

SP - 998

EP - 1010

JO - I E E E Transactions on Visualization and Computer Graphics

JF - I E E E Transactions on Visualization and Computer Graphics

SN - 1077-2626

IS - 6

ER -