Exploring Big Data Landscapes with Elastic Displays
Dietrich Kammer, Mandy Keck, Mathias Müller, Thomas Gründer, Rainer Groh: Exploring Big Data Landscapes with Elastic Displays. Mensch und Computer 2017 – Workshopband. Regensburg: Gesellschaft für Informatik e.V., Oldenbourg Verlag, Regensburg, Germany, 2017.
Abstract
In this paper, we propose a concept to help data analysts to quickly assess parameters and results of cluster algorithms. The presentation and interaction on a flexible display makes it possible to grasp the functioning of algorithms and focus on the data itself. Two interaction concepts are presented, which demonstrate the strength of elastic displays: a layer concept that allows the recognition of differences between various parameter settings of cluster algorithms, and a Zoomable User Interface, which encourages the in-depth analysis of clusters.
@conference{BDL_MUC,
title = {Exploring Big Data Landscapes with Elastic Displays},
author = {Dietrich Kammer and Mandy Keck and Mathias Müller and Thomas Gründer and Rainer Groh},
editor = {Burghardt, M., Wimmer, R., Wolff, C. & Womser-Hacker, C. },
url = {http://dl.mensch-und-computer.de/handle/123456789/5378},
year = {2017},
date = {2017-09-10},
booktitle = { Mensch und Computer 2017 – Workshopband. Regensburg: Gesellschaft für Informatik e.V.},
publisher = {Oldenbourg Verlag},
address = {Regensburg, Germany},
abstract = {In this paper, we propose a concept to help data analysts to quickly assess parameters and results of cluster algorithms. The presentation and interaction on a flexible display makes it possible to grasp the functioning of algorithms and focus on the data itself. Two interaction concepts are presented, which demonstrate the strength of elastic displays: a layer concept that allows the recognition of differences between various parameter settings of cluster algorithms, and a Zoomable User Interface, which encourages the in-depth analysis of clusters.},
keywords = {Elastic Displays, Information Visualization},
pubstate = {published},
tppubtype = {conference}
}
Exploring Big Data Landscapes with Elastic Displays
Abstract
In this paper, we propose a concept to help data analysts to quickly assess parameters and results of cluster algorithms. The presentation and interaction on a flexible display makes it possible to grasp the functioning of algorithms and focus on the data itself. Two interaction concepts are presented, which demonstrate the strength of elastic displays: a layer concept that allows the recognition of differences between various parameter settings of cluster algorithms, and a Zoomable User Interface, which encourages the in-depth analysis of clusters.
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BibTeX (Download)
@conference{BDL_MUC, title = {Exploring Big Data Landscapes with Elastic Displays}, author = {Dietrich Kammer and Mandy Keck and Mathias Müller and Thomas Gründer and Rainer Groh}, editor = {Burghardt, M., Wimmer, R., Wolff, C. & Womser-Hacker, C. }, url = {http://dl.mensch-und-computer.de/handle/123456789/5378}, year = {2017}, date = {2017-09-10}, booktitle = { Mensch und Computer 2017 – Workshopband. Regensburg: Gesellschaft für Informatik e.V.}, publisher = {Oldenbourg Verlag}, address = {Regensburg, Germany}, abstract = {In this paper, we propose a concept to help data analysts to quickly assess parameters and results of cluster algorithms. The presentation and interaction on a flexible display makes it possible to grasp the functioning of algorithms and focus on the data itself. Two interaction concepts are presented, which demonstrate the strength of elastic displays: a layer concept that allows the recognition of differences between various parameter settings of cluster algorithms, and a Zoomable User Interface, which encourages the in-depth analysis of clusters.}, keywords = {Elastic Displays, Information Visualization}, pubstate = {published}, tppubtype = {conference} }