Exploring Big Data Landscapes with Elastic Displays.

Dietrich Kammer; Mandy Keck; Mathias Müller; Thomas Gründer; Rainer Groh

doi:10.18420/MUC2017-WS08-0342

Exploring Big Data Landscapes with Elastic Displays.

Dietrich Kammer, Mandy Keck, Mathias Müller, Thomas Gründer, Rainer Groh

Research output: Contribution to conference › Paper › peer-review

3 Citations (Scopus)

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.

Original language	English
Pages	381-387
Number of pages	7
DOIs	https://doi.org/10.18420/MUC2017-WS08-0342
Publication status	Published - 2017
Externally published	Yes
Event	Fachtagung Mensch und Computer 2017 - Regensburg, Germany Duration: 10 Sept 2017 → 13 Sept 2017 http://muc2017.mensch-und-computer.de/

Conference

Conference	Fachtagung Mensch und Computer 2017
Country/Territory	Germany
City	Regensburg
Period	10.09.2017 → 13.09.2017
Internet address	http://muc2017.mensch-und-computer.de/

Keywords

elastic displays
information visualization
Glyph-based Visualization Techniques
dimensionality reduction

Access to Document

10.18420/MUC2017-WS08-0342

https://dblp.org/rec/conf/mc/KammerKMGG17

Cite this

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title = "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.",

keywords = "elastic displays, information visualization, Glyph-based Visualization Techniques, dimensionality reduction",

author = "Dietrich Kammer and Mandy Keck and Mathias M{\"u}ller and Thomas Gr{\"u}nder and Rainer Groh",

note = "Funding Information: Acknowledgements. On behalf of Dietrich Kammer, Mandy Keck and Thomas Gr{\"u}nder, this research (project no. 100238473) has been funded by the European Regional Development Fund and the Free State of Saxony. On behalf of Mathias M{\"u}ller, this research (project no. 100271686) has been funded by the European Social Fund and the Free State of Saxony. Publisher Copyright: Copyright (C) 2017 bei den Autoren.; Fachtagung Mensch und Computer 2017 ; Conference date: 10-09-2017 Through 13-09-2017",

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doi = "10.18420/MUC2017-WS08-0342",

language = "English",

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AU - Kammer, Dietrich

AU - Keck, Mandy

AU - Müller, Mathias

AU - Gründer, Thomas

AU - Groh, Rainer

N1 - Funding Information: Acknowledgements. On behalf of Dietrich Kammer, Mandy Keck and Thomas Gründer, this research (project no. 100238473) has been funded by the European Regional Development Fund and the Free State of Saxony. On behalf of Mathias Müller, this research (project no. 100271686) has been funded by the European Social Fund and the Free State of Saxony. Publisher Copyright: Copyright (C) 2017 bei den Autoren.

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

KW - elastic displays

KW - information visualization

KW - Glyph-based Visualization Techniques

KW - dimensionality reduction

UR - https://www.scopus.com/pages/publications/85138795244

U2 - 10.18420/MUC2017-WS08-0342

DO - 10.18420/MUC2017-WS08-0342

M3 - Paper

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EP - 387

T2 - Fachtagung Mensch und Computer 2017

Y2 - 10 September 2017 through 13 September 2017

ER -

Exploring Big Data Landscapes with Elastic Displays.

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Keywords

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