PLATO: understanding gameplay data through visualization

Günter Wallner; Simone Kriglstein

PLATO: understanding gameplay data through visualization

Günter Wallner
, Simone Kriglstein

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

With the increasing popularity of instrumentation to automatically collect gameplay data the need for adequate analysis tools to fully capitalize on the data has arisen.This includes techniques to visually explore the usually large multivariate data sets. In this paper we describe ongoing work on our spatiotemporal visual analytics system – called PLATO – which currently focuses on providing different representations and methods in order to support analytical reasoning.

Original language	English
Title of host publication	CHI 2013 Games User Research: Practice, methods and applications
Editors	Pejman Mirza-Babael, Veronica Zammitto, Joerg Niesenhaus, Mirweis Sangin, Lennart E. Nacke
Publisher	Association for Computing Machinery, Inc.
Number of pages	5
ISBN (Electronic)	978-1-4503-1952-2
Publication status	Published - 2013
Externally published	Yes
Event	CHI 2013 Games User Research: Practice, methods and applications - Paris, France Duration: 27 Apr 2013 → 2 May 2013 http://gur.hcigames.com/wp-content/uploads/2015/02/2013-Extended-Abstract1.pdf

Workshop

Workshop	CHI 2013 Games User Research: Practice, methods and applications
Abbreviated title	CHI2013
Country/Territory	France
City	Paris
Period	27/04/13 → 2/05/13
Internet address	http://gur.hcigames.com/wp-content/uploads/2015/02/2013-Extended-Abstract1.pdf

Keywords

Game Metrics
Visual Analytics
Gameplay Visualization

Cite this

@inproceedings{1b371fed418e4a7898efb75c1d4648b1,

title = "PLATO: understanding gameplay data through visualization",

abstract = "With the increasing popularity of instrumentation to automatically collect gameplay data the need for adequate analysis tools to fully capitalize on the data has arisen.This includes techniques to visually explore the usually large multivariate data sets. In this paper we describe ongoing work on our spatiotemporal visual analytics system {\textendash} called PLATO {\textendash} which currently focuses on providing different representations and methods in order to support analytical reasoning.",

keywords = "Game Metrics, Visual Analytics, Gameplay Visualization",

author = "G{\"u}nter Wallner and Simone Kriglstein",

year = "2013",

language = "English",

editor = "Pejman Mirza-Babael and Veronica Zammitto and Joerg Niesenhaus and Mirweis Sangin and Nacke, \{Lennart E.\}",

booktitle = "CHI 2013 Games User Research: Practice, methods and applications",

publisher = "Association for Computing Machinery, Inc.",

address = "United States",

note = "CHI 2013 Games User Research: Practice, methods and applications, CHI2013 ; Conference date: 27-04-2013 Through 02-05-2013",

url = "http://gur.hcigames.com/wp-content/uploads/2015/02/2013-Extended-Abstract1.pdf",

}

PLATO: understanding gameplay data through visualization. / Wallner, Günter; Kriglstein, Simone.
CHI 2013 Games User Research: Practice, methods and applications. ed. / Pejman Mirza-Babael; Veronica Zammitto; Joerg Niesenhaus; Mirweis Sangin; Lennart E. Nacke. Association for Computing Machinery, Inc., 2013.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - PLATO: understanding gameplay data through visualization

AU - Wallner, Günter

AU - Kriglstein, Simone

PY - 2013

Y1 - 2013

N2 - With the increasing popularity of instrumentation to automatically collect gameplay data the need for adequate analysis tools to fully capitalize on the data has arisen.This includes techniques to visually explore the usually large multivariate data sets. In this paper we describe ongoing work on our spatiotemporal visual analytics system – called PLATO – which currently focuses on providing different representations and methods in order to support analytical reasoning.

AB - With the increasing popularity of instrumentation to automatically collect gameplay data the need for adequate analysis tools to fully capitalize on the data has arisen.This includes techniques to visually explore the usually large multivariate data sets. In this paper we describe ongoing work on our spatiotemporal visual analytics system – called PLATO – which currently focuses on providing different representations and methods in order to support analytical reasoning.

KW - Game Metrics

KW - Visual Analytics

KW - Gameplay Visualization

M3 - Conference contribution

BT - CHI 2013 Games User Research: Practice, methods and applications

A2 - Mirza-Babael, Pejman

A2 - Zammitto, Veronica

A2 - Niesenhaus, Joerg

A2 - Sangin, Mirweis

A2 - Nacke, Lennart E.

PB - Association for Computing Machinery, Inc.

T2 - CHI 2013 Games User Research: Practice, methods and applications

Y2 - 27 April 2013 through 2 May 2013

ER -

PLATO: understanding gameplay data through visualization

Abstract

Workshop

Keywords

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Cite this