Interactive Integrated Exploration and Management of Visualization Parameters

Information

• Publication Type: PhD-Thesis
• Workgroup(s)/Project(s):
  • ViMaL: A Visualization Mapping Language
• Date: 2015
• Date (Start): October 2011
• Date (End): June 2015
• 1st Reviewer: Stefan Bruckner
• 2nd Reviewer: Eduard Gröller
• Rigorosum: 30. June 2015
• First Supervisor: Stefan Bruckner

Abstract

Visualization algorithms are parameterized to offer universality in terms of handling various data types, showing different aspects of the visualized data, or producing results useful for domain experts from different fields. Hence, input parameters are an important aspect of the visualization process. Their exploration and management are tasks which enable the visualization reusability, portability, and interdisciplinary communication.

With increasing availability of visualization systems, which are suitable for a great variety of tasks, their complexity increases as well. This usually involves many input parameters necessary for the meaningful visualization of data. Multiple input parameters form parameter spaces which are too large to be explored by brute-force. Knowing the properties of a parameter space is often beneficial for improving data visualization. Therefore, it is important for domain experts utilizing data visualization to have tools for automatic parameter specification and for aiding the manual parameter setting.

In this thesis, we review existing approaches for parameter-space visualization, exploration, and management. These approaches are used with a great variety of underlying algorithms. We focus on their applicability to visualization algorithms. We propose three methods solving specific problems arising from the fact that the output of a visualization algorithm is an image, which is challenging to process automatically and often needs to be analyzed by a human.

First, we propose a method for the exploration of parameter-spaces of visualization algorithms. The method is used to understand effects of combinations of parameters and parts of the internal structure of the visualization algorithms on the final image result. The exploration is carried out by specifying semantics for localized parts of the visualization images in the form of positive and negative examples influenced by a set of input parameters or parts of the visualization algorithm itself. After specifying the localized semantics, global effects of the specified components of the visualization algorithm can be observed. The method itself is independent from the underlying algorithm.

Subsequently, we present a method for managing image-space selections in visualizations and automatically link them with the context in which they were created. The context is described by the values of the visualization parameters influencing the output image. The method contains a mechanism for linking additional views to the selections, allowing the user an effective management of the visualization parameters whose effects are localized to certain areas of the visualizations. We present various applications for the method, as well as an implementation in the form of a library, which is ready to be used in existing visualization systems.

Our third method is designed to integrate dynamic parameters stored during a multiplayer video game session by the individual participating players. For each player, the changing parameter values of the game describe their view of the gameplay. Integrating these multiple views into a single continuous visual narrative provides means for effective summarization of gameplays, useful for entertainment, or even gameplay analysis purposes by semi-professional or professional players. We demonstrate the utility of our approach on an existing video game by producing a gameplay summary of a multiplayer game session. The proposed method opens possibilities for further research in the areas of storytelling, or at a more abstract level, parameter integration for visual computing algorithms.

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BibTeX

@phdthesis{mindek-thesis,
  title =      "Interactive Integrated Exploration and Management of
               Visualization Parameters",
  author =     "Peter Mindek",
  year =       "2015",
  abstract =   "Visualization algorithms are parameterized to offer
               universality in terms of handling various data types,
               showing different aspects of the visualized data, or
               producing results useful for domain experts from different
               fields. Hence, input parameters are an important aspect of
               the visualization process. Their exploration and management
               are tasks which enable the visualization reusability,
               portability, and interdisciplinary communication.  With
               increasing availability of visualization systems, which are
               suitable for a great variety of tasks, their complexity
               increases as well. This usually involves many input
               parameters necessary for the meaningful visualization of
               data. Multiple input parameters form parameter spaces which
               are too large to be explored by brute-force. Knowing the
               properties of a parameter space is often beneficial for
               improving data visualization. Therefore, it is important for
               domain experts utilizing data visualization to have tools
               for automatic parameter specification and for aiding the
               manual parameter setting.  In this thesis, we review
               existing approaches for parameter-space visualization,
               exploration, and management. These approaches are used with
               a great variety of underlying algorithms. We focus on their
               applicability to visualization algorithms. We propose three
               methods solving specific problems arising from the fact that
               the output of a visualization algorithm is an image, which
               is challenging to process automatically and often needs to
               be analyzed by a human.  First, we propose a method for the
               exploration of parameter-spaces of visualization algorithms.
               The method is used to understand effects of combinations of
               parameters and parts of the internal structure of the
               visualization algorithms on the final image result. The
               exploration is carried out by specifying semantics for
               localized parts of the visualization images in the form of
               positive and negative examples influenced by a set of input
               parameters or parts of the visualization algorithm itself.
               After specifying the localized semantics, global effects of
               the specified components of the visualization algorithm can
               be observed. The method itself is independent from the
               underlying algorithm.  Subsequently, we present a method for
               managing image-space selections in visualizations and
               automatically link them with the context in which they were
               created. The context is described by the values of the
               visualization parameters influencing the output image. The
               method contains a mechanism for linking additional views to
               the selections, allowing the user an effective management of
               the visualization parameters whose effects are localized to
               certain areas of the visualizations. We present various
               applications for the method, as well as an implementation in
               the form of a library, which is ready to be used in existing
               visualization systems.  Our third method is designed to
               integrate dynamic parameters stored during a multiplayer
               video game session by the individual participating players.
               For each player, the changing parameter values of the game
               describe their view of the gameplay. Integrating these
               multiple views into a single continuous visual narrative
               provides means for effective summarization of gameplays,
               useful for entertainment, or even gameplay analysis purposes
               by semi-professional or professional players. We demonstrate
               the utility of our approach on an existing video game by
               producing a gameplay summary of a multiplayer game session.
               The proposed method opens possibilities for further research
               in the areas of storytelling, or at a more abstract level,
               parameter integration for visual computing algorithms. ",
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2015/mindek-thesis/",
}