Günter Wallner

A visualization approach for difference analysis of process models and instance traffic

Organizations are often confronted with the task to identify differences and commonalities between process models but also between the instance traffic that presents how instances have progressed through the model. The use cases range from comparison of process variants in order to identify redundancies and inconsistencies between them to the analysis of instance traffic for the (re)design of models. Visualizations can support users in their analysis tasks, e.g., to see if and how the models and their instance traffic have changed. In this paper we present a visualization approach to highlight the differences and commonalities between two models and --- if available --- their instance traffic.

Visualization-based analysis of gameplay data – A review of literature ☆

Abstract As video games are becoming more and more complex and are reaching a broader audience, there is an increasing interest in procedures to analyze player behavior and the impact of design decisions. Game companies traditionally relied on user-testing methods, like playtesting, surveys or videotaping, to obtain player feedback. However, these qualitative methods for data collection are time-consuming and the obtained data is often incomplete or subjective. Therefore, instrumentation became popular in recent years to unobtrusively obtain the detailed data required to thoroughly evaluate player behavior. To make sense of the large amount of data, appropriate tools and visualizations have been developed. This article reviews literature on visualization-based analysis of game metric data in order to give an overview of the current state of this emerging field of research. We discuss issues related to gameplay analysis, propose a broad categorization of visualization techniques and discuss their characteristics. Furthermore, we point out open problems to promote future research in this area.

A spatiotemporal visualization approach for the analysis of gameplay data

Contemporary video games are highly complex systems with many interacting variables. To make sure that a game provides a satisfying experience, a meaningful analysis of gameplay data is crucial, particularly because the quality of a game directly relates to the experience a user gains from playing it. Automatic instrumentation techniques are increasingly used to record data during playtests. However, the evaluation of the data requires strong analytical skills and experience. The visualization of such gameplay data is essentially an information visualization problem, where a large number of variables have to be displayed in a comprehensible way in order to be able to make global judgments. This paper presents a visualization tool to assist the analytical process. It visualizes the game space as a set of nodes which players visit over the course of a game and is also suitable to observe time-dependent information, such as player distribution. Our tool is not tailored to a specific type of genre. To show the flexibility of our approach we use two different kinds of games as case studies.

Technical Section: PLATO: A visual analytics system for gameplay data

During the last decade the game industry has evolved into a highly competitive market. This has prompted game developers to seek ways to increase the quality of their games which in turn is, to a large extent, dependent on the quality of the player experience. In addition to adapting qualitative evaluation methods, developers have therefore started to use instrumentation techniques to unobtrusively collect large amounts of data of player behavior over time. This creates the need for adequate analysis tools in order to explore and make sense of the data. In this paper we present PLATO, a visual analytics system for time-dependent and multidimensional gameplay data. Gameplay is formally represented as a graph which gives us the advantage of a general representation and makes the tool applicable to a wide variety of games. Moreover, doing so enables us to draw upon a large number of graph algorithms. PLATO integrates techniques for subgraph matching, pathfinding, data comparison, and clustering as well as several visualization techniques. We demonstrate the utility of our system by analyzing real world data from a massively multiplayer online role-playing game, a team-based first person shooter, a puzzle game, and a platformer.

Knoocks - A Visualization Approach for OWL Lite Ontologies

With increasing popularity of ontologies in various communities, visualizations of their content and structure became more and more important. In the past few years a number of visualization approaches were developed with the focus either on the representation of the relationships between classes or on the hierarchical structure and instances. However for several applications, a visualization which combines information about instances, classes and hierarchical as well as non-hierarchical relationships is from interest. In this paper we present Knoocks (Knowledge Blocks), which is a visualization approach with focus on both the interconnections within the ontology and the instances in conjunction with their hierarchical structure.

Human Centered Design in Practice: A Case Study with the Ontology Visualization Tool Knoocks

Ontologies make it possible to understand, analyze, exchange or share knowledge of a specific domain and therefore they are becoming popular in various communities. However, ontologies can be very complex and therefore visualizations can support users to understand the ontology easier. Moreover, graphical representations make ontologies with their structure more manageable. For an effective visualization, it is necessary to consider the domain for which the ontology is developed and its users with their needs and expectations. This paper presents the development process of Knoocks (Knowledge Blocks) - a visualization tool for OWL Lite ontologies - which was implemented with the help of the human centered design process. The presented case study underlies the importance of repeated usability evaluations during the development process to identify weak points of the design and missing features which are relevant for the intended users.

Design and evaluation of the educational game DOG eometry : a case study

Educational games have the potential to engage students deeply with a particular topic, because they allow children to actively participate in the learning process rather than just being passive observers. However, the design of educational games can be challenging because serious objectives have to be brought in line with a satisfying gameplay experience. Furthermore, great care has to be taken that the usability of the game does not interfere with the underlying educational goals. This paper discusses the design of DOGeometry, a learning game which combines problem-solving tasks with artistic expression to teach elementary school children the basics of geometric transformations. We evaluated the game design by observing children and automatically logging all user events and report the insights which we gained from analyzing the gathered data not only by statistical means but also through visualizations of gameplay data. The visualizations proved to be extremely helpful to look behind the numbers and to explore the player behavior in more detail.

DOG eometry : teaching geometry through play

This paper describes the evaluation of DOGeometry, an educational game which combines problem-solving tasks with artistic expression to teach concepts of transformation geometry. In contrast to many other educational games in this domain, the game does not use abstract figures but objects from nature to awake childrens interest. Results of the study reveal that the game has been to some extent successful to teach the concepts to the intended age group of 8- to 10-year-old children. Visualizations of automatically tracked gameplay data make a compelling argument for not only considering the learning outcomes but to also observe the intermediate processes to obtain a more thorough understanding of player behavior.

A user study of different gameplay visualizations

With the rising interest in multiplayer gaming, gameplay statistics have become an increasingly important aspect of the overall game experience for many players. As a part of this trend, visualizations have gained great popularity among players, in particular heatmaps since they allow them to reenact the course of a game and to develop new strategies. In this paper we report results of a user study conducted with 29 players (i) to investigate how players use heatmaps and two further graphical representations that use clustering algorithms to interpret gameplay and (ii) to assess the three representations in regard to time efficiency, correctness, suitability, and player preference. Our results show that heatmaps were mainly used to detect hot spots while the cluster representations proved useful to compare variables, allowing the players to uncover relationships between them and in turn allowing a deeper insight into the gameplay data.

Integrating and Inspecting Combined Behavioral Profiling and Social Network Models in Destiny

In this paper two key venues of investigation in game analytics are combined: behavioral profiling and social network analysis. Both venues of research are well developed but combined they permit pattern evaluation across player performance and networks. Here, competitive networks covering almost 3.5 million players of the hybrid online shooter game Destiny are developed and combined with behavioral profiles based on match performance metrics and defined using archetypal analysis. The profiles are embedded in the networks along with other performance indicators for Destiny players. The social behavior of different archetypes is described. Network visualizations are presented which target the problem of making dense networked results actionable.