Evaluation of Visualization Techniques for Communicating Off-Screen Data

Worldwide, the use of mobile devices like tablets has begun to integrate themselves in people’s daily lives. People have thus begun to bring over desktop applications, more specifically visualization applications, into the mobile atmosphere. However, this brings forth some challenges, like how to manage screen space and how the visualizations should present the relevant information. Our take on this was to use various aggregations that would allow users to see data elements that would otherwise be off-screen. We thought it was best to create a variety of different aggregations, allowing us to figure out the best method of the group. While creating our survey questions however, we realized that it would better suit us to figure out the strengths and weaknesses of each aggregations instead of looking for the best one. Our survey asks a variety of questions to the respondents on various different topics within visualization, so that we can figure out the purpose and best use of each of our aggregations

An Evaluation-Guided Approach for Effective Data Visualization on Tablets

There is a rising trend of data analysis and visualization tasks being performed on a tablet device. Apps with interactive data visualization capabilities are available for a wide variety of domains. We investigate whether users grasp how to effectively interpret and interact with visualizations. We conducted a detailed user evaluation to study the abilities of individuals with respect to analyzing data on a tablet through an interactive visualization app. Based upon the results of the user evaluation, we find that most subjects performed well at understanding and interacting with simple visualizations, specifically tables and line charts. A majority of the subjects struggled with identifying interactive widgets, recognizing interactive widgets with overloaded functionality, and understanding visualizations which do not display data for sorted attributes. Based on our study, we identify guidelines for designers and developers of mobile data visualization apps that include recommendations for effective data representation and interaction

Exploring Spatial Interaction and Visualization Paradigms for 3D Cadastral Visualization

Effective visualization of spatial data, especially in the realm of 3D cadastral visualization, relies on the utilization of optimal interaction techniques and user interfaces for navigating complex datasets and understanding property delineations. This paper synthesizes findings from diverse studies investigating the efficacy of interaction modalities and user interfaces in 3D visualization across various domains. Drawing parallels to the broader field of 3D visualization, particularly in interaction tasks and user interface paradigms, this paper examines the potential for advancing 3D cadastral visualization systems. The study identifies fundamental interaction tasks crucial for effective 3D cadastral visualization, including object manipulation, widget manipulation, and data selection and annotation. It evaluates a range of user interfaces, from traditional input methods to emerging technologies such as gesture-based interfaces and virtual reality (VR) headsets, highlighting their respective strengths and limitations.Embracing insights from comparative analyses of immersive and non-immersive scenarios, this paper reveals significant insights into the effectiveness of immersive environments, such as virtual reality and augmented reality, in enhancing user experience and task performance for 3D cadastral visualization. Additionally, it aims to address key challenges associated with visualizing 3D cadastral data in immersive environments by proposing a comprehensive framework for evaluating the effectiveness and utility of immersive visualization for 3D cadastral purposes

Effects of Different Display Form Factors on InfoVis Applications: Exploring Selection Management and Brushing and Linking for Mobile Cross-Device Interaction

Diese Arbeit untersucht wie man mit mehreren, miteinander koordinierten Mobilgeräten Selektionen verwalten und Brushing und Linking unterstützen kann. Im Rahmen der Arbeit wird ein konzeptionelles Framework zur Selektionsverwaltung für mehrere Geräte angedacht und ein Konzept zur Selektionsverwaltung vorstellt, das Brushing und Linking für Mobilgeräte unterstützt. Des Weiteren werden Ziele für den Prototypen erörtert, die zur Umsetzung das Konzept beitragen. Mobile Geräte werden immer häufiger für Informationsvisualisierungen verwendet. Jedoch wurde bisher noch nicht untersucht, wie gängige Interaktionstechniken, wie Brushing und Linking, für diese Geräte anpassen werden müssen. Während des Brushings, werden zusätzlich Selektionen erstellt, für die es bislang keine Art der Verwaltung für Mobilgeräte gibt. In dieser Arbeit wird untersucht wie man Brushing und Linking mit mehreren Mobilgeräten unterstützen kann und Selektionen gleichzeitig verwalten kann.:1 Introduction 1.1 Contributions 1.2 Motivation and Background 1.3 Goals 1.4 Research Questions 1.5 Thesis Overview 2. Related Work 2.1 Mobile Devices for InfoVis and Their Screen Real Estate Issues 2.2 Interacting with CMVs 2.3 Brushing and Linking 2.4 Summary 3 Selection Management and Brushing and Linking for Mobile Cross- Device Interaction 3.1 The Selection Management Framework 3.2 Fundamental Information About VisTiles 3.3 Design Considerations 3.4 Creating Selections Within a Visualization 3.5 Interacting with Selections Within a Visualization 3.6 Managing Multiple Selections 3.7 Managing a Single Selection 3.8 Linking Selections to Other Devices 3.9 Incorporating Join Operations 3.10 Overview over Side-by-side Interactions 3.11 Summary: Reviewing the Selection Management Framework 4 Prototype 4.1 Technical Setup 4.2 Techniques 5 Conclusion and Discussion 5.1 Discussion 5.2 Future Work 5.3 ConclusionThis thesis examines how to manage selections and use brushing and linking with multiple coordinated mobile devices. We discuss thoughts for a conceptual framework for selection management in multi-device environments. We then present a concept for managing selections and supporting brushing and linking for co-located mobile devices. Finally, we are providing an overview of and the goals for our proof-of-concept prototype. More and more mobile devices are used for visualization. However, it is still an open question how to adjust common interaction techniques, such as brushing and linking, for mobile devices. Furthermore, it has not been addressed how to manage the selections that are created through brushing. We explore how brushing and linking can be used in a setting with multiple, co-located mobile devices and how to manage its selections.:1 Introduction 1.1 Contributions 1.2 Motivation and Background 1.3 Goals 1.4 Research Questions 1.5 Thesis Overview 2. Related Work 2.1 Mobile Devices for InfoVis and Their Screen Real Estate Issues 2.2 Interacting with CMVs 2.3 Brushing and Linking 2.4 Summary 3 Selection Management and Brushing and Linking for Mobile Cross- Device Interaction 3.1 The Selection Management Framework 3.2 Fundamental Information About VisTiles 3.3 Design Considerations 3.4 Creating Selections Within a Visualization 3.5 Interacting with Selections Within a Visualization 3.6 Managing Multiple Selections 3.7 Managing a Single Selection 3.8 Linking Selections to Other Devices 3.9 Incorporating Join Operations 3.10 Overview over Side-by-side Interactions 3.11 Summary: Reviewing the Selection Management Framework 4 Prototype 4.1 Technical Setup 4.2 Techniques 5 Conclusion and Discussion 5.1 Discussion 5.2 Future Work 5.3 Conclusio

Designing and implementing an interactive scatterplot visualization for a tablet computer

Tablet computers now offer screen sizes and computing capabilities that are competitive with traditional desktop PCs. Their popularity has grown tremendously, but we are just beginning to see information visualization applications designed for this platform. One potential reason for this limited development is the challenge of designing and implementing a multi-touch interface for visualizations on mobile, tablet devices. In this work, we identify the primary challenges that touch screen interactions pose for information visualization applications. We explore the design space of multi-touch interactions for visualizations and present a prototype information visualization application using a specific technique, a dynamic scatterplot, for an iPad

"It felt like I was part of the data": Comparing Mouse, Touch, and Physical Interaction with Visualizations

With my two exploratory studies I contribute a deeper understanding of the different experiences people have when manipulating data representations using mouse, touch, and physical interaction. To uncover experiences rather than performance measures I employed two different methodologies in the context of “data connectedness.” My first study used Likert-based questionnaires to determine differences in how connected participants felt to the data they were interacting with. To gain a deeper understanding, my second study employed a word selection activity (using the Desirability Toolkit), which led to much richer data. I found that people associated words like “engaged,” “direct,” and “satisfying” with touch and physical interaction, but often used words like “awkward,” “dull,” and “distant” with the mouse. My findings help to tease apart the characteristics of experienced interaction modalities in relation to how people feel about their connection to the data. Furthermore, my work provides a deeper look into how to measure abstract concepts such as connectedness that are highly elusive but important to understanding why certain ways of interacting with data may be more attractive, more liked, or even more effective

Interações de toque e de caneta para visualizações de dados em tablets

Atualmente, a análise e a manipulação de dados são fundamentais para os trabalhadores do conhecimento. Assim sendo, torna-se crucial desenvolver interações para a visualização de dados, de modo a alavancar as capacidades de análise e a melhorar os fluxos de trabalho. Tais interações podem ser compostas por interações de toque e de caneta. Esta dissertação propõe um método de interação para visualizações de dados: a interação bimanual de toque e de caneta. Para este método de interação foram desenvolvidas quatro ações. Estas ações são reconhecidas por uma aplicação que converte as ações do utilizador em reações nas visualizações de dados. Fez-se um pequeno estudo de bibliotecas de visualização, no qual avaliou-se as bibliotecas amCharts, AnyChart, D3.js, LargeVis e VTK. Este sistema e os métodos de interação desenvolvidos foram alvo de um processo de avaliação, a partir do qual foi possível avaliar a viabilidade deste tipo de interação neste contexto. Foi possível determinar que este tipo de interação é praticamente igual em termos de análise das visualizações, mas que apresenta uma menor usabilidade e um maior tempo para realizar as tarefas, quando comparada com a interação com o rato e o teclado.Nowadays, data analysis and manipulation are fundamental for data analysts and other people that analyse data at their jobs. As such, it becomes crucial to develop interactions for data visualization in such a way that it leverages the capabilities of analysis and increasing workflow. These interactions can be comprised of pen and touch based interactions. This dissertation proposes an interaction method for information visualization: the pen and touch bimanual interaction. For this method of interaction, it was developed four actions. These actions are recognized by an application that converts the actions performed by the user into reactions on the data visualization. Furthermore, a small evaluation of data visualization libraries was conducted, in which the libraries: amCharts, AnyChart, D3.js, LargeVis and VTK were evaluated. The developed system and its interactions underwent a user study, after which it was possible to evaluate the viability of this type of interactions in the context of information visualization. It was possible to determine that this type of interaction is practically the same in the analysis of the data visualizations but has a lower level of usability and an increased time to complete tasks when compared with mouse and keyboard interaction