Michael Smuc

Hierarchical Temporal Patterns and Interactive Aggregated Views for Pixel-Based Visualizations

Many real-world problems involve time-oriented data. Time data is different from other kinds of data--explicitly harnessing the structures of time in visualizations can guide and support users’ visual analysis processes. State-of-the-art visualizations hardly take advantage of the structures of time to aid users in understanding and exploring the data. To bring more flexibility to the analysis process, we have developed interactive visual methods incorporating the structures of time within a pixel-based visualization called GROOVE (granular overview overlay). GROOVE uses different techniques to visualize time-oriented data by overlaying several time granularities in one visualization and provides interactive operators, which utilize the structures of time in different ways to capture and explore time-oriented data.

The User Puzzle—Explaining the Interaction with Visual Analytics Systems

Visual analytics emphasizes the interplay between visualization, analytical procedures performed by computers and human perceptual and cognitive activities. Human reasoning is an important element in this context. There are several theories in psychology and HCI explaining open-ended and exploratory reasoning. Five of these theories (sensemaking theories, gestalt theories, distributed cognition, graph comprehension theories and skill-rule-knowledge models) are described in this paper. We discuss their relevance for visual analytics. In order to do this more systematically, we developed a schema of categories relevant for visual analytics research and evaluation. All these theories have strengths but also weaknesses in explaining interaction with visual analytics systems. A possibility to overcome the weaknesses would be to combine two or more of these theories.

A User-Centered Design Approach to Self-Service Ticket Vending Machines

Since their introduction, self-service ticket vending machines (TVMs) have become an increasingly important distribution channel in the public transport sector, progressively replacing the traditional ticket counter. In a public transport setting, where ticket counter closures have left different groups of people dependent on TVM to meet their mobility needs, a single, effective system is required. Research questions: (1) Which barriers do currently hinder the usage of TVM? (2) Which requirements should a barrier-free TVM fulfill? (3) How can we design a new self-service TVM for a nationwide public railway company? (4) How can we ensure that the usability and user experience (UX) is high for all users, especially for those with low levels of technological affinity? Situating the case: Most other studies on the use and usability of TVMs were conducted as post-hoc evaluations. In contrast, our case study presents a user-centered design (UCD) approach that takes the needs of the different target groups into account throughout the whole development process. Theories and concepts that guided the case included UCD, which involves alternating test and evaluation loops that actively involve users to create a usable product and UX, which describes the quality of the experience a person has when interacting with a specific computer system using a specific interaction technique. Methodology: More than 250 participants were involved in focus groups, observations, interviews, and experiments from the very first stages of development. Interface designs were presented to the future end users to obtain their feedback, with the results fed back into the design process. About the case: A prototype for a novel generation of TVM was developed in three phases: First, the context of use was analyzed. In the second phase, we conducted a requirements analysis. Third, different hardware and software interaction designs were iteratively tested and evaluated. The resulting prototype met the requirements of most user groups, though further adjustments are necessary. Conclusions: The UCD approach proved to be a valuable framework for the development and design of self-service systems.

Many roads lead to Rome: mapping users' problem-solving strategies

There is more than one path to a solution, especially when it comes to ill-defined problems like complex, real-world tasks. Until now, the evaluation of information visualizations has often been restricted simply to a measuring of outcomes (time and error) or insights into the data set. A more detailed look into the processes that facilitate or hinder task completion is provided by analysing user problem-solving strategies. The study presented in this paper illustrates how such processes can be assessed and how the resulting knowledge can be used in participatory design to improve a visual analytics tool. For users to be equipped with a problem-solving scaffold, the tools used should allow them to choose their own path to the solution – their own route to Rome. We also discuss how the evaluation of problem-solving strategies can shed more light on the ‘exploratory minds’ of users.

Pep Up Your Time Machine: Recommendations for the Design of Information Visualizations of Time-Dependent Data

Representing time-dependent data plays an important role in information visualization. Time presents specific challenges for the representation of data because time is a complex and highly abstract concept. Basically, there are two ways to support reasoning about time: time can be represented by space, and time can also be represented by time (animation). From the point of view of the users, both forms of representation have their strengths and weaknesses which we will illustrate in this chapter. In recent years, a large number of visualizations has been developed to solve the problem of representing time-dependent data. Nevertheless, it is still not clear which types of visualizations support the cognitive processes of the users. It is necessary to investigate the interactions of real users with visualizations to clarify this issue. The following chapter will give an overview of empirical evaluations and recommendations for the design of visualizations for time-dependent data.

Visualizations at First Sight: Do Insights Require Training?

Understanding novel visualizations can be a challenge even forexperienced users. During iterative usability engineering phases inthe DisCō project, visualizations of time-oriented data areexplored by domain experts and non-experts. The aim of our study isto analyze the generation of knowledge and understanding by meansof visualizations without previous user training. Focusing onapplicability in various business domains for personnel planningand time scheduling, we tested mockups of visualizations with amethod based on user-reported insights. Results show almostidentical behavior of domain experts and non-experts whengenerating insights into the data from scratch. In the course ofworking with a visualization, an interchange of insights into thevisualization and insights into the data was found.

How Do You Connect Moving Dots? Insights from User Studies on Dynamic Network Visualizations

In recent years, the analysis of dynamic network data has become an increasingly prominent research issue. While several visual analytics techniques with the focus on the examination of temporal evolving networks have been proposed in recent years, their effectiveness and utility for end users need to be further analyzed. When dealing with techniques for dynamic network analysis, which integrate visual, computational, and interactive components, users become easily overwhelmed by the amount of information displayed—even in case of small sized networks. Therefore we evaluated visual analytics techniques for dynamic networks during their development, performing intermediate evaluations by means of mock-up and eye-tracking studies and a final evaluation of the running interactive prototype, traceing three pathways of development in detail: The first one focused on the maintenance of the user’s mental map throughout changes of network structure over time, changes caused by user interactions, and changes of analytical perspectives. The second one addresses the avoidance of visual clutter, or at least its moderation. The third pathway of development follows the implications of unexpected user behaviour and multiple problem solving processes. Aside from presenting solutions based on the outcomes of our evaluation, we discuss open and upcoming problems and set out new research questions.

Vertigo zoom: combining relational and temporal perspectives on dynamic networks

A well-designed visualization of dynamic networks has to support the analysis of both temporal and relational features at once. In particular to solve complex synoptic tasks, the users need to understand the topological structure of the network, its evolution over time, and possible interdependencies. In this paper, we introduce the application of the vertigo zoom interaction technique, derived from filmmaking, to information visualizations. When applied to a two-and-a-half-dimensional view, this interaction technique enables smooth transitions between the relational perspective (node-link diagrams and scatter plots) and the time perspective (trajectories and line charts), supporting a seamless visual analysis and preserving the users mental map.

Is your user hunting or gathering insights?: identifying insight drivers across domains

In recent years, using the number of insights to benchmark visual analytics tools has become a prominent method in the Infovis community. The insight methodology has become a frequently used instrument to measure the performance of tools that are developed for highly specialized purposes for highly specialized domain-experts. But some tools have a wider target group of experts with knowledge in different domains. The utility of the insight-method for other expert user groups without specific domain knowledge has been addressed to a far lesser extent. In a case study we give an illustration of how and where insights from experts with and without domain knowledge differ, and how these findings might enrich the evaluation of visualization tools designed for usage across different domains.

Just the other side of the coin? From error to insight analysis

To shed more light on data explorers dealing with complex information visualizations in real-world scenarios, new methodologies and models are needed which overcome existing explanatory gaps. Therefore, a novel model to analyze users’ errors and insights is outlined that is derived from Rasmussen’s model on different levels of cognitive processing, and integrates explorers’ skills, schemes, and knowledge (skill–rule–knowledge model). After locating this model in the landscape of theories for visual analytics, the main building blocks of the model, where three cognitive processing levels are interlinked, are described in detail. A case study illustrates how the cognitive processing efforts can be identified from triangulated eye-tracking and think-aloud data. Finally, the model’s applicability, challenges in measurement, and future research options are discussed.