Silvia Miksch

Visualization of Time-Oriented Data

Time is an exceptional dimension that is common to many application domains such as medicine, engineering, business, or science. Due to the distinct characteristics of time, appropriate visual and analytical methods are required to explore and analyze them. This book starts with an introduction to visualization and historical examples of visual representations. At its core, the book presents and discusses a systematic view of the visualization of time-oriented data along three key questions: what is being visualized (data), why something is visualized (user tasks), and how it is presented (visual representation). To support visual exploration, interaction techniques and analytical methods are required that are discussed in separate chapters. A large part of this book is devoted to a structured survey of 101 different visualization techniques as a reference for scientists conducting related research as well as for practitioners seeking information on how their time-oriented data can best be visualized.

Visualizing time-oriented data-A systematic view

The analysis of time-oriented data is an important task in many application scenarios. In recent years, a variety of techniques for visualizing such data have been published. This variety makes it difficult for prospective users to select methods or tools that are useful for their particular task at hand. In this article, we develop and discuss a systematic view on the diversity of methods for visualizing time-oriented data. With the proposed categorization we try to untangle the visualization of time-oriented data, which is such an important concern in Visual Analytics. The categorization is not only helpful for users, but also for researchers to identify future tasks in Visual Analytics.

Visual Methods for Analyzing Time-Oriented Data

Providing appropriate methods to facilitate the analysis of time-oriented data is a key issue in many application domains. In this paper, we focus on the unique role of the parameter time in the context of visually driven data analysis. We will discuss three major aspects - visualization, analysis, and the user. It will be illustrated that it is necessary to consider the characteristics of time when generating visual representations. For that purpose, we take a look at different types of time and present visual examples. Integrating visual and analytical methods has become an increasingly important issue. Therefore, we present our experiences in temporal data abstraction, principal component analysis, and clustering of larger volumes of time-oriented data. The third main aspect we discuss is supporting user-centered visual analysis. We describe event-based visualization as a promising means to adapt the visualization pipeline to needs and tasks of users.

Semantic depth of field

We present a new technique called Semantic Depth of Field (SDOF) as an alternative approach to focus-and-context displays of information. We utilize a well-known method from photography and cinematography (depth-of-field effect) for information visualization, which is to blur different parts of the depicted scene in dependence of their relevance. Independent of their spatial locations, objects of interest are depicted sharply in SDOF, whereas the context of the visualization is blurred. In this paper, we present a flexible model of SDOF which can be easily adopted to various types of applications. We discuss pros and cons of the new technique, give examples of application, and describe a fast prototype implementation of SDOF.

Connecting time-oriented data and information to a coherent interactive visualization

In modern intensive care units (ICUs), the medical staff has to monitor a huge amount of high-dimensional and time-oriented data, which needs to be visualized user- and task-specifically to ease diagnosis and treatment planning. Available visual representations, like diagrams or charts neglect the implicit information as well as a-priory or associated knowledge about the data and its meaning (for example, 38.5°C (101.3°F) is moderate fever and 41°C (105.8°F) is critical fever). Another challenge is to provide appropriate interaction techniques to explore and navigate the data and its temporal dimensions. In this context one major challenge is to connect time-oriented data and information to a coherent interactive visualization. In this paper we present different interactive visualization techniques which enable the users to reveal the data at several levels of detail and abstraction, ranging from a broad overview to the fine structure. We will also introduce a time visualization and navigation technique that connects overview+detail, pan+zoom, and focus+context features to one powerful time-browser.

Metaphors of movement: a visualization and user interface for time-oriented, skeletal plans

Therapy planning plays an increasingly important role in the everyday work of physicians. Clinical protocols or guidelines are typically represented using flow-charts, decision tables, or plain text. These representations are badly suited, however, for complex medical procedures.One representation method that overcomes these problems is the language Asbru. But because Asbru has a LISP-like syntax (and also incorporates many concepts from computer science), it is not suitable for physicians.Therefore, we developed a visualization and user interface to deal with treatment plans expressed in Asbru. We use graphical metaphors to make the underlying concepts easier to grasp, employ glyphs to communicate complex temporal information and colors to make it possible to understand the connection between the two views (Topological View and Temporal View) available in the system. In this paper, we present the design ideas behind AsbruView, and discuss its usefulness based on the results of a usability study we performed with six physicians.

Interactive Information Visualization to Explore and Query Electronic Health Records

Physicians are confronted with increasingly complex patient histories based on which they must make life-critical treatment decisions. At the same time, clinical researchers are eager to study the growing databases of patient histories to detect unknown patterns, ensure quality control, and discover surprising outcomes. Designers of Electronic Health Record systems (EHRs) have great potential to apply innovative visual methods to support clinical decision-making and research. This work surveys the state-of-the-art of information visualization systems for exploring and querying EHRs, as described in the scientific literature. We examine how systems differ in their features and highlight how these differences are related to their design and the medical scenarios they tackle. The systems are compared on a set of criteria: (1) data types covered, (2) multivariate analysis support, (3) number of patient records used (one or multiple), and (4) user intents addressed. Based on our survey and evidence gained from evaluation studies, we believe that effective information visualization can facilitate analysis of EHRs for patient treatment and clinical research. Thus, we encourage the information visualization community to study the application of their systems in health care. Our monograph is written for both scientific researchers and designers of future user interfaces for EHRs. We hope it will help them understand this vital domain and appreciate the features and virtues of existing systems, so they can create still more advanced systems. We identify potential future research topics in interactive support for data abstraction, in systems for intermittent users, such as patients, and in more detailed evaluations.

PlanningLines: novel glyphs for representing temporal uncertainties and their evaluation

Dealing with temporal uncertainties is a key issue in domains like project management or medical treatment planning. However, support for temporal indeterminacies is not very well integrated in current methods, techniques, and tools. In this paper, we present a visualization technique called PlanningLines that allows for representing temporal uncertainties and aims at supporting project managers in their difficult planning and controlling tasks. We conducted a controlled experiment to gather empirical evidence on the strengths and limitations of our approach. Main results are that PlanningLine users make fewer mistakes and are faster in conducting tasks than users of a traditional visualization technique.

Focus+context taken literally

A common feature of information visualization applications, and also other areas, is to direct the users attention to certain objects. This alerts users to a problem or shows the matching objects in response to a query. Often users also want to quickly understand the information pointed out in the context of the other information and not just see the results. This is one type of the focus+context (F+C) technique, which provides both detailed information of the currently most relevant objects, as well as giving users an idea of the context. The authors present a focus+context method that blurs objects based on their relevance (rather than distance) to direct the users attention.

Effective data validation of high-frequency data: time-point-, time-interval-, and trend-based methods.

Real-time systems for monitoring and therapy planning, which receive their data from on-line monitoring equipment and computer-based patient records, require reliable data. Data validation has to utilize and combine a set of fast methods to detect, eliminate, and repair faulty data, which may lead to life-threatening conclusions. The strength of data validation results from the combination of numerical and knowledge-based methods applied to both continuously-assessed high-frequency data and discontinuously-assessed data. Dealing with high-frequency data, examining single measurements is not sufficient. It is essential to take into account the behavior of parameters over time. We present time-point-, time-interval-, and trend-based methods for validation and repair. These are complemented by time-independent methods for determining an overall reliability of measurements. The data validation benefits from the temporal data-abstraction process, which provides automatically derived qualitative values and patterns. The temporal abstraction is oriented on a context-sensitive and expectation-guided principle. Additional knowledge derived from domain experts forms an essential part for all of these methods. The methods are applied in the field of artificial ventilation of newborn infants. Examples from the real-time monitoring and therapy-planning system VIE-VENT illustrate the usefulness and effectiveness of the methods.