Heidrun Schumann
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Towards a Unified User Interface for Visual Analysis of Retinal Data in Ophthalmology Open
The visual analysis of retinal data contributes to the understanding of a wide range of eye diseases. For the evaluation of cross-sectional studies, ophthalmologists rely on workflows and toolsets established in their work environment. Tha…
Computational Analysis Support Open
This chapter is concerned with computational methods to support the analysis of time-oriented data. A general overview of temporal data analysis is provided and specific application examples will be used for demonstration.
Involving the Human via Interaction Open
This chapter explains why involving the human is important when visually analyzing time and time-oriented data. Some general assertions will be made and basic interaction concepts introduced. The chapter also covers advanced interaction me…
Conclusion Open
This chapter briefly summarizes the content of the book and describes practical concerns of visualizing time-oriented data in real-world data settings. Visual analytics is briefly outlined as a modern approach that combines visualization, …
Guiding the Selection of Visualization Techniques Open
This chapter describes how researchers and practitioners can be guided in making informed decisions when selecting visualization techniques for time and time-oriented data. The TimeViz Browser is introduced and a general conceptual model f…
Introduction Open
Space and time are two outstanding dimensions because, in conjunction, they represent the four-dimensional space or simply the world we are living in. Basically, every piece of data we measure is related and often only meaningful within th…
Time and Time-Oriented Data Open
This chapter investigates in detail the characteristics of time and time-oriented data. Design aspects for modeling time and time-oriented data are introduced and discussed using examples. The chapter also sheds some light on data quality.
Crafting Visualizations of Time-Oriented Data Open
Many different types of data are related to time. Meteorological data, financial data, census data, medical data, simulation data, news articles, photo collections, or project plans, to name only a few examples, all contain temporal inform…
Historical Background Open
This chapter takes a look back in time and presents a selection of historical visual representations of time-oriented data. The representation of time in the arts is a second aspect covered in this chapter.
Visualization of Time-Oriented Data Open
This is an open access book. The revised edition gives a brief primer to visualization and a review of historical time-oriented visual representations.
Visual Analytics for Early Detection of Retinal Diseases Open
Advances in optical coherence tomography (OCT) have enabled noninvasive imaging of substructures of the human retina with high spatial resolution. OCT examinations are now a standard procedure in clinics and an integral part of ophthalmic …
Customizable Coordination of Independent Visual Analytics Tools Open
While it is common to use multiple independent analysis tools in combination, it is still cumbersome to carry out a cross-tool visual analysis. Some dedicated frameworks addressing this issue exist, yet in order to use them, a Visual Analy…
A theoretical model for pattern discovery in visual analytics Open
The word ‘pattern’ frequently appears in the visualisation and visual analytics literature, but what do we mean when we talk about patterns? We propose a practicable definition of the concept of a pattern in a data distribution as a combin…
Responsive Matrix Cells: A Focus+Context Approach for Exploring and Editing Multivariate Graphs Open
Matrix visualizations are a useful tool to provide a general overview of a graph's structure. For multivariate graphs, a remaining challenge is to cope with the attributes that are associated with nodes and edges. Addressing this challenge…
A Characterization of Data Exchange between Visual Analytics Tools Open
Over the past years, the visualization of large and complex data sets brought up various Visual Analytics (VA) tools in order to solve domain-specific tasks. These VA tools are typically implemented as individual software components in dat…
Varying Annotations in the Steps of the Visual Analysis Open
Annotations in Visual Analytics (VA) have become a common means to support the analysis by integrating additional information into the VA system. That additional information often depends on the current process step in the visual analysis.…
Thickness of Intraretinal Layers in Patients with Type 2 Diabetes Mellitus Depending on a Concomitant Diabetic Neuropathy: Results of a Cross-Sectional Study Using Deviation Maps for OCT Data Analysis Open
Optical coherence tomography (OCT) supports the detection of thickness changes in intraretinal layers at an early stage of diabetes mellitus. However, the analysis of OCT data in cross-sectional studies is complex and time-consuming. We in…
Interactive Visual Data Analysis Open
In the age of big data, being able to make sense of data is an important key to success. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and…
Exploring Time Series Segmentations Using Uncertainty and Focus+Context Techniques Open
Time series segmentation is employed in various domains and continues to be a relevant topic of research. A segmentation pipeline is composed of different steps involving several parameterizable algorithms. Existing Visual Analytics approa…
Multi-display Visual Analysis: Model, Interface, and Layout Computation Open
Modern display environments offer great potential for involving multiple users in presentations, discussions, and data analysis sessions. By showing multiple views on multiple displays, information exchange can be improved, several perspec…
Making Parameter Dependencies of Time‐Series Segmentation Visually Understandable Open
This work presents an approach to support the visual analysis of parameter dependencies of time‐series segmentation. The goal is to help analysts understand which parameters have high influence and which segmentation properties are highly …
Enhanced Grid-Based Visual Analysis of Retinal Layer Thickness with Optical Coherence Tomography Open
Optical coherence tomography enables high-resolution 3D imaging of retinal layers in the human eye. The thickness of the layers is commonly assessed to understand a variety of retinal and systemic disorders. Yet, the thickness data are com…
Deviation Maps for Understanding Thickness Changes of Inner Retinal Layers in Children with Type 1 Diabetes Mellitus Open
Purpose: To analyze the use of deviation maps (DevMs) to understand thickness changes of inner retinal layers in optical coherence tomography (OCT) data. To test a new visual analytics (VA) method with reduced complexity of OCT data analys…
Lightweight Coordination of Multiple Independent Visual Analytics Tools Open
With the advancement of Visual Analytics (VA) and its spread into various application fields comes along a specialization of methods and tools. This adds complexity and requires extra effort when devising domain-dependent VA solutions, as …
View article: A Review and Characterization of Progressive Visual Analytics
A Review and Characterization of Progressive Visual Analytics Open
Progressive Visual Analytics (PVA) has gained increasing attention over the past years. It brings the user into the loop during otherwise long-running and non-transparent computations by producing intermediate partial results. These partia…
Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series Open
For the automatic segmentation of multivariate time series domain experts at first need to consider a huge space of alternative configurations of algorithms and parameters. We assume that only a small subset of these configurations needs t…
Supporting Visual Parameter Analysis of Time Series Segmentation with Correlation Calculations Open
Parameter analysis can be used to find out how individual parameters influence the output of an algorithm. We aim to support the visual parameter analysis of algorithms for the segmentation of time series. To this end, we automatically sea…