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Visual Analysis of Geo-spatial Data in 3D Terrain Environments using Focus+Context
(The Eurographics Association, 2017)
Visual analysis of geo-spatial data represented within a three-dimensional frame of reference is a challenging task. Focus+ Context is a common concept that aids this process. This paper addresses the question, how ...
On Quality Indicators for Progressive Visual Analytics
(The Eurographics Association, 2019)
A key component in using Progressive Visual Analytics (PVA) is to be able to gauge the quality of intermediate analysis outcomes. This is necessary in order to decide whether a current partial outcome is already good enough ...
Visual Analytics of Event Data using Multiple Mining Methods
(The Eurographics Association, 2019)
Most researchers use a single method of mining to analyze event data. This paper uses case studies from two very different domains (electronic health records and cybersecurity) to investigate how researchers can gain ...
Guidance or No Guidance? A Decision Tree Can Help
(The Eurographics Association, 2018)
Guidance methods have the potential of bringing considerable benefits to Visual Analytics (VA), alleviating the burden on the user and allowing a positive analysis outcome. However, the boundary between conventional VA ...
Visual Analysis of Optical Coherence Tomography Data in Ophthalmology
(The Eurographics Association, 2017)
Optical coherence tomography (OCT) enables noninvasive high-resolution 3D imaging of the human retina and thus, plays a fundamental role in detecting a wide range of ocular diseases. Despite OCT's diagnostic value, managing ...
A Set-based Visual Analytics Approach to Analyze Retail Data
(The Eurographics Association, 2018)
This paper explores how a set-based visual analytics approach could be useful for analyzing customers' shopping behavior, and makes three main contributions. First, it describes the scale and characteristics of a real-world ...
Quantifying Uncertainty in Multivariate Time Series Pre-Processing
(The Eurographics Association, 2019)
In multivariate time series analysis, pre-processing is integral for enabling analysis, but inevitably introduces uncertainty into the data. Enabling the assessment of the uncertainty and allowing uncertainty-aware analysis, ...
Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series
(The Eurographics Association, 2018)
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 ...
Combining Cluster and Outlier Analysis with Visual Analytics
(The Eurographics Association, 2017)
Cluster and outlier analysis are two important tasks. Due to their nature these tasks seem to be opposed to each other, i.e., data objects either belong to a cluster structure or a sparsely populated outlier region. In ...