Dirk J. Lehmann

Dirk J. Lehmann
Ostfalia University of Applied Sciences

Professor

About

30
Publications
6,028
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
539
Citations

Publications

Publications (30)
Article
Radial axes plots are projection methods that represent high‐dimensional data samples as points on a two‐dimensional plane. These techniques define mappings through a set of axis vectors, each associated with a data variable, which users can manipulate interactively to create different plots and analyze data from multiple points of view. However, u...
Conference Paper
Multi-variate visualizations of geospatial data often use combinations of different visual cues, such as color and texture. For textures, different point distributions (blue noise, regular grids, etc.) can encode nominal data. In this paper, we study the suitability of point distribution interpolation to encode quantitative information. For the int...
Article
Analysts often use visualisation techniques like a scatterplot matrix (SPLOM) to explore multivariate datasets. The scatterplots of a SPLOM can help to identify and compare two‐dimensional global patterns. However, local patterns which might only exist within subsets of records are typically much harder to identify and may go unnoticed among larger...
Article
In statistics, machine learning, and related fields, feature selection is the process of choosing a smaller subset of features to work with. This is an important topic since selecting a subset of features can help analysts to interpret models and data, and to decrease computational runtimes. While many techniques are purely automatic, the data visu...
Conference Paper
Full-text available
Large vertically-mounted high-resolution multi-touch displays are becoming increasingly available for interactive data visualisation. Such devices are well-suited to small-team collaborative visual analysis. In particular, the visual analysis of large high-dimensional datasets can benefit from high-resolution displays capable of showing multiple co...
Article
This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analysis of lake sediment cores. The goal is to gain hypotheses about landscape evolution and climate conditions in the past. To this end,...
Article
One main task for domain experts in analysing their nD data is to detect and interpret class/cluster separations and outliers. In fact, an important question is, which features/dimensions separate classes best or allow a cluster-based data classification. Common approaches rely on projections from nD to 2D, which comes with some challenges, such as...
Article
Full-text available
The UN Comtrade database is the world's largest repository of bilateral trade data. Their complexity poses a challenge to visualization systems, leading to issues such as scalability and visual clutter. Thus, we propose a radial layout-based visual exploration system to enable the user to smoothly explore the change over time and to explore differe...
Article
Radial axes plots are multivariate visualization techniques that extend scatterplots in order to represent high-dimensional data as points on an observable display. Well-known methods include star coordinates or principal component biplots, which represent data attributes as vectors that define axes, and produce linear dimensionality reduction mapp...
Article
Full-text available
Data analysis often involves finding models that can explain patterns in data, and reduce possibly large data sets to more compact model-based representations. In Statistics, many methods are available to compute model information. Among others, regression models are widely used to explain data. However, regression analysis typically searches for t...
Article
Star Coordinates are a popular projection technique in order to analyze and to disclose characteristic patterns of multidimensional data. Unfortunately, the shape, appearance, and distribution of such patterns are strongly affected by the given scaling of the data and can mislead the projection-based data analysis. In an extreme case, patterns migh...
Article
To project high-dimensional data to a 2D domain, there are two well-established classes of approaches: RadViz and Star Coordinates. Both are well-explored in terms of accuracy, completeness, distortions, and interaction issues. We present a generalization of both RadViz and Star Coordinates such that it unifies both approaches. We do so by consider...
Article
Finding good projections of n-dimensional datasets into a 2D visualization domain is one of the most important problems in Information Visualization. Users are interested in getting maximal insight into the data by exploring a minimal number of projections. However, if the number is too small or improper projections are used, then important data pa...
Article
The visual analysis of multivariate projections is a challenging task, because complex visual structures occur. This causes fatigue or misinterpretations, which distorts the analysis. In fact, the same projection can lead to different analysis results. We provide visual guidance pictograms to improve objectivity of the visual search. A visual guida...
Article
The number of visualizations being required for a complete view on data non-linearly grows with the number of data dimensions. Thus, relevant visualizations need to be filtered to guide the user during the visual search. A popular filter approach is the usage of quality metrics, which map a visual pattern to a real number. This way, visualizations...
Conference Paper
Identifying differences among the distribution of samples of different observations is an important issue in many research fields. We provide a general framework to detect these difference spots in d-dimensional feature space. Such spots occur not only at various locations , they may also come in various shapes and multiple sizes, even at the same...
Article
Full-text available
Direct Numerical Simulations of premixed combustion produce terabytes of raw data, which are prohibitively large to be stored, and have to be analyzed and visualized. A simultaneous and integrated treatment of data storage, data analysis and data visualization is required. For this, we introduce a sparse representation tailored to DNS data which ca...
Article
Full-text available
Understanding the hemodynamics of blood flow in vascular pathologies such as intracranial aneurysms is essential for both their diagnosis and treatment. Computational Fluid Dynamics (CFD) simulations of blood flow based on patient-individual data are performed to better understand aneurysm initiation and progression and more recently, for predictin...
Article
Star coordinates is a popular projection technique from an nD data space to a 2D/3D visualization domain. It is defined by setting n coordinate axes in the visualization domain. Since it generally defines an affine projection, strong distortions can occur: an nD sphere can be mapped to an ellipse of arbitrary size and aspect ratio. We propose to re...
Article
Full-text available
Cerebral aneurysms are a pathological vessel dilatation that bear a high risk of rupture. For the understanding and evaluation of the risk of rupture, the analysis of hemodynamic information plays an important role. Besides quantitative hemodynamic information, also qualitative flow characteristics, e.g., the inflow jet and impingement zone are cor...
Article
The scatterplot matrix (SPLOM) is a well-established technique to visually explore high-dimensional data sets. It is characterized by the number of scatterplots (plots) of which it consists of. Unfortunately, this number quadratically grows with the number of the data set’s dimensions. Thus, an SPLOM scales very poorly. Consequently, the usefulness...
Article
Two-dimensional transfer functions are an effective and well-accepted tool in volume classification. The design of them mostly depends on the user's experience and thus remains a challenge. Therefore, we present an approach in this paper to automate the transfer function design based on 2D density plots. By exploiting their smoothness, we adopted t...
Technical Report
Full-text available
In this paper we analyze weather maps to distinguish between the three main circulation forms which are essential factors for weather composition and are fundamental for weather forecasters. We propose a set of features specifically tailored for the classification of these circulation forms in General Weather Situations and use these to train a sup...
Article
Continuous Parallel Coordinates (CPC) are a contemporary visualization technique in order to combine several scalar fields, given over a common domain. They facilitate a continuous view for parallel coordinates by considering a smooth scalar field instead of a finite number of straight lines. We show that there are feature curves in CPC which appea...
Conference Paper
Full-text available
This paper proposes a vector field visualization approach that extracts and visualizes grouped regions of static 3D vector fields of similar curvature behavior. These regions are argued to ease the recognition of regions of potential interest and accelerate the general exploration process of vector fields. Our approach detects regions of similar ge...
Conference Paper
Modern visualization methods are needed to cope with very highdimensional data. Efficient visual analytical techniques are required to extract the information content in these data. The large number of possible projections for each method, which usually grow quadratically or even exponentially with the number of dimensions, urges the necessity to e...
Article
Full-text available
Zusammenfassung Für multidimensionale Datensätze existieren eine Reihe von automatischen Analysemethoden und Visualisierungstechniken, um ihnen innewohnende Zusammenhänge und Charakteristika aufzudecken. Die zunehmende Größe und Komplexität solcher Daten macht es notwendig, beide Ansätze miteinander zu kombinieren. In diesem Artikel stellen wir Ihn...
Article
The concept of continuous scatterplot (CSP) is a modern visualization technique. The idea is to define a scalar density value based on the map between an n-dimensional spatial domain and an m-dimensional data domain, which describe the CSP space. Usually the data domain is two-dimensional to visually convey the underlying, density coded, data. In t...
Conference Paper
Parallel coordinates and scatterplot matrices are widely used to visualize multidimensional data sets. But these visualization techniques are insufficient when the number of dimensions grows. To solve this problem, different approaches to preselect the best views or dimensions have been proposed in the last years. However, there are still several s...
Conference Paper
Preoperative neck dissection planning benefits from a smooth, organic visualization of the main blood vessels of the neck, in particular the carotid artery and jugular vein. While most reconstruction techniques for vasculature are designed for segmenting the complete vessel tree, our goal is to isolate these specific blood vessels of the neck from...