Tatiana von Landesberger

• PhD.
• Head of Department at Technical University of Darmstadt

Background: Hospital-onset bacteremia (HOB) is one of the most common hospital-acquired infections, resulting in increased in-hospital morbidity and mortality. To support clinicians in assessing patients at risk, data-driven applications can be implemented as decision-support. Objectives: We aim at rigorously collecting clinician's needs in an i...

Data visualization methodologies were intensively leveraged during the COVID-19 pandemic. We review our design experience working on a set of interdisciplinary COVID-19 pandemic projects. We describe the challenges we met in these projects, characterize the respective user communities, the goals and tasks we supported, and the data types and visual...

Visual validation of regression models in scatterplots is a common practice for assessing model quality, yet its efficacy remains unquantified. We conducted two empirical experiments to investigate individuals' ability to visually validate linear regression models (linear trends) and to examine the impact of common visualization designs on validati...

This report documents the program and the outcomes of Dagstuhl Seminar "Reflections on Pandemic Visualization" (24091). The fight against COVID-19 has highlighted the crucial role of data visualization and analytics, prompting significant innovations and collaborations. This Dagstuhl Seminar brought together experts from various fields to reflect o...

Prior research has shown that human perception of similarity differs from mathematical measures in visual comparison tasks, including those involving directed acyclic graphs. This divergence can lead to missed differences and skepticism about algorithmic results. To address this, we aim to learn the structural differences humans detect in graphs vi...

Comparing directed acyclic graphs is essential in various fields such as healthcare, social media, finance, biology, and marketing. DAGs often result from contagion processes over networks, including information spreading, retweet activity, disease transmission, financial crisis propagation, malware spread, and gene mutations. For instance, in dise...

Creating graph visualizations involves many decisions, such as layout, node and edge appearance, and color choices. These decisions are challenging due to the multitude of options available. For instance, graph layout can be force-directed or orthogonal, and edges can be curved, tapered, partially drawn, or animated. Thus, research offers a multitu...

Zusammenfassung Nosokomiale Infektionen stellen weltweit, aber auch in Deutschland eine enorme Belastung für Patient*innen, Beschäftigte im Gesundheitswesen, Angehörige und die Gesellschaft dar. Zentrale Aufgaben der Infektionsprävention sind die Erfassung und Bewertung von Infektionen mit dem Ziel, Präventionspotenziale und Risikofaktoren zu ident...

We introduce two novel visualization designs to support practitioners in performing identification and discrimination tasks on large value ranges (i.e., several orders of magnitude) in time-series data: (1) The order of magnitude horizon graph, which extends the classic horizon graph; and (2) the order of magnitude line chart, which adapts the log-...

We investigate the ability of individuals to visually validate statistical models in terms of their fit to the data. While visual model estimation has been studied extensively, visual model validation remains under-investigated. It is unknown how well people are able to visually validate models, and how their performance compares to visual and comp...

This paper presents a comprehensive investigation of the factors that influence visual comparison in colored node-link diagrams. We conducted a user study in which participants were asked to identify differences in pairs of directed acyclic graphs (DAGs) under time constraints. Previous studies focused on the perception of differences in node-link...

We investigate the ability of individuals to visually validate statistical models in terms of their fit to the data. While visual model estimation has been studied extensively, visual model validation remains under-investigated. It is unknown how well people are able to visually validate models, and how their performance compares to visual and comp...

We introduce two novel visualization designs to support practitioners in performing identification and discrimination tasks on large value ranges (i.e., several orders of magnitude) in time-series data: (1) The order of magnitude horizon graph, which extends the classic horizon graph; and (2) the order of magnitude line chart, which adapts the log-...

Visualization researchers and visualization professionals seek appropriate abstractions of visualization requirements that permit considering visualization solutions independently from specific problems. Abstractions can help us design, analyze, organize, and evaluate the things we create. The literature has many task structures (taxonomies, typolo...

Visualization researchers and visualization professionals seek appropriate abstractions of visualization requirements that permit considering visualization solutions independently from specific problems. Abstractions can help us design, analyze, organize, and evaluate the things we create. The literature has many task structures (taxonomies, typolo...

When planning series of events or processes, everyone has to cope with temporal uncertainty. Popular examples are holiday planning or train trips. There are several approaches to visualize temporal uncertainty when temporal data and events are already defined, but common research usually does not take uncertainty into account, neither as input nor...

This paper presents a novel color scheme designed to address the challenge of visualizing data series with large value ranges, where scale transformation provides limited support. We focus on meteorological data, where the presence of large value ranges is common. We apply our approach to meteorological scatterplots, as one of the most common plots...

Early anticipation of COVID-19 infection chains within hospitals is of high importance for initiating suitable measures at the right time. Infection control specialists can be supported by application systems able of consolidating and analyzing heterogeneous, up-to-now non-standardized and distributed data needed for tracking COVID-19 infections an...

Zusammenfassung Die SARS-CoV-2-Pandemie hat viele sehr spezielle Fragen des Datenschutzes und der Datensicherheit aufgeworfen. Der vorliegende Beitrag widmet sich den mit der Veröffentlichung von Infiziertenzahlen verbundenen Re-Identifikationsrisiken. Er zeigt einen Weg auf, diese Risiken mit Mitteln des technischen Datenschutzes zu reduzieren, um...

The spread of multidrug resistant organisms (MDRO) is a global healthcare challenge. Nosocomial outbreaks caused by MDRO are an important contributor to this threat. Computer-based applications facilitating outbreak detection can be essential to address this issue. To allow application reusability across institutions, the various heterogeneous micr...

The perception of differences between graphs represented as node-link diagrams is an important issue in many disciplines. This paper presents results from a study with 40 participants. The goal of the study was to test whether shape, density, and edge crossings of the graph influence the perception of differences between graphs and the order in whi...

Security awareness and education programmes are rolled out in more and more organisations. However, their effectiveness over time and, correspondingly, appropriate intervals to remind users' awareness and knowledge are an open question. In an attempt to address this open question, we present a field investigation in a German organisation from the p...

In this paper, we analyze the layout stability for the squarify and slice-and-dice treemap layout algorithms when changing the visualization containers resolution. We also explore how rescaling a finished layout to another resolution compares to a recalculated layout, i.e. fixed layout versus changing layout. For our evaluation, we examine a real w...

Data sets with large value range are difficult to visualize with traditional linear bar charts. Usually, a logarithmic scale is used in these cases. However, the logarithmic scale suffers from non-linearity. Recently, scale-stack bar charts and magnitude markers, improve the readability of values. However, they have other disadvantages such as vari...

Bacteria and viruses are transmitted among patients in the hospital. Infection control experts develop strategies for infection control. Currently, this is done mostly manually, which is time-consuming and error-prone. Visual analysis approaches mainly focus disease spread on population level. We learn a RNN model for detection of potential infecti...

Visual comparison of graphs has become widespread in various disciplines. To support this task, it is necessary to generate graph drawings that facilitate the perception of differences. However, while readability of single graphs has been widely investigated, knowledge about the recognition of differences in graphs in general and directed acyclic g...

Clinicians and hygienists need to identify outbreaks and transmission patterns of pathogen infections among hospital patients. Such analysis requires the combination of the microbiological laboratory results with the location and contacts among patients. Currently, this is a cumbersome manual and time-consuming task that includes reading multiple t...

Data comparison in various domains can be effectively supported by visual analytics solutions combining interactive visualization and algorithmic analysis. The design of such solutions should match the comparison problem at hand: the input data and the task specification. This requires several choices from algorithm to visual design and interaction...

Train trip planning means deciding on one of several travel connections. Possible train delays lead to uncertainties in the schedule connections and may influence the planning decisions. Although several designs for the visualization of the available train trips exist, it is still unclear how these designs and the visualization of delay uncertainty...

From¹ a set of trajectories of the players and the ball in a football (soccer) game, we computationally estimate, for each time frame, the pressure of the defending players upon the ball and the opponents. The extracted pressure relationships are visualized in detailed and summarized forms. Interactive filtering enables exploration of the pressure...

Data comparison is one of the core tasks in exploratory analysis, which combines algorithmic analysis and interactive visualization in a visual data comparison process. Comparison of large and complex datasets requires several steps-i.e., a workflow. This article discusses the comparison process, its research challenges, and examples of solutions.

This paper presents Storyfinder, an application which consists of a browser plugin and a web server backend with the goal to highlight and manage the information contained in web pages by combining techniques from natural language processing and visual analytics. Webpages are analyzed while visiting them by means of natural language processing comp...

Modern movement tracking technologies enable acquisition of high quality data about movements of the players and the ball in the course of a football match. However, there is a big difference between the raw data and the insights into team behaviors that analysts would like to gain. To enable such insights, it is necessary first to establish relati...

Crowdsourcing offers great potential to overcome the limitations of controlled lab studies. To guide future designs of crowdsourcing-based studies for visualization, we review visualization research that has attempted to leverage crowdsourcing for empirical evaluations of visualizations. We discuss six core aspects for successful employment of crow...

While visual comparison of directed acyclic graphs (DAGs) is commonly encountered in various disciplines (e.g., finance, biology), knowledge about humans' perception of graph similarity is currently quite limited. By graph similarity perception we mean how humans perceive commonalities and differences in graphs and herewith come to a similarity jud...

While visual comparison of directed acyclic graphs (DAGs) is commonly encountered in various disciplines (e.g., finance, biology), knowledge about humans' perception of graph similarity is currently quite limited. By graph similarity perception we mean how humans perceive commonalities and differences in graphs and herewith come to a similarity jud...

The visual exploration of graphs encoding relationships between entities of multiple types (e.g., persons, locations,...) supports journalists in finding newsworthy information in large text collections. Journalists may have interest in certain entity types or their relations such as locations or person-person relations. This interest may change du...

The visual exploration of graphs encoding relationships between entities of multiple types (e.g., persons, locations,...) supports journalists in finding newsworthy information in large text collections. Journalists may have interest in certain entity types or their relations such as locations or person-person relations. This interest may change du...

Uncertainty about possible train delays has an impact on train trips, as the exact arrival time is unknown during trip planning. Delays can lead to missing a connecting train at the transfer station, or to coming too late to an appointment at the destination. Facing this uncertainty, the traveler may wish to use an earlier train or a different conn...

Nodes in real world networks often have a geographic position. In many cases such as for simulation or optimization, there is a need for non-trivial synthetic geo-located networks. As synthetic datasets are required to have specific properties such as connectivity and geographic distribution, often networks need to be generated. However, their crea...

Static geolocated graphs have nodes connected by edges, where both can have geographic location and associated attributes. For example, it can be uncertain exactly where a node is located or whether an edge between two nodes exists. Because source data is often incomplete or inexact, it is necessary to visualize this uncertainty to help users make...

We present new/s/leak, a novel tool developed for and with the help of journalists, which enables the automatic analysis and discovery of newsworthy stories from large textual datasets. We rely on different NLP preprocessing steps such named entity tagging, extraction of time expressions, entity networks, relations and metadata. The system features...

Current technologies allow movements of the players and the ball in football matches to be tracked and recorded with high accuracy and temporal frequency. We demonstrate an approach to analyzing football data with the aim to find typical patterns of spatial arrangement of the field players. It involves transformation of original coordinates to rela...

The rising quantity and complexity of data creates a need to design and optimize data processing pipelines - the set of data processing steps, parameters and algorithms that perform operations on the data. Visualization can support this process but, although there are many examples of systems for visual parameter analysis, there remains a need to s...

Relationships between classical music composers are known due to explicit historic material, for instance the friendship between Joseph Haydn and Wolfgang Amadeus Mozart, as well as the influence of the latter on Ludwig van Beethoven. While Haydn and Mozart were critics of each others work, Mozart and Beethoven probably never met in person. In spit...

Learning more about people mobility is an important task for official decision makers and urban planners. Mobility data sets characterize the variation of the presence of people in different places over time as well as movements (or flows) of people between the places. The analysis of mobility data is challenging due to the need to analyze and comp...

The quality of automatic 3D medical segmentation algorithms needs to be assessed on test datasets comprising several 3D images (i.e., instances of an organ). The experts need to compare the segmentation quality across the dataset in order to detect systematic segmentation problems. However, such comparative evaluation is not supported well by curre...

Geo-located graph drawings often suffer from map visualization problems, such as overplotting of nodes as well as edges and location of parts of the graph being outside of the screen. One cause of these problems is often an irregular distribution of nodes on the map. Zooming and panning do not solve the problems, as they either only show the overvi...

Geo-located graph drawings often suffer from map visualization problems, such as overplotting of nodes as well as edges and location of parts of the graph being outside of the screen. One cause of these problems is often an irregular distribution of nodes on the map. Zooming and panning do not solve the problems, as they either only show the overvi...

3D medical image segmentation is needed for diagnosis and treatment. As manual segmentation is very costly, automatic segmentation algorithms are needed. For finding best algorithms, several algorithms need to be evaluated on a set of organ instances. This is currently difficult due to dataset size and complexity. In this paper, we present a novel...

Foldovers (i.e., folding of triangles in a 3D mesh) are artifacts that cause problems for morphing. Mesh morphing uses vertex correspondences among the source and the target mesh to define the morphing path. Although there exist techniques for making a foldover-free mesh morphing, identification and correction of foldovers in existing correspondenc...

The evaluation of 3D medical image segmentation quality requires a reliable detailed comparison of a reference segmentation with an automatic segmentation. It should be able to measure the quality accurately and, thus, to reveal problematic regions. While several (global) measures, providing a single quality value, are available, the only widely us...

Most visualization techniques have traditionally used two-dimensional, instead of three-dimensional representations to visualize multidimensional and multivariate data. In this article, a way to demonstrate the underlying superiority of three-dimensional, with respect to two-dimensional, representation is proposed. Specifically, it is based on the...

Proteins are essential parts in all living organisms. They consist of sequences of amino acids. An interaction with reactive agent can stimulate a mutation at a specific position in the sequence. This mutation may set off a chain reaction, which effects other amino acids in the protein. Chain reactions need to be analyzed, as they may invoke unwant...

Interaction (or human-computer interaction/HCI) is a key ingredient of modern visualization and visual analysis systems. It allows the user to manage the data and to explore its different aspects, as well as to shape its visual representation and to observe it from different perspectives-ultimately to pursue the user's analytical goal. Yet, so far...

We present a system for visual exploration of time-dependent activity sensor and emotion state data gained from psychological experiments. The real data has several quality problems such as missing or implausible observations as well as data inconsistencies. Therefore, our system automatically pre-processes the data. It then shows the results in an...

Multivariate networks are present in various domains such as biology, or social science. In such networks, the nodes often have several quantitative attributes, which determine similarity of nodes (e.g., person’s characteristics in social networks). When interpreting these networks, often both node connectivity and node similarity need to be analyz...

The study of movement data is an important task in a variety of domains such as transportation, biology, or finance. Often, the data objects are grouped (e.g. countries by continents). We distinguish three main categories of movement data analysis, based on the focus of the analysis: (a) movement characteristics of an individual in the context of i...

Understanding relationships between people and organizations by reading newspaper articles is difficult to manage for humans due to the large amount of data. To address this problem, we present and evaluate a new visual analytics system, which offers interactive exploration and tagging of social networks extracted from newspapers. For the visual ex...

Interaction is a vital component in the visualization of multivariate networks. It enables greater amounts of information to be seen and explored than is possible with static visualization. Interaction can also help show the information landscape of the data while still allowing users to find and view areas of interest in greater detail and pivot b...

Evolutionary relationships between organisms are frequently derived as phylogenetic trees inferred from multiple sequence alignments (MSAs). The MSA parameter space is exponentially large, so tens of thousands of potential trees can emerge for each dataset. A proposed visual-analytics approach can reveal the parameters' impact on the trees. Given i...

In various application areas (social science, transportation, or medicine) analysts need to gain knowledge from large amounts of data. This analysis is often supported by interactive Visual Analytics tools that combine automatic analysis with interactive visualization. Such a data analysis process is not streamlined, but consists of several steps a...

Huge amounts of multivariate research data are produced and made publicly available in digital libraries. Little research focused on similarity functions that take multivariate data documents as a whole into account. Such similarity functions are highly beneficial for users, by enabling them to browse and query large collections of multivariate dat...

The importance of medical image segmentation increases in fields like treatment planning or computer aided diagnosis. For high quality automatic segmentations, algorithms based on statistical shape models (SSMs) are often used. They segment the image in an iterative way. However, segmentation experts and other users can only asses the final segment...

Large amounts of multivariate data are collected in different areas of scientific research and industrial production. These data are collected, archived and made publicly available by research data repositories. In addition to meta-data based access, content-based approaches are highly desirable to effectively retrieve, discover and analyze data se...

The study of movement data is an important task in a variety of domains such as transportation, biology, or finance. Often, the data objects are grouped (e. g. countries by continents). We distinguish three main categories of movement data analysis, based on the focus of the analysis: (a) movement characteristics of an individual in the context of...

Contagion is a process whereby the collapse of a node in a network leads to the collapse of neighboring nodes and thereby sets off a chain reaction in the network. It thereby creates a special type of time-dependent network. Such processes are studied in various applications, e.g., in financial network analysis, infection diffusion prediction, supp...

Segmentation of medical images is a prerequisite in clinical practice. Many segmentation algorithms use statistical shape models. Due to the lack of tools providing prior information on the data, standard models are frequently used. However, they do not necessarily describe the data in an optimal way. Model-based segmentation can be supported by Vi...

We focus on visual analysis of space-and time-referenced categor-ical data, which describe possible states of spatial (geographical) objects or locations and their changes over time. The analysis of these data is difficult as there are only limited possibilities to ana-lyze the three aspects (location, time and category) simultaneously. We present...

Visual analysis of time series data is an important, yet challenging task with many application examples in fields such as financial or news stream data analysis. Many visual time series analysis approaches consider a global perspective on the time series. Fewer approaches consider visual analysis of local patterns in time series, and often rely on...

Huge amounts of various research data are produced and made publicly available in digital libraries. An important category is bivariate data (measurements of one variable versus the other). Examples of bivariate data include observations of temperature and ozone levels (e.g., in environmental observation), domestic production and unemployment (e.g....

Subspace clustering addresses an important problem in clustering multi-dimensional data. In sparse multi-dimensional data, many dimensions are irrelevant and obscure the cluster boundaries. Subspace clustering helps by mining the clusters present in only locally relevant subsets of dimensions. However, understanding the result of subspace clusterin...

One of the central motivations for visual analytics research is the so-called information overload—implying the challenge for human users in understanding and making decisions in presence of too much information (Yang et al. in Decision Support Systems 35(1):89–102, 2003). Visual-interactive systems, integrated with automatic data analysis techniqu...

Traditionally, the visual analysis of hierarchies, respectively, trees, is conducted by focusing on one given hierarchy. However, in many research areas multiple, differing hierarchies need to be analyzed simultaneously in a comparative way - in particular to highlight differences between them, which sometimes can be subtle. A prominent example is...

The analysis of large graphs plays a prominent role in various fields of research and is relevant in many important application areas. Effective visual analysis of graphs requires appropriate visual presentations in combination with respective user interaction facilities and algorithmic graph analysis methods. How to design appropriate graph analys...

Exploration and selection of data descriptors representing objects using a set of features are important components in many data analysis tasks. Usually, for a given dataset, an optimal data description does not exist, as the suitable data representation is strongly use case dependent. Many solutions for selecting a suitable data description have b...