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This thesis aims to investigate the visualization approaches in the field of annotated discourse relations and to find a solution that meets the requirements best by comparing different programming tools. The subject of this research are coherence relations, which have several properties that can be challenging for many visualization methods. The thesis presents five different visualization options from both the application and the development perspective. The initially tested simple HTML approaches as well as the software package displaCy show the insufficient level for the visualization purposes of this work. The alternative implementation with D3 would optimally meet the requirements but goes beyond the scope of the project. The main method chosen in this thesis was implemented as a single web application and uses the brat annotation tool, which fulfills most of the defined requirements for the representation of the coherence relations. The application graphically displays the coherence relations annotated in the text and offers a filter function for different relation types.
Developing large software projects is a complicated task and can be demanding for developers. Continuous integration is common practice for reducing complexity. By integrating and testing changes often, changesets are kept small and therefore easily comprehensible. Travis CI is a service that offers continuous integration and continuous deployment in the cloud. Software projects are build, tested, and deployed using the Travis CI infrastructure without interrupting the development process. This report describes how Travis CI works, presents how time-driven, periodic building is implemented as well as how CI data visualization can be done, and proposes a way of dealing with dependency problems.
Intuitive Modelle der Informatik sind gedankliche Vorstellungen über informatische Konzepte, die mit subjektiver Gewissheit verbunden sind. Menschen verwenden sie, wenn sie die Arbeitsweise von Computerprogrammen nachvollziehen oder anderen erklären, die logische Korrektheit eines Programms prüfen oder in einem kreativen Prozess selbst Programme entwickeln. Intuitive Modelle können auf verschiedene Weise repräsentiert und kommuniziert werden, etwa verbal-abstrakt, durch ablauf- oder strukturorientierte Abbildungen und Filme oder konkrete Beispiele. Diskutiert werden in dieser Arbeit grundlegende intuitive Modelle für folgende inhaltliche Aspekte einer Programmausführung: Allokation von Aktivität bei einer Programmausführung, Benennung von Entitäten, Daten, Funktionen, Verarbeitung, Kontrollstrukturen zur Steuerung von Programmläufen, Rekursion, Klassen und Objekte. Mit Hilfe eines Systems von Online-Spielen, der Python Visual Sandbox, werden die psychische Realität verschiedener intuitiver Modelle bei Programmieranfängern nachgewiesen und fehlerhafte Anwendungen (Fehlvorstellungen) identifiziert.
Software maintenance encompasses any changes made to a software system after its initial deployment and is thereby one of the key phases in the typical software-engineering lifecycle. In software maintenance, we primarily need to understand structural and behavioral aspects, which are difficult to obtain, e.g., by code reading. Software analysis is therefore a vital tool for maintaining these systems: It provides - the preferably automated - means to extract and evaluate information from their artifacts such as software structure, runtime behavior, and related processes. However, such analysis typically results in massive raw data, so that even experienced engineers face difficulties directly examining, assessing, and understanding these data. Among other things, they require tools with which to explore the data if no clear question can be formulated beforehand. For this, software analysis and visualization provide its users with powerful interactive means. These enable the automation of tasks and, particularly, the acquisition of valuable and actionable insights into the raw data. For instance, one means for exploring runtime behavior is trace visualization. This thesis aims at extending and improving the tool set for visual software analysis by concentrating on several open challenges in the fields of dynamic and static analysis of software systems. This work develops a series of concepts and tools for the exploratory visualization of the respective data to support users in finding and retrieving information on the system artifacts concerned. This is a difficult task, due to the lack of appropriate visualization metaphors; in particular, the visualization of complex runtime behavior poses various questions and challenges of both a technical and conceptual nature. This work focuses on a set of visualization techniques for visually representing control-flow related aspects of software traces from shared-memory software systems: A trace-visualization concept based on icicle plots aids in understanding both single-threaded as well as multi-threaded runtime behavior on the function level. The concept’s extensibility further allows the visualization and analysis of specific aspects of multi-threading such as synchronization, the correlation of such traces with data from static software analysis, and a comparison between traces. Moreover, complementary techniques for simultaneously analyzing system structures and the evolution of related attributes are proposed. These aim at facilitating long-term planning of software architecture and supporting management decisions in software projects by extensions to the circular-bundle-view technique: An extension to 3-dimensional space allows for the use of additional variables simultaneously; interaction techniques allow for the modification of structures in a visual manner. The concepts and techniques presented here are generic and, as such, can be applied beyond software analysis for the visualization of similarly structured data. The techniques' practicability is demonstrated by several qualitative studies using subject data from industry-scale software systems. The studies provide initial evidence that the techniques' application yields useful insights into the subject data and its interrelationships in several scenarios.
One of the key challenges in modern Facility Management (FM) is to digitally reflect the current state of the built environment, referred to as-is or as-built versus as-designed representation. While the use of Building Information Modeling (BIM) can address the issue of digital representation, the generation and maintenance of BIM data requires a considerable amount of manual work and domain expertise. Another key challenge is being able to monitor the current state of the built environment, which is used to provide feedback and enhance decision making. The need for an integrated solution for all data associated with the operational life cycle of a building is becoming more pronounced as practices from Industry 4.0 are currently being evaluated and adopted for FM use. This research presents an approach for digital representation of indoor environments in their current state within the life cycle of a given building. Such an approach requires the fusion of various sources of digital data. The key to solving such a complex issue of digital data integration, processing and representation is with the use of a Digital Twin (DT). A DT is a digital duplicate of the physical environment, states, and processes. A DT fuses as-designed and as-built digital representations of built environment with as-is data, typically in the form of floorplans, point clouds and BIMs, with additional information layers pertaining to the current and predicted states of an indoor environment or a complete building (e.g., sensor data). The design, implementation and initial testing of prototypical DT software services for indoor environments is presented and described. These DT software services are implemented within a service-oriented paradigm, and their feasibility is presented through functioning and tested key software components within prototypical Service-Oriented System (SOS) implementations. The main outcome of this research shows that key data related to the built environment can be semantically enriched and combined to enable digital representations of indoor environments, based on the concept of a DT. Furthermore, the outcomes of this research show that digital data, related to FM and Architecture, Construction, Engineering, Owner and Occupant (AECOO) activity, can be combined, analyzed and visualized in real-time using a service-oriented approach. This has great potential to benefit decision making related to Operation and Maintenance (O&M) procedures within the scope of the post-construction life cycle stages of typical office buildings.
Die effektive Erzeugung von Wissen ist eine der zentralen Herausforderungen des 21. Jahrhunderts. Informations- und Kommunikationstechnologien, wie die Neuen Medien, durchdringen alle Bereiche des täglichen Lebens. Sie ermöglichen den Zugriff auf gigantische Datenmengen, die die Grundvoraussetzung für die Generierung von Wissen darstellen, aber gleichzeitig eine Datenflut bedeuten, der wir ohnmächtig gegenüberstehen. Innerhalb der raumwissenschaftlichen Fachdisziplinen spielen die Neuen Medien für die Kommunikation von Sachinformation eine wichtige Rolle. Die internetbasierte Distribution von Karten, angereichert mit zusätzlichen Informationen in Form von Audiosequenzen oder Filmausschnitten, spiegelt diese Entwicklung wieder. Vor diesem Hintergrund erfolgt die Untersuchung der Frage, ob Neue Medien dazu genutzt werden können, raumwissenschaftliche Fachinhalte zu vermitteln. Von besonderem Interesse ist dabei die Frage, ob durch den Einsatz Neuer Medien in der Lehre ein Mehrwert für die Benutzer entsteht. Der Ausgangspunkt dieser Forschungsfrage besteht in der herausragenden Bedeutung von Visualisierung zur leicht verständlichen Darstellung komplexer Sachverhalte, sowie der entsprechenden Werkzeug- und Methodenkompetenz für die Nutzung Neuer Medien in den raumwissen-schaftlichen Disziplinen. Die Grundlage für die Entwicklung von mehrwertigen Lernangeboten ist die Betrachtung von Lernen als Kommunikationsprozess zur Konstruktion von Wissen, was bedeutet, dass der Entwickler derartiger Angebote über Möglichkeiten zur Optimierung dieses Kommunikationsprozesses verfügt. Auf dieser Basis erfolgt eine Erweiterung des in den raumwissenschaftlichen Disziplinen verwendeten Kommunikationsbegriffs um den Aspekt der Lehre von Fachinhalten. Als relevante Ansatzpunkte für die Optimierung der Kommunikation von Fachinhalten werden die didaktische und die mediale Aufbereitung identifiziert. Diese können zum einen die Motivation der Lernenden positiv beeinflussen und zum anderen durch Wirkung auf die Wahrnehmung der Lernenden zu einem vereinfachten Verständnis beitragen. Im Mittelpunkt der didaktischen Aufbereitung steht die problemorientierte Vermittlung der Inhalte, d.h. sie werden anhand konkreter Problemsituationen aus der Praxis vermittelt und gelten deshalb als besonders anschaulich und anwendungsorientiert. Bei der medialen Aufbereitung steht die Verwendung einer Kombination aus Text und Graphik/Animation im Mittelpunkt, die darauf abzielt, das Verstehen komplexer Sachverhalte zu erleichtern. Zur Überprüfung der Forschungsfrage haben Studierende raumwissenschaftlicher Studiengänge der Universität Potsdam das Lernangebot ausprobiert und anhand eines Fragebogens verschiedene Aspekte bewertet. Themenschwerpunkt dieser Evaluation waren die Akzeptanz, die Bedienbarkeit, die didak-tische und mediale Aufbereitung der Inhalte, die Auswahl und Verständlichkeit der Inhalte sowie die Praxistauglichkeit. Ein Großteil der Befragten hat dem Lernangebot einen Mehrwert gegenüber konventionellen Bildungsangeboten bescheinigt. Als Aspekte dieses Mehrwertes haben sich vor allem die Praxisnähe, die Unabhängigkeit von Zeit und Ort bei der Nutzung und die Vermittlung der Inhalte auf der Grundlage einer Kombination aus Text und interaktiven Animationen herauskristallisiert.
Die visuelle Kommunikation ist eine effiziente Methode, um dynamische Phänomene zu beschreiben. Informationsobjekte präzise wahrzunehmen, einen schnellen Zugriff auf strukturierte und relevante Informationen zu ermöglichen, erfordert konsistente und nach dem formalen Minimalprinzip konzipierte Analyse- und Darstellungsmethoden. Dynamische Raumphänomene in Geoinformationssystemen können durch den Mangel an konzeptionellen Optimierungsanpassungen aufgrund ihrer statischen Systemstruktur nur bedingt die Informationen von Raum und Zeit modellieren. Die Forschung in dieser Arbeit ist daher auf drei interdisziplinäre Ansätze fokussiert. Der erste Ansatz stellt eine echtzeitnahe Datenerfassung dar, die in Geodatenbanken zeitorientiert verwaltet wird. Der zweite Ansatz betrachtet Analyse- und Simulationsmethoden, die das dynamische Verhalten analysieren und prognostizieren. Der dritte Ansatz konzipiert Visualisierungsmethoden, die insbesondere dynamische Prozesse abbilden. Die Symbolisierung der Prozesse passt sich bedarfsweise in Abhängigkeit des Prozessverlaufes und der Interaktion zwischen Datenbanken und Simulationsmodellen den verschiedenen Entwicklungsphasen an. Dynamische Aspekte können so mit Hilfe bewährter Funktionen aus der GI-Science zeitnah mit modularen Werkzeugen entwickelt und visualisiert werden. Die Analyse-, Verschneidungs- und Datenverwaltungsfunktionen sollen hierbei als Nutzungs- und Auswertungspotential alternativ zu Methoden statischer Karten dienen. Bedeutend für die zeitliche Komponente ist das Verknüpfen neuer Technologien, z. B. die Simulation und Animation, basierend auf einer strukturierten Zeitdatenbank in Verbindung mit statistischen Verfahren. Methodisch werden Modellansätze und Visualisierungstechniken entwickelt, die auf den Bereich Verkehr transferiert werden. Verkehrsdynamische Phänomene, die nicht zusammenhängend und umfassend darstellbar sind, werden modular in einer serviceorientierten Architektur separiert, um sie in verschiedenen Ebenen räumlich und zeitlich visuell zu präsentieren. Entwicklungen der Vergangenheit und Prognosen der Zukunft werden über verschiedene Berechnungsmethoden modelliert und visuell analysiert. Die Verknüpfung einer Mikrosimulation (Abbildung einzelner Fahrzeuge) mit einer netzgesteuerten Makrosimulation (Abbildung eines gesamten Straßennetzes) ermöglicht eine maßstabsunabhängige Simulation und Visualisierung des Mobilitätsverhaltens ohne zeitaufwendige Bewertungsmodellberechnungen. Zukünftig wird die visuelle Analyse raum-zeitlicher Veränderungen für planerische Entscheidungen ein effizientes Mittel sein, um Informationen übergreifend verfügbar, klar strukturiert und zweckorientiert zur Verfügung zu stellen. Der Mehrwert durch visuelle Geoanalysen, die modular in einem System integriert sind, ist das flexible Auswerten von Messdaten nach zeitlichen und räumlichen Merkmalen.
This work introduces novel internal and external memory algorithms for computing voxel skeletons of massive voxel objects with complex network-like architecture and for converting these voxel skeletons to piecewise linear geometry, that is triangle meshes and piecewise straight lines. The presented techniques help to tackle the challenge of visualizing and analyzing 3d images of increasing size and complexity, which are becoming more and more important in, for example, biological and medical research. Section 2.3.1 contributes to the theoretical foundations of thinning algorithms with a discussion of homotopic thinning in the grid cell model. The grid cell model explicitly represents a cell complex built of faces, edges, and vertices shared between voxels. A characterization of pairs of cells to be deleted is much simpler than characterizations of simple voxels were before. The grid cell model resolves topologically unclear voxel configurations at junctions and locked voxel configurations causing, for example, interior voxels in sets of non-simple voxels. A general conclusion is that the grid cell model is superior to indecomposable voxels for algorithms that need detailed control of topology. Section 2.3.2 introduces a noise-insensitive measure based on the geodesic distance along the boundary to compute two-dimensional skeletons. The measure is able to retain thin object structures if they are geometrically important while ignoring noise on the object's boundary. This combination of properties is not known of other measures. The measure is also used to guide erosion in a thinning process from the boundary towards lines centered within plate-like structures. Geodesic distance based quantities seem to be well suited to robustly identify one- and two-dimensional skeletons. Chapter 6 applies the method to visualization of bone micro-architecture. Chapter 3 describes a novel geometry generation scheme for representing voxel skeletons, which retracts voxel skeletons to piecewise linear geometry per dual cube. The generated triangle meshes and graphs provide a link to geometry processing and efficient rendering of voxel skeletons. The scheme creates non-closed surfaces with boundaries, which contain fewer triangles than a representation of voxel skeletons using closed surfaces like small cubes or iso-surfaces. A conclusion is that thinking specifically about voxel skeleton configurations instead of generic voxel configurations helps to deal with the topological implications. The geometry generation is one foundation of the applications presented in Chapter 6. Chapter 5 presents a novel external memory algorithm for distance ordered homotopic thinning. The presented method extends known algorithms for computing chamfer distance transformations and thinning to execute I/O-efficiently when input is larger than the available main memory. The applied block-wise decomposition schemes are quite simple. Yet it was necessary to carefully analyze effects of block boundaries to devise globally correct external memory variants of known algorithms. In general, doing so is superior to naive block-wise processing ignoring boundary effects. Chapter 6 applies the algorithms in a novel method based on confocal microscopy for quantitative study of micro-vascular networks in the field of microcirculation.
Bei der Erstellung von Visualisierungen gibt es im Wesentlichen zwei Ansätze. Zum einen können mit geringem Aufwand schnell Standarddiagramme erstellt werden. Zum anderen gibt es die Möglichkeit, individuelle und interaktive Visualisierungen zu programmieren. Dies ist jedoch mit einem deutlich höheren Aufwand verbunden.
Flower ermöglicht eine schnelle Erstellung individueller und interaktiver Visualisierungen, indem es den Entwicklungssprozess stark vereinfacht und die Nutzer bei den einzelnen Aktivitäten wie dem Import und der Aufbereitung von Daten, deren Abbildung auf visuelle Elemente sowie der Integration von Interaktivität direkt unterstützt.
Today, point clouds are among the most important categories of spatial data, as they constitute digital 3D models of the as-is reality that can be created at unprecedented speed and precision. However, their unique properties, i.e., lack of structure, order, or connectivity information, necessitate specialized data structures and algorithms to leverage their full precision. In particular, this holds true for the interactive visualization of point clouds, which requires to balance hardware limitations regarding GPU memory and bandwidth against a naturally high susceptibility to visual artifacts.
This thesis focuses on concepts, techniques, and implementations of robust, scalable, and portable 3D visualization systems for massive point clouds. To that end, a number of rendering, visualization, and interaction techniques are introduced, that extend several basic strategies to decouple rendering efforts and data management: First, a novel visualization technique that facilitates context-aware filtering, highlighting, and interaction within point cloud depictions. Second, hardware-specific optimization techniques that improve rendering performance and image quality in an increasingly diversified hardware landscape. Third, natural and artificial locomotion techniques for nausea-free exploration in the context of state-of-the-art virtual reality devices. Fourth, a framework for web-based rendering that enables collaborative exploration of point clouds across device ecosystems and facilitates the integration into established workflows and software systems.
In cooperation with partners from industry and academia, the practicability and robustness of the presented techniques are showcased via several case studies using representative application scenarios and point cloud data sets. In summary, the work shows that the interactive visualization of point clouds can be implemented by a multi-tier software architecture with a number of domain-independent, generic system components that rely on optimization strategies specific to large point clouds. It demonstrates the feasibility of interactive, scalable point cloud visualization as a key component for distributed IT solutions that operate with spatial digital twins, providing arguments in favor of using point clouds as a universal type of spatial base data usable directly for visualization purposes.
Spatio-temporal data denotes a category of data that contains spatial as well as temporal components. For example, time-series of geo-data, thematic maps that change over time, or tracking data of moving entities can be interpreted as spatio-temporal data.
In today's automated world, an increasing number of data sources exist, which constantly generate spatio-temporal data. This includes for example traffic surveillance systems, which gather movement data about human or vehicle movements, remote-sensing systems, which frequently scan our surroundings and produce digital representations of cities and landscapes, as well as sensor networks in different domains, such as logistics, animal behavior study, or climate research.
For the analysis of spatio-temporal data, in addition to automatic statistical and data mining methods, exploratory analysis methods are employed, which are based on interactive visualization. These analysis methods let users explore a data set by interactively manipulating a visualization, thereby employing the human cognitive system and knowledge of the users to find patterns and gain insight into the data.
This thesis describes a software framework for the visualization of spatio-temporal data, which consists of GPU-based techniques to enable the interactive visualization and exploration of large spatio-temporal data sets. The developed techniques include data management, processing, and rendering, facilitating real-time processing and visualization of large geo-temporal data sets. It includes three main contributions:
- Concept and Implementation of a GPU-Based Visualization Pipeline.
The developed visualization methods are based on the concept of a GPU-based visualization pipeline, in which all steps -- processing, mapping, and rendering -- are implemented on the GPU. With this concept, spatio-temporal data is represented directly in GPU memory, using shader programs to process and filter the data, apply mappings to visual properties, and finally generate the geometric representations for a visualization during the rendering process. Data processing, filtering, and mapping are thereby executed in real-time, enabling dynamic control over the mapping and a visualization process which can be controlled interactively by a user.
- Attributed 3D Trajectory Visualization.
A visualization method has been developed for the interactive exploration of large numbers of 3D movement trajectories. The trajectories are visualized in a virtual geographic environment, supporting basic geometries such as lines, ribbons, spheres, or tubes. Interactive mapping can be applied to visualize the values of per-node or per-trajectory attributes, supporting shape, height, size, color, texturing, and animation as visual properties. Using the dynamic mapping system, several kind of visualization methods have been implemented, such as focus+context visualization of trajectories using interactive density maps, and space-time cube visualization to focus on the temporal aspects of individual movements.
- Geographic Network Visualization.
A method for the interactive exploration of geo-referenced networks has been developed, which enables the visualization of large numbers of nodes and edges in a geographic context. Several geographic environments are supported, such as a 3D globe, as well as 2D maps using different map projections, to enable the analysis of networks in different contexts and scales. Interactive filtering, mapping, and selection can be applied to analyze these geographic networks, and visualization methods for specific types of networks, such as coupled 3D networks or temporal networks have been implemented.
As a demonstration of the developed visualization concepts, interactive visualization tools for two distinct use cases have been developed. The first contains the visualization of attributed 3D movement trajectories of airplanes around an airport. It allows users to explore and analyze the trajectories of approaching and departing aircrafts, which have been recorded over the period of a month. By applying the interactive visualization methods for trajectory visualization and interactive density maps, analysts can derive insight from the data, such as common flight paths, regular and irregular patterns, or uncommon incidents such as missed approaches on the airport.
The second use case involves the visualization of climate networks, which are geographic networks in the climate research domain. They represent the dynamics of the climate system using a network structure that expresses statistical interrelationships between different regions. The interactive tool allows climate analysts to explore these large networks, analyzing the network's structure and relating it to the geographic background. Interactive filtering and selection enables them to find patterns in the climate data and identify e.g. clusters in the networks or flow patterns.