Visual place recognition is the task of finding same places in a set of database images for a given set of query images. This becomes particularly challenging for long-term applications when the environmental condition changes between or within the database and query set, e.g., from day to night. Visual place recognition in changing environments can be used if global position data like GPS is not available or very inaccurate, or for redundancy. It is required for tasks like loop closure detection in SLAM, candidate selection for global localization, or multi-robot/multi-session mapping and map merging. In contrast to pure image retrieval, visual place recognition can often build upon additional information and data for improvements in performance, runtime, or memory usage. This includes additional data-inherent knowledge about information that is contained in the image sets themselves because of the way they were recorded. Using data-inherent knowledge avoids the dependency on other sensors, which increases the generality of methods for an integration into many existing place recognition pipelines. This thesis focuses on the usage of additional data-inherent knowledge. After the discussion of basics about visual place recognition, the thesis gives a systematic overview of existing data-inherent knowledge and corresponding methods. Subsequently, the thesis concentrates on a deeper consideration and exploitation of four different types of additional data-inherent knowledge. This includes 1) sequences, i.e., the database and query set are recorded as spatio-temporal sequences so that consecutive images are also adjacent in the world, 2) knowledge of whether the environmental conditions within the database and query set are constant or continuously changing, 3) intra-database similarities between the database images, and 4) intra-query similarities between the query images. Except for sequences, all types have received only little attention in the literature so far. For the exploitation of knowledge about constant conditions within the database and query set (e.g., database: summer, query: winter), the thesis evaluates different descriptor standardization techniques. For the alternative scenario of continuous condition changes (e.g., database: sunny to rainy, query: sunny to cloudy), the thesis first investigates the qualitative and quantitative impact on the performance of image descriptors. It then proposes and evaluates four unsupervised learning methods, including our novel clustering-based descriptor standardization method K-STD and three PCA-based methods from the literature. To address the high computational effort of descriptor comparisons during place recognition, our novel method EPR for efficient place recognition is proposed. Given a query descriptor, EPR uses sequence information and intra-database similarities to identify nearly all matching descriptors in the database. For a structured combination of several sources of additional knowledge in a single graph, the thesis presents our novel graphical framework for place recognition. After the minimization of the graph's error with our proposed ICM-based optimization, the place recognition performance can be significantly improved. For an extensive experimental evaluation of all methods in this thesis and beyond, a benchmark for visual place recognition in changing environments is presented, which is composed of six datasets with thirty sequence combinations.

This thesis extends a localisation theory for finite algebras to certain classes of infinite structures. Based on ideas and constructions originally stemming from Tame Congruence Theory, algebras are studied via local restrictions of their relational counterpart (Relational Structure Theory). In this respect, first those subsets are identified that are suitable for such a localisation process, i. e. that are compatible with the relational clone structure of the counterpart of an algebra. It is then studied which properties of the global algebra can be transferred to its localisations, called neighbourhoods. Thereafter, it is discussed how this process can be reversed, leading to the concept of covers. These are collections of neighbourhoods that allow information retrieval about the global structure from knowledge about the local restrictions. Subsequently, covers are characterised in terms of a decomposition equation, and connections to categorical equivalences of algebras are explored. In the second half of the thesis, a refinement concept for covers is introduced in order to find optimal, non-refinable covers, eventually leading to practical algorithms for their determination. Finally, the text establishes further theoretical foundations, e. g. several irreducibility notions, in order to ensure existence of non-refinable covers via an intrinsic characterisation, and to prove under some conditions that they are uniquely determined in a canonical sense. At last, the applicability of the developed techniques is demonstrated using two clear expository examples. / Diese Dissertation erweitert eine Lokalisierungstheorie für endliche Algebren auf gewisse Klassen unendlicher Strukturen. Basierend auf Ideen und Konstruktionen, die ursprünglich der Tame Congruence Theory entstammen, werden Algebren über lokale Einschränkungen ihres relationalen Gegenstücks untersucht (Relationale Strukturtheorie). In diesem Zusammenhang werden zunächst diejenigen Teilmengen identifiziert, welche für einen solchen Lokalisierungsprozeß geeignet sind, d. h., die mit der Relationenklonstruktur auf dem Gegenstück einer Algebra kompatibel sind. Es wird dann untersucht, welche Eigenschaften der globalen Algebra auf ihre Lokalisierungen, genannt Umgebungen, übertragen werden können. Nachfolgend wird diskutiert, wie dieser Vorgang umgekehrt werden kann, was zum Begriff der Überdeckungen führt. Dies sind Systeme von Umgebungen, welche die Rückgewinnung von Informationen über die globale Struktur aus Kenntnis ihrer lokalen Einschränkungen erlauben. Sodann werden Überdeckungen durch eine Zerlegungsgleichung charakterisiert und Bezüge zu kategoriellen Äquivalenzen von Algebren hergestellt. In der zweiten Hälfte der Arbeit wird ein Verfeinerungsbegriff für Überdeckungen eingeführt, um optimale, nichtverfeinerbare Überdeckungen zu finden, was letztlich zu praktischen Algorithmen zu ihrer Bestimmung führt. Schließlich erarbeitet der Text weitere theoretische Grundlagen, beispielsweise mehrere Irreduzibilitätsbegriffe, um die Existenz nichtverfeinerbarer Überdeckungen vermöge einer intrinsischen Charakterisierung sicherzustellen und, unter gewissen Bedingungen, zu beweisen, daß sie in kanonischer Weise eindeutig bestimmt sind. Schlußendlich wird die Anwendbarkeit der entwickelten Methoden an zwei übersichtlichen Beispielen demonstriert.

Superpixels are the results of an image oversegmentation. They are an established intermediate level image representation and used for various applications including object detection, 3d reconstruction and semantic segmentation. While there are various approaches to create such segmentations, there is a lack of knowledge about their properties. In particular, there are contradicting results published in the literature. This thesis identifies segmentation quality, stability, compactness and runtime to be important properties of superpixel segmentation algorithms. While for some of these properties there are established evaluation methodologies available, this is not the case for segmentation stability and compactness. Therefore, this thesis presents two novel metrics for their evaluation based on ground truth optical flow. These two metrics are used together with other novel and existing measures to create a standardized benchmark for superpixel algorithms. This benchmark is used for extensive comparison of available algorithms. The evaluation results motivate two novel segmentation algorithms that better balance trade-offs of existing algorithms: The proposed Preemptive SLIC algorithm incorporates a local preemption criterion in the established SLIC algorithm and saves about 80 % of the runtime. The proposed Compact Watershed algorithm combines Seeded Watershed segmentation with compactness constraints to create regularly shaped, compact superpixels at the even higher speed of the plain watershed transformation. Operating autonomous systems over the course of days, weeks or months, based on visual navigation, requires repeated recognition of places despite severe appearance changes as they are for example induced by illumination changes, day-night cycles, changing weather or seasons - a severe problem for existing methods. Therefore, the second part of this thesis presents two novel approaches that incorporate superpixel segmentations in place recognition in changing environments. The first novel approach is the learning of systematic appearance changes. Instead of matching images between, for example, summer and winter directly, an additional prediction step is proposed. Based on superpixel vocabularies, a predicted image is generated that shows, how the summer scene could look like in winter or vice versa. The presented results show that, if certain assumptions on the appearance changes and the available training data are met, existing holistic place recognition approaches can benefit from this additional prediction step. Holistic approaches to place recognition are known to fail in presence of viewpoint changes. Therefore, this thesis presents a new place recognition system based on local landmarks and Star-Hough. Star-Hough is a novel approach to incorporate the spatial arrangement of local image features in the computation of image similarities. It is based on star graph models and Hough voting and particularly suited for local features with low spatial precision and high outlier rates as they are expected in the presence of appearance changes. The novel landmarks are a combination of local region detectors and descriptors based on convolutional neural networks. This thesis presents and evaluates several new approaches to incorporate superpixel segmentations in local region detection. While the proposed system can be used with different types of local regions, in particular the combination with regions obtained from the novel multiscale superpixel grid shows to perform superior to the state of the art methods - a promising basis for practical applications.

Information visualization is an important research field concerned with making sense and inferring knowledge from data collections. Graph visualizations are specific techniques for data representation relevant in diverse application domains among them biology, software-engineering, and business finance. These data visualizations benefit from the display space provided by novel interactive large display environments. However, these environments also cause new challenges and result in new requirements regarding the need for interaction beyond the desktop and according redesign of analysis tools. This thesis focuses on interactive magic lenses, specialized locally applied tools that temporarily manipulate the visualization. These may include magnification of focus regions but also more graph-specific functions such as pulling in neighboring nodes or locally reducing edge clutter. Up to now, these lenses have mostly been used as single-user, single-purpose tools operated by mouse and keyboard. This dissertation presents the extension of magic lenses both in terms of function as well as interaction for large vertical displays. In particular, this thesis contributes several natural interaction designs with magic lenses for the exploration of graph data in node-link visualizations using diverse interaction modalities. This development incorporates flexible switches between lens functions, adjustment of individual lens properties and function parameters, as well as the combination of lenses. It proposes interaction techniques for fluent multi-touch manipulation of lenses, controlling lenses using mobile devices in front of large displays, and a novel concept of body-controlled magic lenses. Functional extensions in addition to these interaction techniques convert the lenses to user-configurable, personal territories with use of alternative interaction styles. To create the foundation for this extension, the dissertation incorporates a comprehensive design space of magic lenses, their function, parameters, and interactions. Additionally, it provides a discussion on increased embodiment in tool and controller design, contributing insights into user position and movement in front of large vertical displays as a result of empirical investigations and evaluations. / Informationsvisualisierung ist ein wichtiges Forschungsfeld, das das Analysieren von Daten unterstützt. Graph-Visualisierungen sind dabei eine spezielle Variante der Datenrepräsentation, deren Nutzen in vielerlei Anwendungsfällen zum Einsatz kommt, u.a. in der Biologie, Softwareentwicklung und Finanzwirtschaft. Diese Datendarstellungen profitieren besonders von großen Displays in neuen Displayumgebungen. Jedoch bringen diese Umgebungen auch neue Herausforderungen mit sich und stellen Anforderungen an Nutzerschnittstellen jenseits der traditionellen Ansätze, die dadurch auch Anpassungen von Analysewerkzeugen erfordern. Diese Dissertation befasst sich mit interaktiven „Magischen Linsen“, spezielle lokal-angewandte Werkzeuge, die temporär die Visualisierung zur Analyse manipulieren. Dabei existieren zum Beispiel Vergrößerungslinsen, aber auch Graph-spezifische Manipulationen, wie das Anziehen von Nachbarknoten oder das Reduzieren von Kantenüberlappungen im lokalen Bereich. Bisher wurden diese Linsen vor allem als Werkzeug für einzelne Nutzer mit sehr spezialisiertem Effekt eingesetzt und per Maus und Tastatur bedient. Die vorliegende Doktorarbeit präsentiert die Erweiterung dieser magischen Linsen, sowohl in Bezug auf die Funktionalität als auch für die Interaktion an großen, vertikalen Displays. Insbesondere trägt diese Dissertation dazu bei, die Exploration von Graphen mit magischen Linsen durch natürliche Interaktion mit unterschiedlichen Modalitäten zu unterstützen. Dabei werden flexible Änderungen der Linsenfunktion, Anpassungen von individuellen Linseneigenschaften und Funktionsparametern, sowie die Kombination unterschiedlicher Linsen ermöglicht. Es werden Interaktionstechniken für die natürliche Manipulation der Linsen durch Multitouch-Interaktion, sowie das Kontrollieren von Linsen durch Mobilgeräte vor einer Displaywand vorgestellt. Außerdem wurde ein neuartiges Konzept körpergesteuerter magischer Linsen entwickelt. Funktionale Erweiterungen in Kombination mit diesen Interaktionskonzepten machen die Linse zu einem vom Nutzer einstellbaren, persönlichen Arbeitsbereich, der zudem alternative Interaktionsstile erlaubt. Als Grundlage für diese Erweiterungen stellt die Dissertation eine umfangreiche analytische Kategorisierung bisheriger Forschungsarbeiten zu magischen Linsen vor, in der Funktionen, Parameter und Interaktion mit Linsen eingeordnet werden. Zusätzlich macht die Arbeit Vor- und Nachteile körpernaher Interaktion für Werkzeuge bzw. ihre Steuerung zum Thema und diskutiert dabei Nutzerposition und -bewegung an großen Displaywänden belegt durch empirische Nutzerstudien.

Probabilistic models of decision making under various forms of uncertainty have been applied in recent years to numerous behavioral and model-based fMRI studies. These studies were highly successful in enabling a better understanding of behavior and delineating the functional properties of brain areas involved in decision making under uncertainty. However, as different studies considered different models of decision making under uncertainty, it is unclear which of these computational models provides the best account of the observed behavioral and neuroimaging data. This is an important issue, as not performing model comparison may tempt researchers to over-interpret results based on a single model. Here we describe how in practice one can compare different behavioral models and test the accuracy of model comparison and parameter estimation of Bayesian and maximum-likelihood based methods. We focus our analysis on two well-established hierarchical probabilistic models that aim at capturing the evolution of beliefs in changing environments: Hierarchical Gaussian Filters and Change Point Models. To our knowledge, these two, well-established models have never been compared on the same data. We demonstrate, using simulated behavioral experiments, that one can accurately disambiguate between these two models, and accurately infer free model parameters and hidden belief trajectories (e.g., posterior expectations, posterior uncertainties, and prediction errors) even when using noisy and highly correlated behavioral measurements. Importantly, we found several advantages of Bayesian inference and Bayesian model comparison compared to often-used Maximum-Likelihood schemes combined with the Bayesian Information Criterion. These results stress the relevance of Bayesian data analysis for model-based neuroimaging studies that investigate human decision making under uncertainty.

Probabilistic models of decision making under various forms of uncertainty have been applied in recent years to numerous behavioral and model-based fMRI studies. These studies were highly successful in enabling a better understanding of behavior and delineating the functional properties of brain areas involved in decision making under uncertainty. However, as different studies considered different models of decision making under uncertainty, it is unclear which of these computational models provides the best account of the observed behavioral and neuroimaging data. This is an important issue, as not performing model comparison may tempt researchers to over-interpret results based on a single model. Here we describe how in practice one can compare different behavioral models and test the accuracy of model comparison and parameter estimation of Bayesian and maximum-likelihood based methods. We focus our analysis on two well-established hierarchical probabilistic models that aim at capturing the evolution of beliefs in changing environments: Hierarchical Gaussian Filters and Change Point Models. To our knowledge, these two, well-established models have never been compared on the same data. We demonstrate, using simulated behavioral experiments, that one can accurately disambiguate between these two models, and accurately infer free model parameters and hidden belief trajectories (e.g., posterior expectations, posterior uncertainties, and prediction errors) even when using noisy and highly correlated behavioral measurements. Importantly, we found several advantages of Bayesian inference and Bayesian model comparison compared to often-used Maximum-Likelihood schemes combined with the Bayesian Information Criterion. These results stress the relevance of Bayesian data analysis for model-based neuroimaging studies that investigate human decision making under uncertainty.

Information visualization is an important research field concerned with making sense and inferring knowledge from data collections. Graph visualizations are specific techniques for data representation relevant in diverse application domains among them biology, software-engineering, and business finance. These data visualizations benefit from the display space provided by novel interactive large display environments. However, these environments also cause new challenges and result in new requirements regarding the need for interaction beyond the desktop and according redesign of analysis tools. This thesis focuses on interactive magic lenses, specialized locally applied tools that temporarily manipulate the visualization. These may include magnification of focus regions but also more graph-specific functions such as pulling in neighboring nodes or locally reducing edge clutter. Up to now, these lenses have mostly been used as single-user, single-purpose tools operated by mouse and keyboard. This dissertation presents the extension of magic lenses both in terms of function as well as interaction for large vertical displays. In particular, this thesis contributes several natural interaction designs with magic lenses for the exploration of graph data in node-link visualizations using diverse interaction modalities. This development incorporates flexible switches between lens functions, adjustment of individual lens properties and function parameters, as well as the combination of lenses. It proposes interaction techniques for fluent multi-touch manipulation of lenses, controlling lenses using mobile devices in front of large displays, and a novel concept of body-controlled magic lenses. Functional extensions in addition to these interaction techniques convert the lenses to user-configurable, personal territories with use of alternative interaction styles. To create the foundation for this extension, the dissertation incorporates a comprehensive design space of magic lenses, their function, parameters, and interactions. Additionally, it provides a discussion on increased embodiment in tool and controller design, contributing insights into user position and movement in front of large vertical displays as a result of empirical investigations and evaluations. / Informationsvisualisierung ist ein wichtiges Forschungsfeld, das das Analysieren von Daten unterstützt. Graph-Visualisierungen sind dabei eine spezielle Variante der Datenrepräsentation, deren Nutzen in vielerlei Anwendungsfällen zum Einsatz kommt, u.a. in der Biologie, Softwareentwicklung und Finanzwirtschaft. Diese Datendarstellungen profitieren besonders von großen Displays in neuen Displayumgebungen. Jedoch bringen diese Umgebungen auch neue Herausforderungen mit sich und stellen Anforderungen an Nutzerschnittstellen jenseits der traditionellen Ansätze, die dadurch auch Anpassungen von Analysewerkzeugen erfordern. Diese Dissertation befasst sich mit interaktiven „Magischen Linsen“, spezielle lokal-angewandte Werkzeuge, die temporär die Visualisierung zur Analyse manipulieren. Dabei existieren zum Beispiel Vergrößerungslinsen, aber auch Graph-spezifische Manipulationen, wie das Anziehen von Nachbarknoten oder das Reduzieren von Kantenüberlappungen im lokalen Bereich. Bisher wurden diese Linsen vor allem als Werkzeug für einzelne Nutzer mit sehr spezialisiertem Effekt eingesetzt und per Maus und Tastatur bedient. Die vorliegende Doktorarbeit präsentiert die Erweiterung dieser magischen Linsen, sowohl in Bezug auf die Funktionalität als auch für die Interaktion an großen, vertikalen Displays. Insbesondere trägt diese Dissertation dazu bei, die Exploration von Graphen mit magischen Linsen durch natürliche Interaktion mit unterschiedlichen Modalitäten zu unterstützen. Dabei werden flexible Änderungen der Linsenfunktion, Anpassungen von individuellen Linseneigenschaften und Funktionsparametern, sowie die Kombination unterschiedlicher Linsen ermöglicht. Es werden Interaktionstechniken für die natürliche Manipulation der Linsen durch Multitouch-Interaktion, sowie das Kontrollieren von Linsen durch Mobilgeräte vor einer Displaywand vorgestellt. Außerdem wurde ein neuartiges Konzept körpergesteuerter magischer Linsen entwickelt. Funktionale Erweiterungen in Kombination mit diesen Interaktionskonzepten machen die Linse zu einem vom Nutzer einstellbaren, persönlichen Arbeitsbereich, der zudem alternative Interaktionsstile erlaubt. Als Grundlage für diese Erweiterungen stellt die Dissertation eine umfangreiche analytische Kategorisierung bisheriger Forschungsarbeiten zu magischen Linsen vor, in der Funktionen, Parameter und Interaktion mit Linsen eingeordnet werden. Zusätzlich macht die Arbeit Vor- und Nachteile körpernaher Interaktion für Werkzeuge bzw. ihre Steuerung zum Thema und diskutiert dabei Nutzerposition und -bewegung an großen Displaywänden belegt durch empirische Nutzerstudien.

In dieser Arbeit werden Unternehmensnetzwerke aus einer abhängigkeitsbasierten Perspektive betrachtet und es wird ein Beitrag zum Management solcher Netzwerke geleistet. Unter dem Begriff Management wird im Kontext dieser Arbeit die ganzheitliche Planung, Kontrolle und Steuerung verstanden. Dabei wurden in sechs wissenschaftlichen Erst- und Koautorenschaften diverse gestaltungsorientierte Forschungsergebnisse in Form von Design-Science-Artefakten entwickelt. Mit deren Hilfe können Managementaktivitäten in den Bereichen Business-IT-Alignment, Partnerauswahl in Netzwerken, sowie IT-Governance auf der Basis von Abhängigkeiten mit interorganisationaler Ausprägung betrachtet und gemeistert werden. In dieser kumulativen Dissertationsschrift werden die Resultate entlang des Lebenszyklus von Unternehmensnetzwerken eingeordnet, wodurch die Relevanz der eingereichten Artikel auf die einzelnen Netzwerklebensphasen gespiegelt wird. Zudem werden sowohl theoretische als auch praktische Implikationen der Resultate diskutiert. Insgesamt tragen sowohl die ganzheitliche Sichtweise als auch der interdisziplinäre Charakter der Ausarbeitungen zu einem gesteigerten Verständnis von Abhängigkeitsbeziehungen in Unternehmensnetzwerken bei.

Superpixels are the results of an image oversegmentation. They are an established intermediate level image representation and used for various applications including object detection, 3d reconstruction and semantic segmentation. While there are various approaches to create such segmentations, there is a lack of knowledge about their properties. In particular, there are contradicting results published in the literature. This thesis identifies segmentation quality, stability, compactness and runtime to be important properties of superpixel segmentation algorithms. While for some of these properties there are established evaluation methodologies available, this is not the case for segmentation stability and compactness. Therefore, this thesis presents two novel metrics for their evaluation based on ground truth optical flow. These two metrics are used together with other novel and existing measures to create a standardized benchmark for superpixel algorithms. This benchmark is used for extensive comparison of available algorithms. The evaluation results motivate two novel segmentation algorithms that better balance trade-offs of existing algorithms: The proposed Preemptive SLIC algorithm incorporates a local preemption criterion in the established SLIC algorithm and saves about 80 % of the runtime. The proposed Compact Watershed algorithm combines Seeded Watershed segmentation with compactness constraints to create regularly shaped, compact superpixels at the even higher speed of the plain watershed transformation. Operating autonomous systems over the course of days, weeks or months, based on visual navigation, requires repeated recognition of places despite severe appearance changes as they are for example induced by illumination changes, day-night cycles, changing weather or seasons - a severe problem for existing methods. Therefore, the second part of this thesis presents two novel approaches that incorporate superpixel segmentations in place recognition in changing environments. The first novel approach is the learning of systematic appearance changes. Instead of matching images between, for example, summer and winter directly, an additional prediction step is proposed. Based on superpixel vocabularies, a predicted image is generated that shows, how the summer scene could look like in winter or vice versa. The presented results show that, if certain assumptions on the appearance changes and the available training data are met, existing holistic place recognition approaches can benefit from this additional prediction step. Holistic approaches to place recognition are known to fail in presence of viewpoint changes. Therefore, this thesis presents a new place recognition system based on local landmarks and Star-Hough. Star-Hough is a novel approach to incorporate the spatial arrangement of local image features in the computation of image similarities. It is based on star graph models and Hough voting and particularly suited for local features with low spatial precision and high outlier rates as they are expected in the presence of appearance changes. The novel landmarks are a combination of local region detectors and descriptors based on convolutional neural networks. This thesis presents and evaluates several new approaches to incorporate superpixel segmentations in local region detection. While the proposed system can be used with different types of local regions, in particular the combination with regions obtained from the novel multiscale superpixel grid shows to perform superior to the state of the art methods - a promising basis for practical applications.

This thesis extends a localisation theory for finite algebras to certain classes of infinite structures. Based on ideas and constructions originally stemming from Tame Congruence Theory, algebras are studied via local restrictions of their relational counterpart (Relational Structure Theory). In this respect, first those subsets are identified that are suitable for such a localisation process, i. e. that are compatible with the relational clone structure of the counterpart of an algebra. It is then studied which properties of the global algebra can be transferred to its localisations, called neighbourhoods. Thereafter, it is discussed how this process can be reversed, leading to the concept of covers. These are collections of neighbourhoods that allow information retrieval about the global structure from knowledge about the local restrictions. Subsequently, covers are characterised in terms of a decomposition equation, and connections to categorical equivalences of algebras are explored. In the second half of the thesis, a refinement concept for covers is introduced in order to find optimal, non-refinable covers, eventually leading to practical algorithms for their determination. Finally, the text establishes further theoretical foundations, e. g. several irreducibility notions, in order to ensure existence of non-refinable covers via an intrinsic characterisation, and to prove under some conditions that they are uniquely determined in a canonical sense. At last, the applicability of the developed techniques is demonstrated using two clear expository examples.:1 Introduction 2 Preliminaries and Notation 2.1 Functions, operations and relations 2.2 Algebras and relational structures 2.3 Clones 3 Relational Structure Theory 3.1 Finding suitable subsets for localisation 3.2 Neighbourhoods 3.3 The restricted algebra A|U 3.4 Covers 3.5 Refinement 3.6 Irreducibility notions 3.7 Intrinsic description of non-refinable covers 3.8 Elaborated example 4 Problems and Prospects for Future Research Acknowledgements Index of Notation Index of Terms Bibliography / Diese Dissertation erweitert eine Lokalisierungstheorie für endliche Algebren auf gewisse Klassen unendlicher Strukturen. Basierend auf Ideen und Konstruktionen, die ursprünglich der Tame Congruence Theory entstammen, werden Algebren über lokale Einschränkungen ihres relationalen Gegenstücks untersucht (Relationale Strukturtheorie). In diesem Zusammenhang werden zunächst diejenigen Teilmengen identifiziert, welche für einen solchen Lokalisierungsprozeß geeignet sind, d. h., die mit der Relationenklonstruktur auf dem Gegenstück einer Algebra kompatibel sind. Es wird dann untersucht, welche Eigenschaften der globalen Algebra auf ihre Lokalisierungen, genannt Umgebungen, übertragen werden können. Nachfolgend wird diskutiert, wie dieser Vorgang umgekehrt werden kann, was zum Begriff der Überdeckungen führt. Dies sind Systeme von Umgebungen, welche die Rückgewinnung von Informationen über die globale Struktur aus Kenntnis ihrer lokalen Einschränkungen erlauben. Sodann werden Überdeckungen durch eine Zerlegungsgleichung charakterisiert und Bezüge zu kategoriellen Äquivalenzen von Algebren hergestellt. In der zweiten Hälfte der Arbeit wird ein Verfeinerungsbegriff für Überdeckungen eingeführt, um optimale, nichtverfeinerbare Überdeckungen zu finden, was letztlich zu praktischen Algorithmen zu ihrer Bestimmung führt. Schließlich erarbeitet der Text weitere theoretische Grundlagen, beispielsweise mehrere Irreduzibilitätsbegriffe, um die Existenz nichtverfeinerbarer Überdeckungen vermöge einer intrinsischen Charakterisierung sicherzustellen und, unter gewissen Bedingungen, zu beweisen, daß sie in kanonischer Weise eindeutig bestimmt sind. Schlußendlich wird die Anwendbarkeit der entwickelten Methoden an zwei übersichtlichen Beispielen demonstriert.:1 Introduction 2 Preliminaries and Notation 2.1 Functions, operations and relations 2.2 Algebras and relational structures 2.3 Clones 3 Relational Structure Theory 3.1 Finding suitable subsets for localisation 3.2 Neighbourhoods 3.3 The restricted algebra A|U 3.4 Covers 3.5 Refinement 3.6 Irreducibility notions 3.7 Intrinsic description of non-refinable covers 3.8 Elaborated example 4 Problems and Prospects for Future Research Acknowledgements Index of Notation Index of Terms Bibliography