jETI: ein serviceorientiertes framework zur high level Ausführung von Remote-Komponenten

Mit dem massiven Aufkommen an geschäftlichem Datenaustausch in Zeiten voranschreitender Globalisierung, dem Erfolg des Community getriebenen Web 2.0 und dem expliziten Wandel hin zur serviceorientierten Denkweise insbesondere im Kontext komplexer Geschäftsprozesse wird vor allem deutlich, dass wachsender Bedarf an einer offenen, standardisierten Technologie zur Vernetzung, Ausführung und Bereitstellung von Diensten und Prozessen besteht. Um diesen Bedarf zu decken, bestehende Probleme zu lösen und neue Aspekte der Ausführung vernetzter Dienste zu erkennen soll in dieser Arbeit eine ganzheitliche Experimentierplattform zur serviceorientierten Orchestrierung, insbesondere von verteilt agierenden Komponenten vorgestellt werden. Nutzer sollen dabei in die Lage versetzt werden, Funktionalitäten auf eine möglichst einfache Art und Weise ausprobieren, benutzen und anbieten zu können. Im Kern soll hier der Teilbereich einer integrierten Umgebung beleuchtet werden, welche die Verifikation und Handhabung von standardisierten Remote Service Komponenten als auch die Anbindung heterogener, proprietärer Dienste von Drittanbietern unterstützt. Die vorgelegte Arbeit umfasst dabei vor allem die Konzeption und Realisierung einer ganzheitlichen Service-Integrationsplattform, welche es nicht ausschließlich, aber insbesondere Domänenexperten ermöglichen soll, Funktionalitäten verteilt und effizient anbieten und nutzen zu können, was anhand komplexer und divergenter Fallstudien aus verschiedenen Fachrichtungen belegt wird. Zum Testen und evaluieren komplexer Technologien soll dabei zusätzlich eine integrierte Testumgebung dienen. Aktuelle Technologien des Semantic Web vervollständigen letztendlich das Einsatzgebiet in puncto automatischer Modellierung und Verifikation sowie dynamischer Suche von adäquat dedizierten Diensten

An evaluation methodology and framework for semantic web services technology

Software engineering has been driven over decades by the trend towards component based development and loose coupling. Service oriented architectures and Web Services in particular are the latest product of this long-reaching development. Semantic Web Services (SWS) apply the paradigms of the Semantic Web to Web Services to allow more flexible and dynamic service usages. Numerous frameworks to realize SWS have been put forward in recent years but their relative advantages and general maturity are not easy to assess. This dissertation presents a solution to this issue. It defines a general methodology and framework for SWS technology evaluation as well as concrete benchmarks to assess the functional scope and performance of various approaches. The presented benchmarks have been executed within international evaluation campaign. The thesis thus comprehensively covers theoretical, methodological as well as practical results regarding the evaluation and assessment of SWS technologies

Methods for Efficient and Accurate Discovery of Services

With an increasing number of services developed and offered in an enterprise setting or the Web, users can hardly verify their requirements manually in order to find appropriate services. In this thesis, we develop a method to discover semantically described services. We exploit comprehensive service and request descriptions such that a wide variety of use cases can be supported. In our discovery method, we compute the matchmaking decision by employing an efficient model checking technique

Neural and Symbolic AI - mind the gap! Aligning Artificial Neural Networks and Ontologies

Artificial neural networks have been the key to solve a variety of different problems. However, neural network models are still essentially regarded as black boxes, since they do not provide any human-interpretable evidence as to why they output a certain re sult. In this dissertation, we address this issue by leveraging on ontologies and building small classifiers that map a neural network’s internal representations to concepts from an ontology, enabling the generation of symbolic justifications for the output of neural networks. Using two image classification problems as testing ground, we discuss how to map the internal representations of a neural network to the concepts of an ontology, exam ine whether the results obtained by the established mappings match our understanding of the mapped concepts, and analyze the justifications obtained through this method

Efficient Maximum A-Posteriori Inference in Markov Logic and Application in Description Logics

Maximum a-posteriori (MAP) query in statistical relational models computes the most probable world given evidence and further knowledge about the domain. It is arguably one of the most important types of computational problems, since it is also used as a subroutine in weight learning algorithms. In this thesis, we discuss an improved inference algorithm and an application for MAP queries. We focus on Markov logic (ML) as statistical relational formalism. Markov logic combines Markov networks with first-order logic by attaching weights to first-order formulas. For inference, we improve existing work which translates MAP queries to integer linear programs (ILP). The motivation is that existing ILP solvers are very stable and fast and are able to precisely estimate the quality of an intermediate solution. In our work, we focus on improving the translation process such that we result in ILPs having fewer variables and fewer constraints. Our main contribution is the Cutting Plane Aggregation (CPA) approach which leverages symmetries in ML networks and parallelizes MAP inference. Additionally, we integrate the cutting plane inference (Riedel 2008) algorithm which significantly reduces the number of groundings by solving multiple smaller ILPs instead of one large ILP. We present the new Markov logic engine RockIt which outperforms state-of-the-art engines in standard Markov logic benchmarks. Afterwards, we apply the MAP query to description logics. Description logics (DL) are knowledge representation formalisms whose expressivity is higher than propositional logic but lower than first-order logic. The most popular DLs have been standardized in the ontology language OWL and are an elementary component in the Semantic Web. We combine Markov logic, which essentially follows the semantic of a log-linear model, with description logics to log-linear description logics. In log-linear description logic weights can be attached to any description logic axiom. Furthermore, we introduce a new query type which computes the most-probable 'coherent' world. Possible applications of log-linear description logics are mainly located in the area of ontology learning and data integration. With our novel log-linear description logic reasoner ELog, we experimentally show that more expressivity increases quality and that the solutions of optimal solving strategies have higher quality than the solutions of approximate solving strategies

Forschungsbericht Universität Mannheim 2008 / 2009

Die Universität Mannheim hat seit ihrer Entstehung ein spezifisches Forschungsprofil, welches sich in ihrer Entwicklung und derz eitigen Struktur deutlich widerspiegelt. Es ist geprägt von national und international sehr anerkannten Wirtschafts- und Sozialwissenschaften und deren Vernetzung mit leistungsstarken Geisteswissenschaften, Rechtswissenschaft sowie Mathematik und Informatik. Die Universität Mannheim wird auch in Zukunft einerseits die Forschungsschwerpunkte in den Wirtschafts- und Sozialwissenschaften fördern und andererseits eine interdisziplinäre Kultur im Zusammenspiel aller Fächer der Universität anstreben