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Institut
In recent years ontologies have become common on the WWW to provide high-level descriptions of specific domains. These descriptions could be effectively used to build applications with the ability to find implicit consequences of their represented knowledge. The W3C developed the Resource Description Framework RDF, a language to describe the semantics of the data on the web, and the Ontology Web Language OWL, a family of knowledge representation languages for authoring ontologies. In this thesis we propose an ontology API engineering framework that makes use of the state-of-the-art ontology modeling technologies as well as of software engineering technologies. This system simplifies the design and implementation process of developing dedicated APIs for ontologies. Developers of semantic web applications usually face the problem of mapping entities or complex relations described in the ontology to object-oriented representations. Mapping complex relationship structures that come with complex ontologies to a useful API requires more complicated API representations than does the mere mapping of concepts to classes. The implementation of correct object persistence functions in such class representations also becomes quite complex.
Existing tools for generating application programming interfaces (APIs) for ontologies lack sophisticated support for mapping the logics-based concepts of the ontology to an appropriate object-oriented implementation of the API. Such a mapping has to overcome the fundamental differences between the semantics described in the ontology and the pragmatics, i.e., structure, functionalities, and behavior implemented in the API. Typically, concepts from the ontology are mapped one-to-one to classes in the targeted programming language. Such a mapping only produces concept representations but not an API at the desired level of granularity expected by an application developer. We present a Model-Driven Engineering (MDE) process to generate customized APIs for ontologies. This API generation is based on the semantics defined in the ontology but also leverages additional information the ontology provides. This can be the inheritance structure of the ontology concepts, the scope of relevance of an ontology concept, or design patterns defined in the ontology.
We propose a new approach for mobile visualization and interaction of temporal information by integrating support for time with today's most prevalent visualization of spatial information, the map. Our approach allows for an easy and precise selection of the time that is of interest and provides immediate feedback to the users when interacting with it. It has been developed in an evolutionary process gaining formative feedback from end users.
Knowledge compilation is a common technique for propositional logic knowledge bases. A given knowledge base is transformed into a normal form, for which queries can be answered efficiently. This precompilation step is expensive, but it only has to be performed once. We apply this technique to concepts defined in the Description Logic ALC. We introduce a normal form called linkless normal form for ALC concepts and discuss an efficient satisability test for concepts given in this normal form. Furthermore, we will show how to efficiently calculate uniform interpolants of precompiled concepts w.r.t. a given signature.
Mobile payment has been a payment option in the market for a long time now and was predicted to become a widely used payment method. However, over the years, the market penetration rate of mPayments has been relatively low, despite it having all characteristics required of a convenient payment method. The primaryrnreason for this has been cited as a lack of customer acceptance mainly caused due to the lack of perceived security by the end-user. Although biometric authentication is not a new technology, it is experiencing a revival in the light of the present day terror threats and increased security requirements in various industries. The application of biometric authentication in mPayments is analysed here and a suitable biometric authentication method for use with mPayments is recommended. The issue of enrolment, human and technical factors to be considered are discussed and the STOF business model is applied to a BiMoP (biometric mPayment) application.
Die vorliegende Arbeit stellt eine Methode für die korpusbasierte Analyse der Verwendung von Softwarebibliotheken in Java-Programmen vor. Die meisten größeren Softwareprojekte verwenden Softwarebibliotheken, die als Schnittstelle für den Programmierer sogenannte APIs (application programming interfaces) bereitstellen. Um den Umstieg von einer solchen API auf eine andere zu unterstützen, strebt man Werkzeuge zur automatisierten API-Migration an. Zur Entwicklung solcher Werkzeuge fehlen allerdings noch Basisdaten. Statistiken und Beobachtungen zur Verwendung von APIs in der Praxis wurden bisher nur mit sehr kleinen Korpora von Projekten und APIs durchgeführt. Wir stellen in dieser Arbeit daher eine Analysemethode vor, die für Messungen an großen Korpora geeignet ist. Hierzu erzeugen wir zunächst einen Korpus von auf SourceForge gehosteten Open-Source-Projekten sowie einen Korpus von Softwarebibliotheken. In der Folge werden alle Projekte des Korpus compiliert, wobei ein Compiler-Plugin für den javac detaillierte Informationen über jede einzelne Methode liefert, die der Compiler erstellt. Diese Informationen werden in einer Datenbank gespeichert und analysiert.
This dissertation provides an interdisciplinary contribution to the project ReGLaN-Health & Logistics. ReGLaN-Health & Logistics, is an international cooperation deriving benefits from the capabilities of scientists working on different fields. The aim of the project is the development of a socalled SDSS that supports decision makers working within health systems with a special focus on rural areas. In this dissertation, one important component for the development of the DSS named EWARS is proposed and described in detail. This component called SPATTB is developed with the intention of dealing with spatial data, i.e. data with additional geocoded information with regard to the special requirements of the EWARS.rnrnAn important component in the process of developing the EWARS is the concept of GIS. Classically, geocoded information with a vectorial character numerically describing spatial phenomena is managed and processed in a GIS. For the development of the EWARS, the manageability of the type of data exemplarily given by (x,y,o) with coordinates x,y ) and Ozon-concentration o is not sufficient. It is described, that the manageable data has to be extended to data of type (x,y,f ), where (x,y) are the geocoded information, but where f is not only a numerical value but a functional description of a certain phenomenom. An example for the existence and appearance of that type of data is the geocoded information about the variation of the Ozon-concentration in time or depending on temperature. A knowledge-base as important subsystem of DSS containing expert knowledge is mentioned. This expert-knowledge can be made manageable when using methods from the field of fuzzy logic. Thereby mappings, socalled fuzzy-sets, are generated. Within the EWARS, these mappings will be used with respect to additional geocoded data. The knowledge about the geocoded mapping information only at a finite set of locations (x,y) associated with mapping information f is not sufficient in applications that need continuous statements in a certain geographical area. To provide a contribution towards solving this problem, methods from the field of computer geometry and CAD, so-called Bezier-methods, are used for interpolating this geocoded mapping information. Classically, these methods operates on vectors a the multidimensional vector-space whose elements contain real-valued components but in terms of dealing with mapping information, there has to be an extension on topological vector spaces since mapping spaces can be defined as such spaces. This builds a new perspective and possibility in the application of these methods. Therefore, the according algorithms have to be extended; this work is presented. The field of Artificial Neural Networks plays an important role for the processing and management of the data within the EWARS, where features of biological processes and structures are modeled and implemented as algorithms. Generally, the developed methods can be divided as usable in terms of interpolation or approximation functional coherences and in such being applicable to classification problems. In this dissertation one method from each type is regarded in more detailed. Thereby, the classical algorithms of the so-called Backpropagation-Networks for approximation and the Kohonen-Networks for classification are described. Within the thesis, an extension of these algorithms is then proposed using coherences from mathematical measure-theory and approximation theory. The mentioned extension of these algorithms is based on a preprocessing of the mapping data using integration methods from measure theory.