An extended ontology-based context model and manipulation calculus for dynamic web service processes

Services are oered in an execution context that is determined by how a provider provisions the service and how the user consumes it. The need for more exibility requires the provisioning and consumption aspects to be addressed at runtime. We propose an ontology-based context model providing a framework for service provisioning and consumption aspects and techniques for managing context constraints for Web service processes where dynamic context concerns can be monitored and validated at service process run-time. We discuss the contextualization of dynamically relevant aspects of Web service processes as our main goal, i.e. capture aspects in an extended context model. The technical contributions of this paper are a context model ontology for dynamic service contexts and an operator calculus for integrated and coherent context manipulation, composition and reasoning. The context model ontology formalizes dynamic aspects of Web services and facilitates reasoning. We present the context ontology in terms of four core dimensions - functional, QoS, domain and platform - which are internally interconnected

Towards the ontology-based consolidation of production-centric standards

Production-­centric international standards are intended to serve as an important route towards information sharing across manufacturing decision support systems. As a consequence of textual-­based definitions of concepts acknowledged within these standards, their inability to fully interoperate becomes an issue especially since a multitude of standards are required to cover the needs of extensive domains such as manufacturing industries. To help reinforce the current understanding to support the consolidation of production-­centric standards for improved information sharing, this article explores the specification of well-defined core concepts which can be used as a basis for capturing tailored semantic definitions. The potentials of two heavyweight ontological approaches, notably Common Logic (CL) and the Web Ontology Language (OWL) as candidates for the task, are also exposed. An important finding regarding these two methods is that while an OWL-­based approach shows capabilities towards applications which may require flexible hierarchies of concepts, a CL-­based method represents a favoured contender for scoped and facts-­driven manufacturing applications

A methodology for provably stable behaviour-based intelligent control

This paper presents a design methodology for a class of behaviour-based control systems, arguing its potential for application to safety critical systems. We propose a formal basis for subsumption architecture design based on two extensions to Lyapunov stability theory, the Second Order Stability Theorems, and interpretations of system safety and liveness in Lyapunov stability terms. The subsumption of the new theorems by the classical stability theorems serves as a model of dynamical subsumption, forming the basis of the design methodology. Behaviour-based control also offers the potential for using simple computational mechanisms, which will simplify the safety assurance process. © 2005 Elsevier B.V. All rights reserved

Description Logic for Scene Understanding at the Example of Urban Road Intersections

Understanding a natural scene on the basis of external sensors is a task yet to be solved by computer algorithms. The present thesis investigates the suitability of a particular family of explicit, formal representation and reasoning formalisms for this task, which are subsumed under the term Description Logic

Data protection regulation ontology for compliance

The GDPR is the current data protection regulation in Europe. A significant market demand has been created ever since GDPR came into force. This is mostly due to the fact that it can go outside of European borders if the data processed belongs to European citizens. The number of companies who require some type of regulation or standard compliance is ever-increasing and the need for cyber security and privacy specialists has never been greater. Moreover, the GDPR has inspired a series of similar regulations all over the world. This further increases the market demand and makes the work of companies who work internationally more complicated and difficult to scale. The purpose of this thesis is to help consultancy companies to automate their work by using semantic structures known as ontologies. By doing this, they can increase productivity and reduce costs. Ontologies can store data and their semantics (meaning) in a machine-readable format. In this thesis, an ontology has been designed which is meant to help consultants generate checklists (or runbooks) which they are required to deliver to their clients. The ontology is designed to handle concepts such as security measures, company information, company architecture, data sensitivity, privacy mechanisms, distinction between technical and organisational measures, and even conditionality. The ontology was evaluated using a litmus test. In the context of this ontology, the litmus test was composed of a collection of competency questions. Competency questions were collected based on the use-cases of the ontology. These questions were later translated to SPARQL queries which were run against a test ontology. The ontology has successfully passed the given litmus test. Thus, it can be concluded that the implemented functionality matches the proposed design

The configuration of design and manufacture knowledge models from a heavyweight ontological foundation

Problems related to knowledge sharing in design and manufacture, for supporting automated decision-making procedures, are associated with the inability to communicate the full meaning of concepts and their intent within and across system boundaries. To remedy these issues, it is important that the explicit structuring of semantics, i.e., meaning in computation form, is first performed and that these semantics become sharable across systems. This paper proposes an expressive (heavyweight) Common Logic-based ontological foundation as a basis for capturing the meaning of generic feature-oriented design and manufacture concepts. This ontological foundation serves as a semantic ground over which design and manufacture knowledge models can be configured in an integrity-driven way. The implications involved in the specification of the ontological foundation are discussed alongside the types of mechanisms that allow knowledge models to be configured. A test case scenario is then analysed in order to further support and verify the researched approach