Pseudo-contractions as Gentle Repairs

Updating a knowledge base to remove an unwanted consequence is a challenging task. Some of the original sentences must be either deleted or weakened in such a way that the sentence to be removed is no longer entailed by the resulting set. On the other hand, it is desirable that the existing knowledge be preserved as much as possible, minimising the loss of information. Several approaches to this problem can be found in the literature. In particular, when the knowledge is represented by an ontology, two different families of frameworks have been developed in the literature in the past decades with numerous ideas in common but with little interaction between the communities: applications of AGM-like Belief Change and justification-based Ontology Repair. In this paper, we investigate the relationship between pseudo-contraction operations and gentle repairs. Both aim to avoid the complete deletion of sentences when replacing them with weaker versions is enough to prevent the entailment of the unwanted formula. We show the correspondence between concepts on both sides and investigate under which conditions they are equivalent. Furthermore, we propose a unified notation for the two approaches, which might contribute to the integration of the two areas

Ontology evolution: a process-centric survey

Ontology evolution aims at maintaining an ontology up to date with respect to changes in the domain that it models or novel requirements of information systems that it enables. The recent industrial adoption of Semantic Web techniques, which rely on ontologies, has led to the increased importance of the ontology evolution research. Typical approaches to ontology evolution are designed as multiple-stage processes combining techniques from a variety of fields (e.g., natural language processing and reasoning). However, the few existing surveys on this topic lack an in-depth analysis of the various stages of the ontology evolution process. This survey extends the literature by adopting a process-centric view of ontology evolution. Accordingly, we first provide an overall process model synthesized from an overview of the existing models in the literature. Then we survey the major approaches to each of the steps in this process and conclude on future challenges for techniques aiming to solve that particular stage

OPTIMIZATION OF NONSTANDARD REASONING SERVICES

The increasing adoption of semantic technologies and the corresponding increasing complexity of application requirements are motivating extensions to the standard reasoning paradigms and services supported by such technologies. This thesis focuses on two of such extensions: nonmonotonic reasoning and inference-proof access control. Expressing knowledge via general rules that admit exceptions is an approach that has been commonly adopted for centuries in areas such as law and science, and more recently in object-oriented programming and computer security. The experiences in developing complex biomedical knowledge bases reported in the literature show that a direct support to defeasible properties and exceptions would be of great help. On the other hand, there is ample evidence of the need for knowledge confidentiality measures. Ontology languages and Linked Open Data are increasingly being used to encode the private knowledge of companies and public organizations. Semantic Web techniques facilitate merging different sources of knowledge and extract implicit information, thereby putting at risk security and the privacy of individuals. But the same reasoning capabilities can be exploited to protect the confidentiality of knowledge. Both nonmonotonic inference and secure knowledge base access rely on nonstandard reasoning procedures. The design and realization of these algorithms in a scalable way (appropriate to the ever-increasing size of ontologies and knowledge bases) is carried out by means of a diversified range of optimization techniques such as appropriate module extraction and incremental reasoning. Extensive experimental evaluation shows the efficiency of the developed optimization techniques: (i) for the first time performance compatible with real-time reasoning is obtained for large nonmonotonic ontologies, while (ii) the secure ontology access control proves to be already compatible with practical use in the e-health application scenario.

Data integration in the rail domain

The exchange of information is crucial to the operation of railways; starting with the distribution of timetables, information must constantly be exchanged in any railway network. The slow evolution of the information environment within the rail industry has resulted in the existence of a diverse range of systems, only able to exchange information essential to railway operations. Were the cost of data integration reduced, then further cost reductions and improvements to customer service would follow as barriers to the adoption of other technologies are removed. The need for data integration has already been studied extensively and has been included in the UK industry's rail technical strategy however, despite it's identification as a key technique for improving integration, uptake of ontology remains limited. This thesis considers techniques to reduce barriers to the take up of ontology in the UK rail industry, and presents a case study in which these techniques are applied. Amongst the key barriers to uptake identified are a lack of software engineers with ontology experience, and the diverse information environment within the rail domain. Techniques to overcomes these barriers using software based tools are considered, and example tools produced which aid the overcoming of these barriers. The case study presented is of a degraded mode signalling system, drawing data from a range of diverse sources, integrated using an ontology. Tools created to improve data integration are employed in this commercial project, successfully combing signalling data with (simulated) train positioning data

Analyse de modèles géométriques d'assemblages pour les structures et les enrichir avec des informations fonctionnelles

The digital mock-up (DMU) of a product has taken a central position in the product development process (PDP). It provides the geometric reference of the product assembly, as it defines the shape of each individual component, as well as the way components are put together. However, observations show that this geometric model is no more than a conventional representation of what the real product is. Additionally, and because of its pivotal role, the DMU is more and more required to provide information beyond mere geometry to be used in different stages of the PDP. An increasingly urging demand is functional information at different levels of the geometric representation of the assembly. This information is shown to be essential in phases such as geometric pre-processing for finite element analysis (FEA) purposes. In this work, an automated method is put forward that enriches a geometric model, which is the product DMU, with function information needed for FEA preparations. To this end, the initial geometry is restructured at different levels according to functional annotation needs. Prevailing industrial practices and representation conventions are taken into account in order to functionally interpret the pure geometric model that provides a start point to the proposed method.La maquette numérique d'un produit occupe une position centrale dans le processus de développement de produit. Elle est utilisée comme représentation de référence des produits, en définissant la forme géométrique de chaque composant, ainsi que les représentations simplifiées des liaisons entre composants. Toutefois, les observations montrent que ce modèle géométrique n'est qu'une représentation simplifiée du produit réel. De plus, et grâce à son rôle clé, la maquette numérique est de plus en plus utilisée pour structurer les informations non-géométriques qui sont ensuite utilisées dans diverses étapes du processus de développement de produits. Une demande importante est d'accéder aux informations fonctionnelles à différents niveaux de la représentation géométrique d'un assemblage. Ces informations fonctionnelles s'avèrent essentielles pour préparer des analyses éléments finis. Dans ce travail, nous proposons une méthode automatisée afin d'enrichir le modèle géométrique extrait d'une maquette numérique avec les informations fonctionnelles nécessaires pour la préparation d'un modèle de simulation par éléments finis. Les pratiques industrielles et les représentations géométriques simplifiées sont prises en compte lors de l'interprétation d'un modèle purement géométrique qui constitue le point de départ de la méthode proposée

Automatic generation of semantic Mashups in web portals

The Web has become an important source for information, which are created by independent providers. Web portals provide an unified point of access to content, data, services and web applications located throughout the enterprise. However, Web users have often only an insufficient available amount of time, to effectively use the available information resources. This thesis proposes a mashup framework that automatically mashes-up web portal content with related background information. The background information are derived from information web services that are composed by an evolutionary algorithm

Repairing ABoxes through Active Integrity Constraints

International audienceIn the literature of database repairing, active integrity constraints have provided a means of restoring integrity through a set of preferred update actions. While this is a known issue in the database community, it has not yet been directly applied to description logics. In this paper, we extend description logic TBoxes by a similar set of preferred actions and tackle the problem of ABox repairing by taking into account the new "active" TBox. For this, a mainly syntactic approach is explored and a further, dynamic logic oriented, semantic approach is suggested and briefly previewed

A framework for analyzing changes in health care lexicons and nomenclatures

Ontologies play a crucial role in current web-based biomedical applications for capturing contextual knowledge in the domain of life sciences. Many of the so-called bio-ontologies and controlled vocabularies are known to be seriously defective from both terminological and ontological perspectives, and do not sufficiently comply with the standards to be considered formai ontologies. Therefore, they are continuously evolving in order to fix the problems and provide valid knowledge. Moreover, many problems in ontology evolution often originate from incomplete knowledge about the given domain. As our knowledge improves, the related definitions in the ontologies will be altered. This problem is inadequately addressed by available tools and algorithms, mostly due to the lack of suitable knowledge representation formalisms to deal with temporal abstract notations, and the overreliance on human factors. Also most of the current approaches have been focused on changes within the internal structure of ontologies, and interactions with other existing ontologies have been widely neglected. In this research, alter revealing and classifying some of the common alterations in a number of popular biomedical ontologies, we present a novel agent-based framework, RLR (Represent, Legitimate, and Reproduce), to semi-automatically manage the evolution of bio-ontologies, with emphasis on the FungalWeb Ontology, with minimal human intervention. RLR assists and guides ontology engineers through the change management process in general, and aids in tracking and representing the changes, particularly through the use of category theory. Category theory has been used as a mathematical vehicle for modeling changes in ontologies and representing agents' interactions, independent of any specific choice of ontology language or particular implementation. We have also employed rule-based hierarchical graph transformation techniques to propose a more specific semantics for analyzing ontological changes and transformations between different versions of an ontology, as well as tracking the effects of a change in different levels of abstractions. Thus, the RLR framework enables one to manage changes in ontologies, not as standalone artifacts in isolation, but in contact with other ontologies in an openly distributed semantic web environment. The emphasis upon the generality and abstractness makes RLR more feasible in the multi-disciplinary domain of biomedical Ontology change management