A rise in the number of ontologies that are integrated and distributed in numerous application systems may provide the users to access the ontologies with different privileges and purposes. In this situation, preserving confidential information from possible unauthorized disclosures becomes a critical requirement. For instance, in the clinical sciences, unauthorized disclosures of medical information do not only threaten the system but also, most importantly, the patient data. Motivated by this situation, this thesis initially investigates a privacy problem, called the identity problem, where the identity of (anonymous) objects stored in Description Logic ontologies can be revealed or not. Then, we consider this problem in the context of role-based access control to ontologies and extend it to the problem asking if the identity belongs to a set of known individuals of cardinality smaller than the number k. If it is the case that some confidential information of persons, such as their identity, their relationships or their other properties, can be deduced from an ontology, which implies that some privacy policy is not fulfilled, then one needs to repair this ontology such that the modified one complies with the policies and preserves the information from the original ontology as much as possible. The repair mechanism we provide is called gentle repair and performed via axiom weakening instead of axiom deletion which was commonly used in classical approaches of ontology repair. However, policy compliance itself is not enough if there is a possible attacker that can obtain relevant information from other sources, which together with the modified ontology still violates the privacy policies. Safety property is proposed to alleviate this issue and we investigate this in the context of privacy-preserving ontology publishing. Inference procedures to solve those privacy problems and additional investigations on the complexity of the procedures, as well as the worst-case complexity of the problems, become the main contributions of this thesis.:1. Introduction 1.1 Description Logics 1.2 Detecting Privacy Breaches in Information System 1.3 Repairing Information Systems 1.4 Privacy-Preserving Data Publishing 1.5 Outline and Contribution of the Thesis 2. Preliminaries 2.1 Description Logic ALC 2.1.1 Reasoning in ALC Ontologies 2.1.2 Relationship with First-Order Logic 2.1.3. Fragments of ALC 2.2 Description Logic EL 2.3 The Complexity of Reasoning Problems in DLs 3. The Identity Problem and Its Variants in Description Logic Ontologies 3.1 The Identity Problem 3.1.1 Description Logics with Equality Power 3.1.2 The Complexity of the Identity Problem 3.2 The View-Based Identity Problem 3.3 The k-Hiding Problem 3.3.1 Upper Bounds 3.3.2 Lower Bound 4. Repairing Description Logic Ontologies 4.1 Repairing Ontologies 4.2 Gentle Repairs 4.3 Weakening Relations 4.4 Weakening Relations for EL Axioms 4.4.1 Generalizing the Right-Hand Sides of GCIs 4.4.2 Syntactic Generalizations 4.5 Weakening Relations for ALC Axioms 4.5.1 Generalizations and Specializations in ALC w.r.t. Role Depth 4.5.2 Syntactical Generalizations and Specializations in ALC 5. Privacy-Preserving Ontology Publishing for EL Instance Stores 5.1 Formalizing Sensitive Information in EL Instance Stores 5.2 Computing Optimal Compliant Generalizations 5.3 Computing Optimal Safe^{\exists} Generalizations 5.4 Deciding Optimality^{\exists} in EL Instance Stores 5.5 Characterizing Safety^{\forall} 5.6 Optimal P-safe^{\forall} Generalizations 5.7 Characterizing Safety^{\forall\exists} and Optimality^{\forall\exists} 6. Privacy-Preserving Ontology Publishing for EL ABoxes 6.1 Logical Entailments in EL ABoxes with Anonymous Individuals 6.2 Anonymizing EL ABoxes 6.3 Formalizing Sensitive Information in EL ABoxes 6.4 Compliance and Safety for EL ABoxes 6.5 Optimal Anonymizers 7. Conclusion 7.1 Main Results 7.2 Future Work Bibliography

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Inevitably, it becomes more and more important to verify that the systems surrounding us have certain properties. This is indeed unavoidable for safety-critical systems such as power plants and intensive-care units. We refer to the term system in a broad sense: it may be man-made (e.g. a computer system) or natural (e.g. a patient in an intensive-care unit). Whereas in Model Checking it is assumed that one has complete knowledge about the functioning of the system, we consider an open-world scenario and assume that we can only observe the behaviour of the actual running system by sensors. Such an abstract sensor could sense e.g. the blood pressure of a patient or the air traffic observed by radar. Then the observed data are preprocessed appropriately and stored in a fact base. Based on the data available in the fact base, situation-awareness tools are supposed to help the user to detect certain situations that require intervention by an expert. Such situations could be that the heart-rate of a patient is rather high while the blood pressure is low, or that a collision of two aeroplanes is about to happen. Moreover, the information in the fact base can be used by monitors to verify that the system has certain properties. It is not realistic, however, to assume that the sensors always yield a complete description of the current state of the observed system. Thus, it makes sense to assume that information that is not present in the fact base is unknown rather than false. Moreover, very often one has some knowledge about the functioning of the system. This background knowledge can be used to draw conclusions about the possible future behaviour of the system. Employing description logics (DLs) is one way to deal with these requirements. In this thesis, we tackle the sketched problem in three different contexts: (i) runtime verification using a temporalised DL, (ii) temporalised query entailment, and (iii) verification in DL-based action formalisms.

Description Logics (DLs) are a family of logic-based knowledge representation languages used to describe the knowledge of an application domain and reason about it in formally well-defined way. They allow users to describe the important notions and classes of the knowledge domain as concepts, which formalize the necessary and sufficient conditions for individual objects to belong to that concept. A variety of different DLs exist, differing in the set of properties one can use to express concepts, the so-called concept constructors, as well as the set of axioms available to describe the relations between concepts or individuals. However, all classical DLs have in common that they can only express exact knowledge, and correspondingly only allow exact inferences. Either we can infer that some individual belongs to a concept, or we can't, there is no in-between. In practice though, knowledge is rarely exact. Many definitions have their exceptions or are vaguely formulated in the first place, and people might not only be interested in exact answers, but also in alternatives that are "close enough". This thesis is aimed at tackling how to express that something "close enough", and how to integrate this notion into the formalism of Description Logics. To this end, we will use the notion of similarity and dissimilarity measures as a way to quantify how close exactly two concepts are. We will look at how useful measures can be defined in the context of DLs, and how they can be incorporated into the formal framework in order to generalize it. In particular, we will look closer at two applications of thus measures to DLs: Relaxed instance queries will incorporate a similarity measure in order to not just give the exact answer to some query, but all answers that are reasonably similar. Prototypical definitions on the other hand use a measure of dissimilarity or distance between concepts in order to allow the definitions of and reasoning with concepts that capture not just those individuals that satisfy exactly the stated properties, but also those that are "close enough".

This essay examines the incentives and notions behind the practice of genealogy, in terms of how discourses and notions of kinship, identity and history is expressed against the setting of genealogy as a cultural and social phenomenon that is gaining a growing interest amongst the general public. Through qualitative interviews with six amateur genealogists, the study explores how notions of kinship and history shape the way in which genealogists come to understand themselves and their place in the world. Furthermore, the study explores how genealogists make use of the specific knowledge that they have acquired through their engagement with genealogy. Through analysis of discourse and the logics approach, the essay shows that lack of specific knowledge about one’s ancestry is seen as an inherent reason for seeking knowledge through genealogy. The essay indicates that the notion of understanding oneself can be seen as a significant incentive and driving force in the practice of genealogy, where kinship is made meaningful through identity formation. The essay also shows that genealogy is made meaningful through notions and desires of belonging and affinity, and that genealogy can be seen as a way for genealogists to either create or maintain links between generations, to places, or with the past in general. Furthermore, the essay shows examples of how genealogy can be seen as a way to explore alternative aspects of history, and that the knowledge that is acquired through genealogy can be employed to challenge understandings of “real” and “authentic” history. Lastly, the essay shows that genealogy offers a backdrop of historic knowledge that can be used by genealogists to contrast notions of the past with notions of the present, in order to express criticism towards society, convey moral messages, and to make sense of the present time.

We propose in the paper a new solution to the so-called Logical Omniscience Problem of epistemic logic. Almost all attempts in the literature to solve this problem consist in weakening the standard epistemic systems: weaker systems are considered where the agents do not possess the full reasoning capacities of ideal reasoners. We shall argue that this solution is not satisfactory: in this way omniscience can be avoided, but many intuitions about the concepts of knowledge and belief get lost. We shall show that axioms for epistemic logics must have the following form: if the agent knows all premises of a valid inference rule, and if she thinks hard enough, then she will know the conclusion. To formalize such an idea, we propose to \dynamize' epistemic logic, that is, to introduce a dynamic component into the language. We develop a logic based on this idea and show that it is suitable for formalizing the notion of actual, or explicit knowledge.

Description Logics (DLs) form a family of knowledge representation formalisms which can be used to represent and reason with conceptual knowledge about a domain of interest. The knowledge represented by DLs is mainly static. In many applications, the domain knowledge is dynamic. This observation motivates the research on how to update the knowledge when changes in the application domain take place. This thesis is dedicated to the study of updating knowledge, more precisely, assertional knowledge represented in DLs. We explore whether the updated knowledge can be expressed in several standard DLs and, if so, whether it is computable and what is its size.

Constructing description logic ontologies is a difficult task that is normally conducted by experts. Recent results show that parts of ontologies can be constructed from description logic interpretations. However, these results assume the interpretations to be free of errors, which may not be the case for real-world data. To provide some mechanism to handle these errors, the notion of confidence from data mining is introduced into description logics, yielding confident general concept inclusions (confident GCIs) of finite interpretations. The main focus of this work is to prove the existence of finite bases of confident GCIs and to describe some of theses bases explicitly.

Given the large variety of existing logical formalisms it is of utmost importance to select the most adequate one for a specific purpose, e.g. for representing the knowledge relevant for a particular application or for using the formalism as a modeling tool for problem solving. Awareness of the nature of a logical formalism, in other words, of its fundamental intrinsic properties, is indispensable and provides the basis of an informed choice. One such intrinsic property of logic-based knowledge representation languages is the context-dependency of pieces of knowledge. In classical propositional logic, for example, there is no such context-dependence: whenever two sets of formulas are equivalent in the sense of having the same models (ordinary equivalence), then they are mutually replaceable in arbitrary contexts (strong equivalence). However, a large number of commonly used formalisms are not like classical logic which leads to a series of interesting developments. It turned out that sometimes, to characterize strong equivalence in formalism L, we can use ordinary equivalence in formalism L0: for example, strong equivalence in normal logic programs under stable models can be characterized by the standard semantics of the logic of here-and-there. Such results about the existence of characterizing logics has rightly been recognized as important for the study of concrete knowledge representation formalisms and raise a fundamental question: Does every formalism have one? In this thesis, we answer this question with a qualified “yes”. More precisely, we show that the important case of considering only finite knowledge bases guarantees the existence of a canonical characterizing formalism. Furthermore, we argue that those characterizing formalisms can be seen as classical, monotonic logics which are uniquely determined (up to isomorphism) regarding their model theory. The other main part of this thesis is devoted to argumentation semantics which play the flagship role in Dung’s abstract argumentation theory. Almost all of them are motivated by an easily understandable intuition of what should be acceptable in the light of conflicts. However, although these intuitions equip us with short and comprehensible formal definitions it turned out that their intrinsic properties such as existence and uniqueness, expressibility, replaceability and verifiability are not that easily accessible. We review the mentioned properties for almost all semantics available in the literature. In doing so we include two main axes: namely first, the distinction between extension-based and labelling-based versions and secondly, the distinction of different kind of argumentation frameworks such as finite or unrestricted ones.

Innovations such as combustion engines, electricity and assembly lines have all had a significant role in manufacturing, where the past three industrial revolutions have changed the way manufacturing is performed. The technical progress within the manufacturing industry continues at a high rate and today's progress can be seen as a part of the fourth industrial revolution. The progress can be exemplified by ”Industrie 4.0”; the German government's vision of future manufacturing. Previous studies have been conducted with the aim of investigating the benefits, progress and relevance of Industry 4.0-technologies. Little emphasis in these studies has been put on differences in implementation and relevance of Industry 4.0-technologies across and within industries. This thesis aims to investigate the adoption of Industry 4.0-technologies among and within selected industries and what types of patterns that exists among them. Using a qualitative multiple case study consisting of firms from Aerospace, Heavy equipment, Automation, Electronics and Motor Vehicle Industry, we gain insight into how leading firms are implementing the technologies. In order to identify the factors determining how Industry 4.0-technologies are implemented and what common themes can be found, we introduce the concept production logic, which is built upon the connection between competitive priorities; quality, flexibility, delivery time, cost efficiency and ergonomics. This thesis has two contributions. In our first contribution, we have categorized technologies within Industry 4.0 into two bundles; the Human-Machine-Interface (HMI) and the connectivity bundle. The HMI bundle includes devices for assisting operators in manufacturing activities, such as touchscreens, augmented reality and collaborative robots. The connectivity-bundle includes systems for connecting devices, collecting and analyzing data from the digitalized factory. The result of this master thesis indicates that depending on a firm’s or industry’s logic of production, the adoption of elements from the technology bundles differ. Firms where flexibility is dominant tend to implement elements from the HMI-bundle to a larger degree. In the other end, firms with few product variations where quality and efficiency dominates the production logic tends to implement elements from the connectivity bundle in order to tightly monitor and improve quality in their assembly. Regardless of production logic, firms are implementing elements from both bundles, but with different composition and applications. The second contribution is within the literature of technological transitions. In this contribution, we have studied the rise and development of the HMI-bundle in the light of Geels (2002) Multi-Level Perspective (MLP). It can be concluded that an increased pressure on the landscape-level in the form of changes in the consumer-market and the attitudes within the labor force has created a gradual spread of the HMI-bundle within industries. The bundles have also been studied through Rogers (1995) five attributes of innovation, where the lack of testability and observability prevents increased application of M2M-interfaces. Concerning Big Data and analytics, the high complexity prevents the technology from being further applied. As the HMI-bundle involves a number of technologies with large differences in properties, it is hard draw any conclusion using the attributes of innovation about what limits their application.