Description Logics (DLs) belong to a successful family of knowledge representation formalisms with two key assets: formally well-defined semantics which allows to represent knowledge in an unambiguous way and automated reasoning which allows to infer implicit knowledge from the one given explicitly. This thesis investigates various reasoning techniques for tractable DLs in the EL family which have been implemented in the CEL system. It suggests that the use of the lightweight DLs, in which reasoning is tractable, is beneficial for ontology design and maintenance both in terms of expressivity and scalability. The claim is supported by a case study on the renown medical ontology SNOMED CT and extensive empirical evaluation on several large-scale biomedical ontologies.

We adapt existing approaches for privacy-preserving publishing of linked data to a setting where the data are given as Description Logic (DL) ABoxes with possibly anonymised (formally: existentially quantified) individuals and the privacy policies are expressed using sets of concepts of the DL EL. We provide a chacterization of compliance of such ABoxes w.r.t. EL policies, and show how optimal compliant anonymisations of ABoxes that are non-compliant can be computed. This work extends previous work on privacy-preserving ontology publishing, in which a very restricted form of ABoxes, called instance stores, had been considered, but restricts the attention to compliance. The approach developed here can easily be adapted to the problem of computing optimal repairs of quantified ABoxes.

Reasoners can be used to derive implicit consequences from an ontology. Sometimes unwanted consequences are revealed, indicating errors or privacy-sensitive information, and the ontology needs to be appropriately repaired. The classical approach is to remove just enough axioms such that the unwanted consequences vanish. However, this is often too rough since mere axiom deletion also erases many other consequences that might actually be desired. The goal should not be to remove a minimal number of axioms but to modify the ontology such that only a minimal number of consequences is removed, including the unwanted ones. Specifically, a repair should rather be logically entailed by the input ontology, instead of being a subset. To this end, we introduce a framework for computing fixed-premise repairs of $\mathcal{EL}$ TBoxes. In the first variant the conclusions must be generalizations of those in the input TBox, while in the second variant no such restriction is imposed. In both variants, every repair is entailed by an optimal one and, up to equivalence, the set of all optimal repairs can be computed in exponential time. A prototypical implementation is provided. In addition, we show new complexity results regarding gentle repairs. / This is an extended version of an article accepted at the 45th German Conference on Artificial Intelligence (KI 2022).

[pt] A lógica descritiva intuicionista iALC foi criada para modelar e raciocinar sobre o domínio de Leis baseada na Jurisprudência Kelseniana [1]. No decorrer da década anterior, essa lógica foi usada de diversas maneiras para modelar normas ou formalizar raciocínio jurídico [2, 3, 4, 5, 6, 7, 8, 9, 10]. Neste trabalho pretendemos complementar trabalhos anteriores ralizados com essa lógica ao preencher algumas lacunas encontradas enquanto trabalhando com ela. A primeira lacuna ocorre por iALC não ter um modo intuitivo de explicar raciocínio nela realizado para pessoas fora do domínio da Lógica. Ela tem um Cálculo de Sequentes (CS) [6] correto e completo (com respeito a modelos conceituais intuitionistas [3]) que tem sido menos usado que o desejado, e isso se dá em grande parte devido à maneira pouco intuitiva com que CS representa provas. Apresentamos um sistema de Dedução Natural (DN) correto e completo e com (quasi-)normalização para compensar por essa dificuldade em explicar CS para não-lógicos, especialmente os do domínio legal, essenciais para nossa pesquisa. Normalização completa não é possível devido a um tipo de derivação - tirando essa exceção, o resto do sistema gera derivações uniformes. A segunda lacuna envolve não poder lidar com raciocínio não-monotônico (RNM). Em geral, utiliza-se raciocínio monotônico, no qual, se é possível concluir algo de um conjunto de premissas, não há como acrescentar outra premissa de modo a evitar a conclusão prévia. Isso não é o caso em um julgamento legal, por exemplo, no qual lados opostos buscam convencer um juiz ou júri de consequências opostas ao adicionar premissas diferentes ao caso em questão. Propomos uma investigação de caráter exploratório em busca de uma extensão de iALC para lidar com RNM a fim de representar raciocínio jurídico em outras facetas da Lei como o processo judicial, que é não-monotônico por natureza. Apresentamos propriedades desejadas e uma possível aplicação de um sistema assim via um estudo de caso. Detalhamos mais a motivação tanto para o sistema de DN quanto a extensão de RNM, assim como as decisões tomadas ao criar cada um. / [en] The intuitionistic description logic iALC was created to model and reason over the domain of Law based on Kelsenian Jurisprudence [1]. Over the past decade, this logic has been used in several ways to either model norms or formalise legal reasoning [2, 3, 4, 5, 6, 7, 8, 9, 10]. In this work we intend to complement previous research done with this logic by filling some gaps found while working with it. The first gap occurs in iALC needing an intuitive way to explain reasoning for non-logicians. It has a sound and complete (concerning intuitionistic conceptual models [3]) Sequent Calculus (SC) [6] that has seen less usage than expected due to its non-intuitive way of presenting a proof. We present a (quasi-)normalising, sound and complete (w.r.t. TBox validity for intuitionistic conceptual models) Natural Deduction (ND) System to cover this difficulty in explaining SC to non-logicians, especially those in the domain of Law, which are essential to us. We do not achieve full normalisation due to a kind of derivation which cannot be normalised - aside from this exception, the rest of the system can provide uniform derivations. The second gap is being unable to deal with non-monotonic reasoning (NMR). Usually, one considers monotonic reasoning, in which, if one can conclude something from a set of premises, there is no way to add another premise to avoid said conclusion. This is not the case in a court of law, for instance, in which different parties aim to convince a judge or jury of opposite consequences by adding different premises to the case itself. We provide an exploratory investigation of an extension of iALC to deal with NMR to represent legal reasoning in aspects of the Law, such as the judicial process, which is non-monotonic by nature. We present desirable properties and a possible application of such a system via a case study. We explain further the motivation for both the ND system and the NMR extension and the decisions taken for both.

Simple counting quantifiers that can be used to compare the number of role successors of an individual or the cardinality of a concept with a fixed natural number have been employed in Description Logics (DLs) for more than two decades under the respective names of number restrictions and cardinality restrictions on concepts. Recently, we have considerably extended the expressivity of such quantifiers by allowing to impose set and cardinality constraints formulated in the quantifier-free fragment of Boolean Algebra with Presburger Arithmetic (QFBAPA) on sets of role successors and concepts, respectively. We were able to prove that this extension does not increase the complexity of reasoning. In the present paper, we investigate the expressive power of the DLs obtained in this way, using appropriate bisimulation characterizations and 0–1 laws as tools to differentiate between the expressiveness of different logics. In particular, we show that, in contrast to most classical DLs, these logics are no longer expressible in first-order predicate logic (FOL), and we characterize their first-order fragments. In most of our previous work on DLs with QFBAPA-based set and cardinality constraints we have employed finiteness restrictions on interpretations to ensure that the obtained sets are finite, as required by the standard semantics for QFBAPA. Here we dispense with these restrictions to ease the comparison with classical DLs, where one usually considers arbitrary models rather than finite ones, easier. It turns out that doing so does not change the complexity of reasoning.

We introduce a new description logic that extends the well-known logic ALCQ by allowing the statement of constraints on role successors that are more general than the qualified number restrictions of ALCQ. To formulate these constraints, we use the quantifier-free fragment of Boolean Algebra with Presburger Arithmetic (QFBAPA), in which one can express Boolean combinations of set constraints and numerical constraints on the cardinalities of sets. Though our new logic is considerably more expressive than ALCQ, we are able to show that the complexity of reasoning in it is the same as in ALCQ, both without and with TBoxes. / The first version of this report was put online on April 6, 2017. The current version, containing more information on related work, was put online on July 13, 2017. This is an extended version of a paper published in the proceedings of FroCoS 2017.

In Ontology-Based Data Access (OBDA), user queries are evaluated over a set of facts under the open world assumption, while taking into account background knowledge given in the form of a Description Logic (DL) ontology. Motivated by situation awareness applications, temporal conjunctive queries (TCQs) have recently been proposed as a useful extension of traditional OBDA to support the processing of temporal information. This paper extends the existing complexity analysis of TCQ entailment to very expressive DLs underlying the OWL 2 standard, and in contrast to previous work also allows for queries containing transitive roles. / This is an extended version of the paper “Temporal Conjunctive Queries in Expressive Description Logics with Transitive Roles”, published in the Proceedings of the 28th Australasian Joint Conference on Artificial Intelligence (AI’15).

SweetDeal is a rule-based approach to representation of business contracts that enables software agents to create, evaluate, negotiate, and execute contracts with substantial automation and modularity. It builds upon the situated courteous logic programs knowledge representation in RuleML, the emerging standard for Semantic Web XML rules. Here, we newly extend the SweetDeal approach by also incorporating process knowledge descriptions whose ontologies are represented in DAML+OIL (the close predecessor of W3C's OWL, the emerging standard for Semantic Web ontologies), thereby enabling more complex contracts with behavioral provisions, especially for handling exception conditions (e.g., late delivery or non-payment) that might arise during the execution of the contract. This provides a foundation for representing and automating deals about services – in particular, about Web Services, so as to help search, select, and compose them. We give a detailed application scenario of late delivery in manufacturing supply chain management (SCM). In doing so, we draw upon our new formalization of process ontology knowledge from the MIT Process Handbook, a large, previously-existing repository used by practical industrial process designers. Our system is the first to combine emerging Semantic Web standards for knowledge representation of rules (RuleML) with ontologies (DAML+OIL/OWL) with each other, and moreover for a practical e-business application domain, and further to do so with process knowledge. This also newly fleshes out the evolving concept of Semantic Web Services. A prototype (soon public) i

Els datasets geogràfics representen la realitat mitjançant un conjunt d'entitats temàtiques que sovint no estan definides d'una manera precisa i que diferents persones poden entendre de diferents formes. La integració d'informació geogràfica provinent de diverses fonts presenta un important repte des del punt de vista semàntic. En aquesta tesi es proposa una solució a aquest problema basada en la definició d'un marc semàntic el nucli del qual és una ontologia que representa els conceptes temàtics en un repositori de datasets, així com les relacions entre aquests conceptes. També es proposa un mètode semi-automàtic per fusionar les ontologies d'aplicació dels datasets en el repositori. El marc semàntic permet també la definició de serveis semàntics, en concret la integració en un nou dataset d'informació temàtica provinent de diverses fonts. Finalment, el marc semàntic i els seus serveis s'utilitzaran en un sistema d'indexació i recuperació d'elements multimèdia geo-referenciats a partir del seu contingut geogràfic temàtic. / Los datasets geográficos representan la realidad mediante un conjunto de entidades temáticas que a menudo no están definidas de una manera precisa y que diferentes sujetos pueden entender de distintas formas. La integración de información geográfica proveniente de diversas fuentes presenta un importante reto desde el punto de vista semántico. En esta tesis se propone una solución a este problema basada en la definición de un marco semántico cuyo núcleo es una ontología que representa los conceptos temáticos en un repositorio de datasets, así como las relaciones entre dichos conceptos. También se propone un método semi-automático para fusionar las ontologías de aplicación de los datasets en el repositorio. El marco semántico permite además la definición de servicios semánticos, en concreto la integración en un nuevo dataset de información temática proveniente de diversas fuentes. Finalmente, el marco semántico y sus servicios se utilizarán en un sistema de indexación y recuperación de elementos multimedia geo-referenciados a partir de su contenido geográfico temático. / Geographic datasets represent reality through a set of thematic entities that are often not precisely defined and that may be understood in different ways by different subjects. Integrating geographic information from diverse datasets presents an important challenge from the semantic point of view. A solution to this problem is proposed in this thesis based on the definition of a semantic framework whose core is an ontology that represents the thematic concepts in a repository of datasets as well as their relations. A semi-automatic method is also proposed to merge the application ontologies of the datasets in the repository. The semantic framework supports the definition of semantic services, particularly the integration of the thematic information from diverse datasets in a new one. Finally, the semantic framework and its services have been used in the context of indexing and retrieving geo-referenced multimedia elements based on their thematic geographic content.

Les travaux que nous présentons dans cette thèse concernent l’automatisation de la construction de systèmes médiateurs pour le web sémantique. L’intégration de données de manière générale et la médiation en particulier sont des processus qui visent à exploiter conjointement des sources d’information indépendantes, hétérogènes et distribuées. L’objectif final est de permettre à un utilisateur d’interroger ces données comme si elles provenaient d’un système unique et centralisé grâce à une interface d’interrogation uniforme basée sur un modèle du domaine d’application, appelé schéma global. Durant ces dernières années, beaucoup de projets de recherche se sont intéressés à cette problématique et de nombreux systèmes d’intégration ont été proposés. Cependant, la quantité d’intervention humaine nécessaire pour construire ces systèmes est beaucoup trop importante pour qu’il soit envisageable de les mettre en place dans bien des situations. De plus, face à la diversité et à l’évolution croissante des sources d’information apparaissent de nouveaux chalenges relatifs notamment à la flexibilité et à la rapidité d’accès à l’information. Nos propositions s’appuient sur les modèles et technologies du web sémantique. Cette généralisation du web qui est un vaste espace d’échange de ressources, non seulement entre êtres humains, mais également entre machines, offre par essence les moyens d’une automatisation des processus d’intégration. Ils reposent d’une part sur des langages et une infrastructure dont l’objectif est d’enrichir le web d’informations "sémantiques", et d’autre part sur des usages collaboratifs qui produisent des ressources ontologiques pertinentes et réutilisables. / This thesis is set in a research effort that aims to bring more automation in building mediator-based data integration systems in the semantic Web context. The mediator approach is a conceptual architecture of data integration that involves combining data residing in different sources and providing users with a unified view of these data. The problem of designing effective data integration solutions has been addressed by several researches, and well-known data integration projects have been developed during the 90’s. However, the building process of these systems rely heavily on human intervention so that it is difficult to implement them in many situations. Moreover, faced with the diversity and the increase of available information sources, the easiness and fastness of information access are new challenges. Our proposals are based on models and technologies of semantic web. The semantic web is recognized as a generalization of the current web which enables to find, combine and share resources, not only between humans but also between machines. It provides a good track for automating the integration process. Possibilities offered by the semantic web are based, on the one hand, on languages and an infrastructure aiming to enrich the web with "semantic" information and, on the other hand, on collaborative practices that allow the production of relevant and reusable ontological resources.