Inconsistency-tolerant Query Answering in Ontology-based Data Access

Ontology-based data access (OBDA) is receiving great attention as a new paradigm for managing information systems through semantic technologies. According to this paradigm, a Description Logic ontology provides an abstract and formal representation of the domain of interest to the information system, and is used as a sophisticated schema for accessing the data and formulating queries over them. In this paper, we address the problem of dealing with inconsistencies in OBDA. Our general goal is both to study DL semantical frameworks that are inconsistency-tolerant, and to devise techniques for answering unions of conjunctive queries under such inconsistency-tolerant semantics. Our work is inspired by the approaches to consistent query answering in databases, which are based on the idea of living with inconsistencies in the database, but trying to obtain only consistent information during query answering, by relying on the notion of database repair. We first adapt the notion of database repair to our context, and show that, according to such a notion, inconsistency-tolerant query answering is intractable, even for very simple DLs. Therefore, we propose a different repair-based semantics, with the goal of reaching a good compromise between the expressive power of the semantics and the computational complexity of inconsistency-tolerant query answering. Indeed, we show that query answering under the new semantics is first-order rewritable in OBDA, even if the ontology is expressed in one of the most expressive members of the DL-Lite family

Datalog± Ontology Consolidation

Knowledge bases in the form of ontologies are receiving increasing attention as they allow to clearly represent both the available knowledge, which includes the knowledge in itself and the constraints imposed to it by the domain or the users. In particular, Datalog ± ontologies are attractive because of their property of decidability and the possibility of dealing with the massive amounts of data in real world environments; however, as it is the case with many other ontological languages, their application in collaborative environments often lead to inconsistency related issues. In this paper we introduce the notion of incoherence regarding Datalog± ontologies, in terms of satisfiability of sets of constraints, and show how under specific conditions incoherence leads to inconsistent Datalog ± ontologies. The main contribution of this work is a novel approach to restore both consistency and coherence in Datalog± ontologies. The proposed approach is based on kernel contraction and restoration is performed by the application of incision functions that select formulas to delete. Nevertheless, instead of working over minimal incoherent/inconsistent sets encountered in the ontologies, our operators produce incisions over non-minimal structures called clusters. We present a construction for consolidation operators, along with the properties expected to be satisfied by them. Finally, we establish the relation between the construction and the properties by means of a representation theorem. Although this proposal is presented for Datalog± ontologies consolidation, these operators can be applied to other types of ontological languages, such as Description Logics, making them apt to be used in collaborative environments like the Semantic Web.Fil: Deagustini, Cristhian Ariel David. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Martinez, Maria Vanina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Falappa, Marcelo Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Simari, Guillermo Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin

Paraconsistent Reasoning for OWL 2

A four-valued description logic has been proposed to reason with description logic based inconsistent knowledge bases. This approach has a distinct advantage that it can be implemented by invoking classical reasoners to keep the same complexity as under the classical semantics. However, this approach has so far only been studied for the basid description logic ALC. In this paper, we further study how to extend the four-valued semantics to the more expressive description logic SROIQ which underlies the forthcoming revision of the Web Ontology Language, OWL 2, and also investigate how it fares when adapated to tractable description logics including EL++, DL-Lite, and Horn-DLs. We define the four-valued semantics along the same lines as for ALC and show that we can retain most of the desired properties

Measuring Inconsistencies Propagation from Change Operation Based on Ontology Partitioning

International audienceInconsistency measure is an activity related to the ontology evolution. Being a coherent entity, an ontology must change and a modification operation in ontology could generate inconsistencies in its other parts. It is then important to measure these inconsistencies and follow the impact propagation. In this paper, we propose an inconsistency measure of an ontological change and its propagation effects on the other entities of the ontology. The measure is based on the weight of the dependencies between concepts in a community. Ontology is divided into communities which are a set of concepts that have preferential relations. To follow the impact propagation, we propose a process that uses the Change-and-Fix' approach to mark the impacted entities

Revision in networks of ontologies

euzenat2015aInternational audienceNetworks of ontologies are made of a collection of logic theories, called ontologies, related by alignments. They arise naturally in distributed contexts in which theories are developed and maintained independently, such as the semantic web. In networks of ontologies, inconsistency can come from two different sources: local inconsistency in a particular ontology or alignment, and global inconsistency between them. Belief revision is well-defined for dealing with ontologies; we investigate how it can apply to networks of ontologies. We formulate revision postulates for alignments and networks of ontologies based on an abstraction of existing semantics of networks of ontologies. We show that revision operators cannot be simply based on local revision operators on both ontologies and alignments. We adapt the partial meet revision framework to networks of ontologies and show that it indeed satisfies the revision postulates. Finally, we consider strategies based on network characteristics for designing concrete revision operators

Reasoning-Supported Quality Assurance for Knowledge Bases

The increasing application of ontology reuse and automated knowledge acquisition tools in ontology engineering brings about a shift of development efforts from knowledge modeling towards quality assurance. Despite the high practical importance, there has been a substantial lack of support for ensuring semantic accuracy and conciseness. In this thesis, we make a significant step forward in ontology engineering by developing a support for two such essential quality assurance activities

Expressive probabilistic description logics

AbstractThe work in this paper is directed towards sophisticated formalisms for reasoning under probabilistic uncertainty in ontologies in the Semantic Web. Ontologies play a central role in the development of the Semantic Web, since they provide a precise definition of shared terms in web resources. They are expressed in the standardized web ontology language OWL, which consists of the three increasingly expressive sublanguages OWL Lite, OWL DL, and OWL Full. The sublanguages OWL Lite and OWL DL have a formal semantics and a reasoning support through a mapping to the expressive description logics SHIF(D) and SHOIN(D), respectively. In this paper, we present the expressive probabilistic description logics P-SHIF(D) and P-SHOIN(D), which are probabilistic extensions of these description logics. They allow for expressing rich terminological probabilistic knowledge about concepts and roles as well as assertional probabilistic knowledge about instances of concepts and roles. They are semantically based on the notion of probabilistic lexicographic entailment from probabilistic default reasoning, which naturally interprets this terminological and assertional probabilistic knowledge as knowledge about random and concrete instances, respectively. As an important additional feature, they also allow for expressing terminological default knowledge, which is semantically interpreted as in Lehmann's lexicographic entailment in default reasoning from conditional knowledge bases. Another important feature of this extension of SHIF(D) and SHOIN(D) by probabilistic uncertainty is that it can be applied to other classical description logics as well. We then present sound and complete algorithms for the main reasoning problems in the new probabilistic description logics, which are based on reductions to reasoning in their classical counterparts, and to solving linear optimization problems. In particular, this shows the important result that reasoning in the new probabilistic description logics is decidable/computable. Furthermore, we also analyze the computational complexity of the main reasoning problems in the new probabilistic description logics in the general as well as restricted cases

Способи обчислення міри неконсистентностей OWL онтологій

Актуальність теми. Розвиток інформаційно-телекомунікаційних технологій сприяє збільшенню обсягів інформації, необхідної для роботи корпоративних систем. Тому на сьогодні існує проблема ефективної обробки даних. Одним із варіантів рішення цієї задачі є обробка даних в системах з використанням онтологій. Онтологія — формалізоване представлення знань про певну предметну область, придатне для автоматизованої обробки. Таким чином дані охоплюють менший об'єм пам'яті, а інформації з них можна отримати більше. Розмір онтологій невпинно зростає, тому неконсистентність або внутрішнє протиріччя онтології в таких випадках є звичним явищем. Для обробки та аналізу таких онтологій необхідно застосовувати способи обчислення міри неконсистентності, які і будуть розглянуті в даній дисертаційній роботі. Об’єктом дослідження є онтологічні системи, некосистентність при побудові онтологій. Предметом дослідження є способи обчислення міри неконсистентності OWL онтологій. Методи дослідження – методи математичної статистики для аналізу обчислення міри некосистентності OWL онтологій. Мета роботи: підвищення ефективності обробки неконсистентних онтологій шляхом застосування обчислення міри невідновідності; адаптація підходів до обчислення міри неконсистентності онтологій в описовій логіці до OWL онтологій; оптимізація способів обчислення міри неконсистентності онтологій задля зменшення часу їх виконання.Actuality of subject. The development of information and telecommunication technologies contributes to the increase of the amount of information necessary for the work of corporate systems. Therefore, today there is a problem of efficient data processing. One of the solutions to this problem is the processing of data in systems using ontologies. Ontology is a formalized representation of knowledge about a particular subject area, suitable for automated processing. This way, the data covers a smaller amount of memory, and more information can be obtained from it. The size of the ontologies is constantly increasing, so the inconsistency or internal contradiction of ontology in such cases is a common occurrence. For the processing and analysis of such ontologies, it is necessary to use methods for calculating the degree of inconsistency, which will be considered in this thesis. The object of the study is ontological systems, non-consistency in the construction of ontologies. The subject of the study is how to calculate the degree of non-consistency of OWL ontologies. Methods of research - methods of mathematical statistics for the analysis of the calculation of the degree of non-consistency of OWL ontologies. The purpose of the work: to increase the efficiency of processing inconsistent ontologies by applying the calculation of the degree of noncompliance; adaptation of approaches to calculating the degree of inconsistency of ontologies in descriptive logic to OWL ontologies; optimization of methods for calculating the degree of inconsistency of ontologies to reduce the time of their implementation.Актуальность темы. Развитие информационно- телекоммуникационных технологий способствует увеличению объемов информации, необходимой для работы корпоративных систем. Поэтому на сегодняшний день существует проблема эффективной обработки данных. Одним из вариантов решения этой задачи является обработка данных в системах с использованием онтологий. Онтология - формализованное представление знаний об определенной предметной области, пригодное для автоматизированной обработки. Таким образом данные охватывают меньший объем памяти, а информации по ним можно больше. Размер онтологий постоянно растет, поэтому неконсистентнисть или внутреннее противоречие онтологии в таких случаях является обычным явлением. Для обработки и анализа таких онтологий необходимо применять способы вычисления степени неконсистентности, которые и будут рассмотрены в данной диссертационной работе. Объектом исследования является онтологические системы, некосистентнисть при построении онтологий. Предметом исследования являются способы вычисления степени неконсистентности OWL онтологий. Методы исследования - методы математической статистики для анализа вычисления меры некосистентности OWL онтологий. Цель работы: повышение эффективности обработки неконсистентних онтологий путем применения вычисления меры несоответствия; адаптация подходов к вычислению степени неконсистентности онтологий в описательной логике в OWL онтологии; оптимизация способов вычисления меры неконсистентности онтологий для уменьшения времени их выполнения