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

Inconsistency Handling in Ontology-Mediated Query Answering: A Progress Report

International audienceThis paper accompanies an invited talk on inconsistency handling in OMQA and presents a concise summary of the research that has been conducted in the area

Dealing with Inconsistencies and Updates in Description Logic Knowledge Bases

The main purpose of an "Ontology-based Information System" (OIS) is to provide an explicit description of the domain of interest, called ontology, and let all the functions of the system be based on such representation, thus freeing the users from the knowledge about the physical repositories where the real data reside. The functionalities that an OIS should provide to the user include both query answering, whose goal is to extract information from the system, and update, whose goal is to modify the information content of the system in order to reflect changes in the domain of interest. The "ontology" is a formal, high quality intentional representation of the domain, designed in such a way to avoid inconsistencies in the modeling of concepts and relationships. On the contrary, the extensional level of the system, constituted by a set of autonomous, heterogeneous data sources, is built independently from the conceptualization represented by the ontology, and therefore may contain information that is incoherent with the ontology itself. This dissertation presents a detailed study on the problem of dealing with inconsistencies in OISs, both in query answering, and in performing updates. We concentrate on the case where the knowledge base in the OISs is expressed in Description Logics, especially the logics of the DL-lite family. As for query answering, we propose both semantical frameworks that are inconsistency-tolerant, and techniques for answering unions of conjunctive queries posed to OISs under such inconsistency-tolerant semantics. As for updates, we present an approach to compute the result of updating a possibly inconsistent OIS with both insertion and deletion of extensional knowledge

Querying and Repairing Inconsistent Prioritized Knowledge Bases: Complexity Analysis and Links with Abstract Argumentation

International audienceIn this paper, we explore the issue of inconsistency handling over prioritized knowledge bases (KBs), which consist of an ontology, a set of facts, and a priority relation between conflicting facts. In the database setting, a closely related scenario has been studied and led to the definition of three different notions of optimal repairs (global, Pareto, and completion) of a prioritized inconsistent database. After transferring the notions of globally-, Pareto- and completion-optimal repairs to our setting, we study the data complexity of the core reasoning tasks: query entailment under inconsistency-tolerant semantics based upon optimal repairs, existence of a unique optimal repair, and enumeration of all optimal repairs. Our results provide a nearly complete picture of the data complexity of these tasks for ontologies formulated in common DL-Lite dialects. The second contribution of our work is to clarify the relationship between optimal repairs and different notions of extensions for (set-based) argumentation frameworks. Among our results, we show that Pareto-optimal repairs correspond precisely to stable extensions (and often also to preferred extensions), and we propose a novel semantics for prioritized KBs which is inspired by grounded extensions and enjoys favourable computational properties. Our study also yields some results of independent interest concerning preference-based argumentation frameworks

Querying and Repairing Inconsistent Prioritized Knowledge Bases: Complexity Analysis and Links with Abstract Argumentation

In this paper, we explore the issue of inconsistency handling over prioritized knowledge bases (KBs), which consist of an ontology, a set of facts, and a priority relation between conflicting facts. In the database setting, a closely related scenario has been studied and led to the definition of three different notions of optimal repairs (global, Pareto, and completion) of a prioritized inconsistent database. After transferring the notions of globally-, Pareto- and completion-optimal repairs to our setting, we study the data complexity of the core reasoning tasks: query entailment under inconsistency-tolerant semantics based upon optimal repairs, existence of a unique optimal repair, and enumeration of all optimal repairs. Our results provide a nearly complete picture of the data complexity of these tasks for ontologies formulated in common DL-Lite dialects. The second contribution of our work is to clarify the relationship between optimal repairs and different notions of extensions for (set-based) argumentation frameworks. Among our results, we show that Pareto-optimal repairs correspond precisely to stable extensions (and often also to preferred extensions), and we propose a novel semantics for prioritized KBs which is inspired by grounded extensions and enjoys favourable computational properties. Our study also yields some results of independent interest concerning preference-based argumentation frameworks.Comment: 27 pages. To appear in the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020) without the appendi

Federated knowledge base debugging in DL-Lite A

Due to the continuously growing amount of data the federation of different and distributed data sources gained increasing attention. In order to tackle the challenge of federating heterogeneous sources a variety of approaches has been proposed. Especially in the context of the Semantic Web the application of Description Logics is one of the preferred methods to model federated knowledge based on a well-defined syntax and semantics. However, the more data are available from heterogeneous sources, the higher the risk is of inconsistency – a serious obstacle for performing reasoning tasks and query answering over a federated knowledge base. Given a single knowledge base the process of knowledge base debugging comprising the identification and resolution of conflicting statements have been widely studied while the consideration of federated settings integrating a network of loosely coupled data sources (such as LOD sources) has mostly been neglected. In this thesis we tackle the challenging problem of debugging federated knowledge bases and focus on a lightweight Description Logic language, called DL-LiteA, that is aimed at applications requiring efficient and scalable reasoning. After introducing formal foundations such as Description Logics and Semantic Web technologies we clarify the motivating context of this work and discuss the general problem of information integration based on Description Logics. The main part of this thesis is subdivided into three subjects. First, we discuss the specific characteristics of federated knowledge bases and provide an appropriate approach for detecting and explaining contradictive statements in a federated DL-LiteA knowledge base. Second, we study the representation of the identified conflicts and their relationships as a conflict graph and propose an approach for repair generation based on majority voting and statistical evidences. Third, in order to provide an alternative way for handling inconsistency in federated DL-LiteA knowledge bases we propose an automated approach for assessing adequate trust values (i.e., probabilities) at different levels of granularity by leveraging probabilistic inference over a graphical model. In the last part of this thesis, we evaluate the previously developed algorithms against a set of large distributed LOD sources. In the course of discussing the experimental results, it turns out that the proposed approaches are sufficient, efficient and scalable with respect to real-world scenarios. Moreover, due to the exploitation of the federated structure in our algorithms it further becomes apparent that the number of identified wrong statements, the quality of the generated repair as well as the fineness of the assessed trust values profit from an increasing number of integrated sources

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

10. Interuniversitäres Doktorandenseminar Wirtschaftsinformatik Juli 2009

Begonnen im Jahr 2000, ist das Interuniversitäre Wirtschaftsinformatik-Doktorandenseminar mittlerweile zu einer schönen Tradition geworden. Zunächst unter Beteiligung der Universitäten Leipzig und Halle-Wittenberg gestartet. Seit 2003 wird das Seminar zusammen mit der Jenaer Universität durchgeführt, in diesem Jahr sind erstmals auch die Technische Universität Dresden und die TU Bergakademie Freiberg dabei. Ziel der Interuniversitären Doktorandenseminare ist der über die eigenen Institutsgrenzen hinausgehende Gedankenaustausch zu aktuellen, in Promotionsprojekten behandelten Forschungsthemen. Indem der Schwerpunkt der Vorträge auch auf das Forschungsdesign gelegt wird, bietet sich allen Doktoranden die Möglichkeit, bereits in einer frühen Phase ihrer Arbeit wichtige Hinweise und Anregungen aus einem breiten Hörerspektrum zu bekommen. In den vorliegenden Research Papers sind elf Beiträge zum diesjährigen Doktorandenseminar in Jena enthalten. Sie stecken ein weites Feld ab - vom Data Mining und Wissensmanagement über die Unterstützung von Prozessen in Unternehmen bis hin zur RFID-Technologie. Die Wirtschaftsinformatik als typische Bindestrich-Informatik hat den Ruf einer thematischen Breite. Die Dissertationsprojekte aus fünf Universitäten belegen dies eindrucksvoll.

A multi-agent approach to adaptive learning using a structured ontology classification system

Diagnostic assessment is an important part of human learning. Tutors in face-to-face classroom environment evaluate students’ prior knowledge before the start of a relatively new learning. In that perspective, this thesis investigates the development of an-agent based Pre-assessment System in the identification of knowledge gaps in students’ learning between a student’s desired concept and some prerequisites concepts. The aim is to test a student's prior skill before the start of the student’s higher and desired concept of learning. This thesis thus presents the use of Prometheus agent based software engineering methodology for the Pre-assessment System requirement specification and design. Knowledge representation using a description logic TBox and ABox for defining a domain of learning. As well as the formal modelling of classification rules using rule-based approach as a reasoning process for accurate categorisation of students’ skills and appropriate recommendation of learning materials. On implementation, an agent oriented programming language whose facts and rule structure are prolog-like was employed in the development of agents’ actions and behaviour. Evaluation results showed that students have skill gaps in their learning while they desire to study a higher-level concept at a given time

Water utility decision support through the semantic web of things

Urban environments are urgently required to become smarter. However, building advanced applications on the Internet of Things requires seamless interoperability. This paper proposes a water knowledge management platform which extends the Internet of Things towards a Semantic Web of Things, by leveraging the semantic web to address the heterogeneity of web resources. Proof of concept is demonstrated through a decision support tool which leverages both the data-driven and knowledge-based programming interfaces of the platform. The solution is grounded in a comprehensive ontology and rule base developed with industry experts. This is instantiated from GIS, sensor, and EPANET data for a Welsh pilot. The web service provides discoverability, context, and meaning for the sensor readings stored in a scalable database. An interface displays sensor data and fault inference notifications, leveraging the complementary nature of serving coherent lower and higher-order knowledge