A framework for integrating and transforming between ontologies and relational databases

Bridging the gap between ontologies, expressed in the Web Ontology Language (OWL), and relational databases is a necessity for realising the Semantic Web vision. Relational databases are considered a good solution for storing and processing ontologies with a large amount of data. Moreover, the vast majority of current websites store data in relational databases, and therefore being able to generate ontologies from such databases is important to support the development of the Semantic Web. Most of the work concerning this topic has either (1) extracted an OWL ontology from an existing relational database that represents as exactly as possible the relational schema, using a limited range of OWL modelling constructs, or (2) extracted a relational database from an existing OWL ontology, that represents as much as possible the OWL ontology. By way of contrast, this thesis proposes a general framework for transforming and mapping between ontologies and databases, via an intermediate low-level Hyper-graph Data Model. The transformation between relational and OWL schemas is expressed using directional Both-As-View mappings, allowing a precise definition of the equivalence between the two schemas, hence data can be mapped back and forth between them. In particular, for a given OWL ontology, we interpret the expressive axioms either as triggers, conforming to the Open-World Assumption, that performs a forward-chaining materialisation of inferred data, or as constraints, conforming to the Closed-World Assumption, that performs a consistency checking. With regards to extracting ontologies from relational databases, we transform a relational database into an exact OWL ontology, then enhance it with rich OWL 2 axioms, using a combination of schema and data analysis. We then apply machine learning algorithms to rank the suggested axioms based on past users’ relevance. A proof-of-concept tool, OWLRel, has been implemented, and a number of well-known ontologies and databases have been used to evaluate the approach and the OWLRel tool.Open Acces

Using ontologies to synchronize change in relational database systems

Ontology is a building block of the semantic Web. Ontology building requires a detailed domain analysis, which in turn requires financial resources, intensive domain knowledge and time. Domain models in industry are frequently stored as relational database schemas in relational databases. An ontology base underlying such schemas can represent concepts and relationships that are present in the domain of discourse. However, with ever increasing demand for wider access and domain coverage, public databases are not static and their schemas evolve over time. Ontologies generated according to these databases have to change to reflect the new situation. Once a database schema is changed, these changes in the schema should also be incorporated in any ontology generated from the database. It is not possible to generate a fresh version of the ontology using the new database schema because the ontology itself may have undergone changes that need to be preserved. To tackle this problem, this paper presents a generic framework that will help to generate and synchronize ontologies with existing data sources. In particular we address the translation between ontologies and database schemas, but our proposal is also sufficiently generic to be used to generate and maintain ontologies based on XML and object oriented databases

RODI: Benchmarking Relational-to-Ontology Mapping Generation Quality

Accessing and utilizing enterprise or Web data that is scattered across multiple data sources is an important task for both applications and users. Ontology-based data integration, where an ontology mediates between the raw data and its consumers, is a promising approach to facilitate such scenarios. This approach crucially relies on useful mappings to relate the ontology and the data, the latter being typically stored in relational databases. A number of systems to support the construction of such mappings have recently been developed. A generic and effective benchmark for reliable and comparable evaluation of the practical utility of such systems would make an important contribution to the development of ontology-based data integration systems and their application in practice. We have proposed such a benchmark, called RODI. In this paper, we present a new version of RODI, which significantly extends our previous benchmark, and we evaluate various systems with it. RODI includes test scenarios from the domains of scientific conferences, geographical data, and oil and gas exploration. Scenarios are constituted of databases, ontologies, and queries to test expected results. Systems that compute relational-to-ontology mappings can be evaluated using RODI by checking how well they can handle various features of relational schemas and ontologies, and how well the computed mappings work for query answering. Using RODI, we conducted a comprehensive evaluation of seven systems

Significant properties in the preservation of relational databases

Relational Databases are the most frequent type of databases used by organizations worldwide and are the base of several information systems. As in all digital objects, and concerning the digital preservation of them, the signi cant properties (signi cant characteristics) must be de ned so that adopted strategies are appropriate. In previous work a neutral format (hardware and software independent) | DBML | was adopted to achieve a standard format used in the digital preservation of the relational databases data and structure. In this paper we walk further in the de nition of the signi cant properties by considering the database semantics as an important characteristic that should be also preserved. For the representation of this higher level of abstraction we are going to use an ontology based approach. We will extract the entityrelationship model from the DBML representation and we will represent it as an ontology

Storing an OWL 2 Ontology in a Relational Database Structure

This paper examines the possibility of storing OWL 2 based ontology information in a classical relational database and reviews some existing methods for ontology databases. In most cases a database is a fitting solution for storing and sharing information among systems, clients or agents. Similarly, in order to make domain ontology information more accessible to systems, in a comparable way, it can be stored and provided in a database form. As of today, there is no consensus on a specific ontology database structure. The main focus of this paper is specifically on OWL 2 as a basis for the description of ontology centric information in a database. The Web Ontology Language OWL 2 is a language for describing ontology information for the Semantic Web. As such it consists of a list of reserved words and grammatical rules for defining many parts of ontology knowledge. Based on this language specification this paper examines the possibility of storing information in a relational database for the description of domain ontology information. By creating a database structure based on OWL2 it is feasible to obtain an approach to storing information about the domain ontology in an utilizable way, by using its descriptive abilities. Nowadays multiple approaches to storing ontology information and OWL in databases exist; most of them are based on storing RDF data or provide persistence for specific OWL software libraries. The examination of the existing approaches provided in this paper, shows how they differ from the goal of obtaining a general, more easily usable and less software library specific database for domain ontology centric information. This paper describes a version of a simple relational database capable of holding and providing ontology knowledge on demand, which can be implemented on a database management system of choice.

Bridging the gap between the semantic web and big data: answering SPARQL queries over NoSQL databases

Nowadays, the database field has gotten much more diverse, and as a result, a variety of non-relational (NoSQL) databases have been created, including JSON-document databases and key-value stores, as well as extensible markup language (XML) and graph databases. Due to the emergence of a new generation of data services, some of the problems associated with big data have been resolved. In addition, in the haste to address the challenges of big data, NoSQL abandoned several core databases features that make them extremely efficient and functional, for instance the global view, which enables users to access data regardless of how it is logically structured or physically stored in its sources. In this article, we propose a method that allows us to query non-relational databases based on the ontology-based access data (OBDA) framework by delegating SPARQL protocol and resource description framework (RDF) query language (SPARQL) queries from ontology to the NoSQL database. We applied the method on a popular database called Couchbase and we discussed the result obtained

Mapping Data to Ontologies with Exceptions Using Answer Set Programming

In ontology-based data access (OBDA), databases are connected to an ontology via mappings from queries over the database to queries over the ontology. In this paper, we define an ASP-based semantics for mappings from relational databases to first-order ontologies, augmented with queries over the ontology in the mapping rule bodies. The resulting formalism can be described as ”ASP modulo theories”, and can be used to express constraints and exceptions in OBDA systems, as well as being a powerful mechanism for succinctly representing OBDA mappings. Furthermore, we show that brave reasoning in this setting has either the same data complexity as ASP, or is at least as hard as the complexity of checking entailment for the ontology queries. Moreover, despite the interaction of ASP rules and the ontology, most properties of ASP are preserved. Finally, we show that for ontologies with UCQ-rewritable queries there exists a natural reduction from our framework to ASP with existential variables