Linking Data to Ontologies

Abstract

Abstract. Many organizations nowadays face the problem of accessing existing data sources by means of flexible mechanisms that are both powerful and efficient. Ontologies are widely considered as a suitable formal tool for sophisticated data access. The ontology expresses the domain of interest of the information system at a high level of abstraction, and the relationship between data at the sources and instances of concepts and roles in the ontology is expressed by means of mappings. In this paper we present a solution to the problem of designing effective systems for ontology-based data access. Our solution is based on three main ingredients. First, we present a new ontology language, based on Description Logics, that is particularly suited to reason with large amounts of instances. The second ingredient is a novel mapping language that is able to deal with the so-called impedance mismatch problem, i.e., the problem arising from the difference between the basic elements managed by the sources, namely data, and the elements managed by the ontology, namely objects. The third ingredient is the query answering method, that combines reasoning at the level of the ontology with specific mechanisms for both taking into account the mappings and efficiently accessing the data at the sources.

Ontology-Driven Extraction of Event Logs from Relational Databases

“…or in the Type column of the same table (which tracks whether the publication is a full/short paper, a front matter, or other). This so-called impedance mismatch is a challenging problem that has been thoroughly investigated in the field of intelligent data access and integration [11].…”

“…In this work, we tackle this overarching problem by resorting to a novel combination of techniques coming from intelligent data access and integration, extended and adapted to the case of process mining and flexible extraction of multi-dimensional event logs from raw relational data. To attack the first problem, we resort to the well-established OBDA framework, which allows one to link the raw data to the domain ontology and overcome the impedance mismatch [1,11]. To tackle the second challenge, we define an event log ontology that mirrors XES, and provide an annotation language to the user, which makes it possible to capture semantic links between the constitutive (combinations of) elements in the domain ontology, and corresponding elements in XES.…”

“…Differently from previous work, the extraction is driven by a conceptual representation of the domain of interest in terms of an ontology. This ontology is linked to the underlying legacy data leveraging the well-established ontology-based data access (OBDA) paradigm [1,11]. In this way, domain experts can focus on the ontological level only, while the connection with the underlying data is automatically managed by the OBDA system.…”

Answering SPARQL Queries over Databases under OWL 2 QL Entailment Regime

“…Ontology-based data access and management (OBDA) is a popular paradigm of organising access to various types of data sources that has been developed since the mid 2000s [11,17,24]. In a nutshell, OBDA separates the user from the data sources (relational databases, triple stores, etc.)…”

“…by means of an ontology which provides the user with a convenient query vocabulary, hides the structure of the data sources, and can enrich incomplete data with background knowledge. About a dozen OBDA systems have been implemented in both academia and industry; e.g., [27,30,24,4,23,15,12,8,20,22]. Most of them support conjunctive queries and the OWL 2 QL profile of OWL 2 as the ontology language (or its generalisations to existential datalog rules).…”