Special Issue on Ontologies and Data Management: Part II
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DITORIAL
Special Issue on Ontologies and Data Management: Part II Thomas Schneider1 · Mantas Šimkus2
© Gesellschaft für Informatik e.V. and Springer-Verlag GmbH Germany, part of Springer Nature 2020
1 Introduction We welcome the readers to Part II of the special issue on Ontologies and Data Management, an issue dedicated to the foundations of employing logic-based ontologies in data management scenarios. The first part of this special issue was published in September 2020 as Issue 3 of Volume 34 (see [15] for an overview of its content). We recall that the publication of this body of works is motivated by the progressively relevant challenge of managing information in the world where increasingly large amounts of loosely structured data are becoming available, e.g., due to the integration of information from heterogeneous data sources. It is acknowledged that traditional relational database tools and techniques alone are not sufficient to address this challenge, but complementing them with new techniques rooted in Knowledge Representation (KR) is believed to be a viable way to alleviate the problem. KR is an active research area of Artificial Intelligence (AI) that is developing methods for representing complex human knowledge in various formalisms, equipped with automated reasoning methods for a computer to draw useful conclusions from the represented knowledge. We recall that in this special issue we are mostly interested in knowledge captured in ontologies, expressed in Description Logics (DLs) as well as various rule-based languages. For a broader introduction to the area, we encourage an interested reader to see the dedicated survey [14]. DLs and rule-based languages are two prominent families of formalisms used in knowledge representation, yet they are orthogonal in many ways, and have their own advantages and disadvantages. DLs are more suitable for structuring knowledge and data, an advantage * Mantas Šimkus [email protected] Thomas Schneider thomas.schneider@uni‑bremen.de 1
University of Bremen, Bremen, Germany
TU Wien, Vienna, Austria
2
that has led DLs to be used as the logical foundation for the OWL family of ontology languages recommended by the World Wide Web Consortium (W3C). In contrast to DLs, rules are very suitable for expressing various information needs, which is witnessed by their use as query languages for relational databases (DATALOG being the most prominent rule-based query language). For this reason, understanding ways of combining the strengths of DLs and rule-based languages is an active research area, which we touch upon in this part of the special issue [1, 4, 6–9]. In contrast to standard rule-based languages, in DLs one usually makes the open-world assumption, which is suitable for constructing generic, reusable, data-independent ontologies. In rule-based languages usually the closed-world assumption is made in order to draw some common-sense conclusions from the concrete available data. Combining the closed-world and the open-world assumptions naturally leads to n
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