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Projekt Druckansicht

Logische Methoden für die Entwicklung von Ontologien

Antragsteller Dr. Yevgeny Kazakov
Fachliche Zuordnung Theoretische Informatik
Bild- und Sprachverarbeitung, Computergraphik und Visualisierung, Human Computer Interaction, Ubiquitous und Wearable Computing
Förderung Förderung von 2011 bis 2017
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 203848503
 
Erstellungsjahr 2019

Zusammenfassung der Projektergebnisse

To process information in an intelligent way, it is necessary to represent relevant knowledge so that it can be understood not only by humans but also by computers. Logic-based ontology languages, such as OWL make this possible by formally specifying which information implicitly follows from the knowledge described by means of ontological axioms. This way, ontologies can be developed by domain experts similarly to software. Just like in software development, ontology development is a error-prone process. This project focuses on development of logic-based methods and tools that can help developing hight quality ontologies. The central part of such tools are ontology reasoners. These are programs that can automatically compute logical consequences of ontologies, e.g., to verify correctness of the information and answer user queries. The first outcome of the project are new methods and tools for ontology debugging. In the first phase of the project, we have developed general goal-directed procedure for generation of proofs for ontological entailments. In the second phase, we used these proofs in newly developed plugins for the ontology editor Protege. The Proof Explanation plugin allows an ontology developer to inspect proofs for an entailment of interest. The plugin includes several proof simplification strategies to improve understanding of proofs. It is also common to explain the ontological entailments using justifications—minimal subset of axioms that entail the given logical conclusion. In our next contribution, we have developed a new resolution-based procedures, using which all such justifications can be efficiently enumerated. Our procedure has some unique advantages compared to other procedures for enumeration of justifications, which use propositional SAT solvers. For example, one can enumerate justification in any desirable order. We have implemented and optimized our procedure, and obtained some very encouraging experimental results. For example, we have been able, for the first time, to compute all justifications for the reasoning results in one of the largest and widely used medical ontologies SNOMED CT. We have developed several Protege plugins that can display such justifications to ontology developers. The second outcome of the project are new complexity results for reasoning with distributed ontologies. Just like in software development, ontologies are rarely developed from scratch, but rather built from existing ontologies. We have defined a new, semantic, ontology import mechanism, using which only the logical consequences over a specified vocabulary of symbols is imported from existing ontologies. We have studied the expressive power of semantic import relations for different ontology languages, and came to a surprising conclusion that the standard reasoning problems become undecidable already for languages, for which reasoning without imports is tractable. The undecidability result is obtained using ontologies with cyclic semantic import relations, which augment languages with a certain form of recursion. But even when restricting the import relations to be acyclic, we showed that reasoning in ontology networks becomes exponentially harder for most of the commonly used languages. The main outcome of these results is that semantic importing gives a new expressive power to ontology languages, which, consequently, increases the worst-case complexity of reasoning. The outcomes of the project were published in workshop and conference publications, and the software was made available in open source tools and libraries. Out tools, such as the ELK reasoner, developed in the first phase of the project, are already used in multiple research and commercial projects, such as in the development of the widely used Gene Ontology and SNOMED CT. We are confident that the new outcomes of the projects will be also used in these settings.

Projektbezogene Publikationen (Auswahl)

 
 

Zusatzinformationen

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