http://dl.gi.de/handle/20.500.12116/36221 Thu, 23 Jul 2026 06:22:08 GMT 2026-07-23T06:22:08Z http://dl.gi.de/handle/20.500.12116/36316 LETHE: Forgetting and Uniform Interpolation for Expressive Description Logics Koopmann, Patrick Uniform interpolation and forgetting describe the task of projecting a given ontology into a user-specified vocabulary, that is, of computing a new ontology that only uses names from a specified set of names, while preserving all logical entailments that can be expressed with those names. This is useful for ontology analysis, ontology reuse and privacy. Lethe  is a tool for performing uniform interpolation on ontologies in expressive description logics, and it can be used from the command line, using a graphical interface, and as a Java library. It furthermore implements methods for computing logical difference and performing abduction using uniform interpolation. We present the tool together with an evaluation on a varied corpus of realistic ontologies. Wed, 01 Jan 2020 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/36316 2020-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/36310 Quantitative Variants of Language Equations and their Applications to Description Logics Marantidis, Pavlos Unification in description logics (DLs) has been introduced as a novel inference service that can be used to detect redundancies in ontologies, by finding different concepts that may potentially stand for the same intuitive notion. Together with the special case of matching, they were first investigated in detail for the DL $${\mathcal{FL}}_0$$ FL 0 , where these problems can be reduced to solving certain language equations. In this thesis, we extend this service in two directions. In order to increase the recall of this method for finding redundancies, we introduce and investigate the notion of approximate unification, which basically finds pairs of concepts that “almost” unify, in order to account for potential small modelling errors. The meaning of “almost” is formalized using distance measures between concepts. We show that approximate unification in $${\mathcal{FL}}_0$$ FL 0 can be reduced to approximately solving language equations, and devise algorithms for solving the latter problem for particular distance measures. Furthermore, we make a first step towards integrating background knowledge, formulated in so-called TBoxes, by investigating the special case of matching in the presence of TBoxes of different forms. We acquire a tight complexity bound for the general case, while we prove that the problem becomes easier in a restricted setting. To achieve these bounds, we take advantage of an equivalence characterization of $${\mathcal{FL}}_0$$ FL 0 concepts that is based on formal languages. Even though our results on the approximate setting cannot deal with TBoxes yet, we prepare the framework that future research can build on. Wed, 01 Jan 2020 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/36310 2020-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/36315 crowd: A Visual Tool for Involving Stakeholders into Ontology Engineering Tasks Braun, Germán; Gimenez, Christian; Cecchi, Laura; Fillottrani, Pablo We present crowd , a web-based visual tool for ontology engineering tasks. Its aim is to involve ontology developers and domain experts into a collaborative comprehension and design of conceptual models, enhancing the communication between them and assessing their quality by fully integrating automatic reasoning in the tool. In this paper we briefly describe the initial requirements, architecture and user interface, and make an evaluation based on a use case and a comparison with related tools. Wed, 01 Jan 2020 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/36315 2020-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/36312 Constructing and Extending Description Logic Ontologies using Methods of Formal Concept Analysis Kriegel, Francesco My thesis describes how methods from Formal Concept Analysis can be used for constructing and extending description logic ontologies. In particular, it is shown how concept inclusions can be axiomatized from data in the description logics $$\mathcal {E}\mathcal {L}$$ E L , $$\mathcal {M}$$ M , $$\textsf {Horn}$$ Horn - $$\mathcal {M}$$ M , and $$\textsf{Prob}\text{-}\mathcal {E}\mathcal {L}$$ Prob - E L . All proposed methods are not only sound but also complete, i.e., the result not only consists of valid concept inclusions but also entails each valid concept inclusion. Moreover, a lattice-theoretic view on the description logic $$\mathcal {E}\mathcal {L}$$ E L is provided. For instance, it is shown how upper and lower neighbors of $$\mathcal {E}\mathcal {L}$$ E L concept descriptions can be computed and further it is proven that the set of $$\mathcal {E}\mathcal {L}$$ E L concept descriptions forms a graded lattice with a non-elementary rank function. Wed, 01 Jan 2020 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/36312 2020-01-01T00:00:00Z