Birgitta König-Ries
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Birgitta König-Ries has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Alsayed Algergawy
University of Jena
1 shared publication - Friederike Klan
German Aerospace Center (DLR), Institute of Data Science, Jena, Germany
1 shared publication - Samira Babalou
Friedrich Schiller University Jena
1 shared publication
Latest Publications
- Open Access
- 24 August 2020
- Published by Springer Nature in Journal on Data Semantics
- Vol. 9 (2-3) , 53-83
Ontology Modularization with OAPT
Ontologies are the backbone of the Semantic Web. As a result, the number of existing ontologies and the number of topics covered by them has increased considerably. With this, reusing these ontologies becomes preferable to constructing new ontologies from scratch. However, a user might be interested in a part and/or a set of parts of a given ontology, only. Therefore, ontology modularization, i.e., splitting up an ontology into smaller parts that can be independently used, becomes a necessity. In this paper, we introduce a new approach to partition ontology based on theseeding-basedscheme, which is developed and implemented through the Ontology Analysis and Partitioning Tool (OAPT). This tool proceeds according to the following methodology: first, before a candidate ontology is partitioned,OAPToptionally analyzes the input ontology to determine, if this ontology is worth considering using a predefined set of criteria that quantify the semantic and structural richness of the ontology. After that, we apply the seeding-based partitioning algorithm to modularize it into a set of modules. To decide upon a suitable number of modules that will be generated by partitioning the ontology, we provide the user a recommendation based on an information theoretic model selection method. We demonstrate the effectiveness of theOAPTtool and validate the performance of the partitioning approach by conducting an extensive set of experiments. The results prove the quality and the efficiency of the proposed tool.
- 24 August 2020
- Published by Springer Nature in Journal on Data Semantics
- Vol. 9 (2-3) , 53-83
Open AccessOntology Modularization with OAPT
Ontologies are the backbone of the Semantic Web. As a result, the number of existing ontologies and the number of topics covered by them has increased considerably. With this, reusing these ontologies becomes preferable to constructing new ontologies from scratch. However, a user might be interested in a part and/or a set of parts of a given ontology, only. Therefore, ontology modularization, i.e., splitting up an ontology into smaller parts that can be independently used, becomes a necessity. In this paper, we introduce a new approach to partition ontology based on theseeding-basedscheme, which is developed and implemented through the Ontology Analysis and Partitioning Tool (OAPT). This tool proceeds according to the following methodology: first, before a candidate ontology is partitioned,OAPToptionally analyzes the input ontology to determine, if this ontology is worth considering using a predefined set of criteria that quantify the semantic and structural richness of the ontology. After that, we apply the seeding-based partitioning algorithm to modularize it into a set of modules. To decide upon a suitable number of modules that will be generated by partitioning the ontology, we provide the user a recommendation based on an information theoretic model selection method. We demonstrate the effectiveness of theOAPTtool and validate the performance of the partitioning approach by conducting an extensive set of experiments. The results prove the quality and the efficiency of the proposed tool.