Ontologies and other knowledge organization systems, such as controlled vocabularies, can be used to enhance the findability of information. By describing the contents of documents using a shared, harmonized terminology, information systems can provide efficient search and browsing functionalities for the contents. Explicit descriptive metadata aims to solve some of the prevailing issues in full text search in many search engines, including the processing of synonyms and homonyms. The use of ontologies as domain models enables the machine-processability of contents, semantic reasoning, information integration, and other intelligent ways of processing the data. The utilization of knowledge organization systems in content indexing and information retrieval can be facilitated by providing automated tools for their efficient use. This thesis studies and presents novel methods and systems for publishing and using knowledge organization systems as ontology services. The research is conducted by designing and evaluating prototype systems that support the use of ontologies in real-life use cases. The research follows the principles of the design science and action research methodologies. The presented ONKI system provides user interface components and application programming interfaces that can be integrated into external applications to enable ontology-based workflows. The features of the system are based on analyzing the needs of the main user groups of ontologies. The common functionalities identified in ontology-based workflows include concept search, browsing, and selection. The thesis presents the Linked Open Ontology cloud approach for managing and publishing a set of interlinked ontologies in an ontology service. The system enables the users to use multiple ontologies as a single, interoperable, cross-domain representation instead of individual ontologies. For facilitating the simultaneous use of ontologies published in different ontology repositories, the Normalized Ontology Repository approach is presented. As a use case of managing and publishing a semantically rich knowledge organization system as an ontology, the thesis presents the Taxon Meta-Ontology model for biological nomenclatures and classifications. The model supports the representation of changes and differing opinions of taxonomic concepts. The ONKI system and the ontologies developed using the methods presented in this thesis have been provided as a living lab service http://onki.fi, which has been run since 2008. The service provides tools and support for the users of ontologies, including content indexers, information searchers, ontology developers, and application developers.
|Translated title of the contribution||Ontology Services for Knowledge Organization Systems|
|Publication status||Published - 2017|
|MoE publication type||G5 Doctoral dissertation (article)|
- semantic web
- knowledge organization systems
- metadata creation
- ontology services