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Designing Core Ontologies
(2011)
One of the key factors that hinders integration of distributed, heterogeneous information systems is the lack of a formal basis for modeling the complex, structured knowledge that is to be exchanged. To alleviate this situation, we present an approach based on core ontologies. Core ontologies are characterized by a high degree of axiomatization and formal precision. This is achieved by basing on a foundational ontology. In addition, core ontologies should follow a pattern-oriented design approach. By this, they are modular and extensible. Core ontologies allow for reusing the structured knowledge they define as well as integrating existing domainrnknowledge. The structured knowledge of the core ontologies is clearly separated from the domain-specific knowledge. Such core ontologies allow for both formally conceptualize their particular fields and to be flexibly combined to cover the needsrnof concrete, complex application domains. Over the last years, we have developed three independent core ontologies for events and objects, multimedia annotations, and personal information management. In this paper, we present the simultaneousrnuse and integration of our core ontologies at the example of a complex, distributed socio-technical system of emergency response. We describe our design approach for core ontologies and discuss the lessons learned in designing them. Finally, we elaborate on the beauty aspects of our core ontologies.
The novel mobile application csxPOI (short for: collaborative, semantic, and context-aware points-of-interest) enables its users to collaboratively create, share, and modify semantic points of interest (POI). Semantic POIs describe geographic places with explicit semantic properties of a collaboratively created ontology. As the ontology includes multiple subclassiffcations and instantiations and as it links to DBpedia, the richness of annotation goes far beyond mere textual annotations such as tags. With the intuitive interface of csxPOI, users can easily create, delete, and modify their POIs and those shared by others. Thereby, the users adapt the structure of the ontology underlying the semantic annotations of the POIs. Data mining techniques are employed to cluster and thus improve the quality of the collaboratively created POIs. The semantic POIs and collaborative POI ontology are published as Linked Open Data.
Ontologies play an important role in knowledge representation for sharing information and collaboratively developing knowledge bases. They are changed, adapted and reused in different applications and domains resulting in multiple versions of an ontology. The comparison of different versions and the analysis of changes at a higher level of abstraction may be insightful to understand the changes that were applied to an ontology. While there is existing work on detecting (syntactical) differences and changes in ontologies, there is still a need in analyzing ontology changes at a higher level of abstraction like ontology evolution or refactoring pattern. In our approach we start from a classification of model refactoring patterns found in software engineering for identifying such refactoring patterns in OWL ontologies using DL reasoning to recognize these patterns.
Semantic descriptions of non-textual media available on the web can be used to facilitate retrieval and presentation of media assets and documents containing them. While technologies for multimedia semantic descriptions already exist, there is as yet no formal description of a high quality multimedia ontology that is compatible with existing (semantic) web technologies. We explain the complexity of the problem using an annotation scenario. We then derive a number of requirements for specifying a formal multimedia ontology, including: compatibility with MPEG-7, embedding in foundational ontologies, and modularisation including separation of document structure from domain knowledge. We then present the developed ontology and discuss it with respect to our requirements.
The lack of a formal event model hinders interoperability in distributed event-based systems. Consequently, we present in this paper a formal model of events, called F. The model bases on an upper-level ontology and pro-vides comprehensive support for all aspects of events such as time and space, objects and persons involved, as well as the structural aspects, namely mereological, causal, and correlational relationships. The event model provides a flexible means for event composition, modeling of event causality and correlation, and allows for representing different interpretations of the same event. The foundational event model F is developed in a pattern-oriented approach, modularized in different ontologies, and can be easily extended by domain specifific ontologies.