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Abstract

Domain experts are skilled in buliding a narrow ontology that reflects their subfield of expertise based on their work experience and personal beliefs. We call this type of ontology a single-viewpoint ontology. There can be a variety of such single viewpoint ontologies that represent a wide spectrum of subfields and expert opinions on the domain. However, to have a complete formal vocabulary for the domain they need to be linked and unified into a multiviewpoint model while having the subjective viewpoint statements marked and distinguished from the objectively true statements. In this study, we propose and implement a two-phase methodology for multiviewpoint ontology construction by nonexpert users. The proposed methodology was implemented for the domain of the effect of diet on health. A large-scale crowdsourcing experiment was conducted with about 750 ontological statements to determine whether each of these statements is objectively true, viewpoint, or erroneous. Typically, in crowdsourcing experiments the workers are asked for their personal opinions on the given subject. However, in our case their ability to objectively assess others' opinions was examined as well. Our results show substantially higher accuracy in classification for the objective assessment approach compared to the results based on personal opinions.

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Abstract

Plurality of beliefs and theories in different knowledge domains calls for modelling multi-viewpoint ontologies and knowledge organization systems (KOS). A generic theoretical approach recently proposed for heterogeneity representation in KOS was linking each ontological statement to a specific validity scope to determine a set of conditions under which the statement is valid. However, the practical applicability of this approach has yet to be empirically assessed. In addition, there is still a need to investigate the types of inconsistencies that might arise in multi-viewpoint ontologies as well as their possible causes. This study proposes a new framework for systematic analysis and classification of inconsistencies in multi-viewpoint ontologies. The framework is based on eight generic logical structures of ontological statements. To test the validity of the proposed framework, two ontologies from different knowledge domains were examined. We found that only three of the eight structures led to inconsistencies in both ontologies, while the other two structures were always present in logically consistent statements. The study has practical implications for building diversified and personalized knowledge systems.

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Date

20. 1.2015 18:30:22