Ontological Modeling of Certification and Inspection Process to Support Smart Disclosure of Product Information

Djoko S. Sayogo, Weijia Ran, Giri Kumar Tayi, Joanne S. Luciano, Luis F. Luna-Reyes, Nicolau Depaula, Holly Jarman, Jing Zhang, Jana Hrdinova, Deborah Lines Andersen, David F. Andersen, Theresa A. Pardo

Source Title: International Journal of Public Administration in the Digital Age (IJPADA)3(2)

ISSN: 2334-4520|EISSN: 2334-4539|EISBN13: 9781466693975|DOI: 10.4018/IJPADA.2016040106

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MLA

Sayogo, Djoko S., et al. "Ontological Modeling of Certification and Inspection Process to Support Smart Disclosure of Product Information." IJPADA vol.3, no.2 2016: pp.86-108. http://doi.org/10.4018/IJPADA.2016040106

APA

Sayogo, D. S., Ran, W., Tayi, G. K., Luciano, J. S., Luna-Reyes, L. F., Depaula, N., Jarman, H., Zhang, J., Hrdinova, J., Andersen, D. L., Andersen, D. F., & Pardo, T. A. (2016). Ontological Modeling of Certification and Inspection Process to Support Smart Disclosure of Product Information. International Journal of Public Administration in the Digital Age (IJPADA), 3(2), 86-108. http://doi.org/10.4018/IJPADA.2016040106

Chicago

Sayogo, Djoko S., et al. "Ontological Modeling of Certification and Inspection Process to Support Smart Disclosure of Product Information," International Journal of Public Administration in the Digital Age (IJPADA) 3, no.2: 86-108. http://doi.org/10.4018/IJPADA.2016040106

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Abstract

The increasing number of certification schemes diminishes the utility of certifications as private regulation and creates several policy challenges. The undergoing efforts to help consumers verify the accuracy of information created by private regulation mechanisms such as certification are currently confronted with the complexities of certification and labeling systems and the difficulties in linking data points across various certification schemes. This paper presents the development of certification and inspection ontology to support smart disclosure of product information. This study proposes that the resulting ontology enables information integration and standardization thus supporting knowledge discovery and sharing by synthesizing information across disparate data sources that is valuable for informing data-driven policy formulation. The ontology also supports standardization of an agreed set of terms and semantics for currently fragmented certification and inspection schemes to support comparability across different certification schemes. The accuracy and consistency of the proposed ontology are verified by using current reasoning tools to run queries based on a set of predefined competency questions.