A semantic-based decision support platform to assist products’ eco-labeling process

• Published in: Industrial management + data systems Vol. 117; no. 7; pp. 1340 - 1361
• Main Authors: Xu, Da, Karray, Mohamed Hedi, Archimède, Bernard
• Format: Journal Article
• Language: English
• Published: Wembley Emerald Publishing Limited 01.01.2017; Emerald Group Publishing Limited
• Subjects: Certification; Consolidation; Decision making; Decision support systems; Descriptive labeling; Documentation; Efficient markets; Environmental performance; Green products; Knowledge; Labeling; Labels; Licenses; Manufacturing; Marking; Ontology; Product safety; Query languages; Software; Subject specialists; Eco-labeling; SWRL; Knowledge base; OWL; Ontology engineering; Decision support
• ISSN: 0263-5577; 1758-5783
• DOI: 10.1108/IMDS-09-2016-0405

Purpose With the rising concern of safety, health and environmental performance, eco-labeled product and service are becoming more and more popular. However, the long and complex process of eco-labeling sometimes demotivates manufacturers and service providers to be certificated. The purpose of this paper is to propose a decision support platform aiming at further improvement and acceleration of the eco-labeling process in order to democratize a broader application and certification of eco-labels, also to consolidate the credibility and validity of eco-labels. Design/methodology/approach This decision support platform is based on a comprehensive knowledge base composed of various domain ontologies that are constructed according to an official eco-label criteria documentation. Findings Through standard Resource Description Framework and Web Ontology Language ontology query interface, the assets of the decision support platform will stimulate domain knowledge sharing and can be applied into other applications. A case study of laundry detergent eco-labeling process is also presented in this paper. Originality/value The authors present a reasoning methodology based on inference with Semantic Web Rule Language (SWRL) rules which allows decision making with explanation.