Towards an Interoperable Decision Support Platform for Eco-labeling Process

Xu, D.; Karray, Hedi; Archimède, Bernard

doi:10.1007/978-3-319-30957-6_19

Cited by 6 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This modular design has advantage in terms of reuse and change of the ontology. Since the descriptive part of the ontology does not change very much but the criterion or the “rules” are altered from time to time, once the “entities” and “rules” are separately managed, we can identify one criterion module rapidly and do the updates without disturbing the other modules (Da et al , 2016).…”

Section: Infrastructure Implementation and Case Studymentioning

confidence: 99%

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

Xu¹,

Karray²,

Archimède³

2017

IMDS

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Infrastructure Implementation and Case Studymentioning

confidence: 99%