Rule-based ontological knowledge base for monitoring partners across supply networks

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This study demonstrates how ontology combined with semantic rules can be used for searching complete business partners in a supply network. Rather than being fully self-sufficient, individual enterprises are often part of a supply chain. Involving partners and understanding the importance of their activities is essential for enterprise agility. The question is how far-reaching and in what capacity a supply network is needed. Partner tracing becomes more difficult if search tasks involve potential partners or conforms to future production planning. This study utilized Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) technologies to develop supply network ontology and a problem-solving ontology, respectively. The three objectives of the study are creating a conceptual knowledge model for describing supply partners and their relationships, developing semantic rules as problem-solving methods for partner tracing in response to research questions and gathering experimental facts for evaluating knowledge-intensive designs. An example in the solar power industry is used to explain the ontological knowledge design and its uses. The experiments in this study showed that ontological approaches can effectively manage intricate and dynamic partnerships among supply networks. This design is also scalable in both domain ontology and task ontology for solving more complex problems.

论文关键词:Supply chain,Business partners,Knowledge-based system,Ontology,Semantic rules

论文评审过程:Available online 7 July 2009.

论文官网地址:https://doi.org/10.1016/j.eswa.2009.06.097