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This paper describes a collaborative approach to ontology development for data qualification for life cycle assessment by taking into consideration the Life Cycle Inventory (LCI) and Data Quality Indicator (DQI). The developed ontology is integrated with rule-based knowledge, to provide userdefined policies for LCI based on DQI. An ontology application management framework is developed to provide a collaborative environment for knowledge engineers and domain experts to define the knowledge explication and recommendation rules based on usage scenario. LCI data from agricultural domain is collected, and mapped to the knowledge base. To demonstrate the advantage of transformed rules, a scenario-based recommender system is built on top of the ontology, and carries out data quality measurement.