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Building data warehouses based on mine-production geoontology

机译:根据矿山生产地貌学建立数据仓库

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摘要

We propose a new approach to decision support system based on conceptualized and systemized domain knowledge for reducing semantic heterogeneity and cognitive biases among multiple data resource and achieving spatial data integration, exchange & share of mine enterprises. Firstly, an architecture and design ideas for data warehouse are established with formalized geo-semantic knowledge. Then the hybrid geoontology model and a goal-driven modeling methods covering static knowledge, dynamic events and humans actors of mine production process is presented based on mining terms, concepts, entities and characteristics. Finally, algorithms and examples to automatically build multidimensional model have been given according to mapping rules between OWL and XML. It is tested that the proposed method has superior usability, could implement standardized and sharing multidimensional models of data warehouses and provide a new way for data integration and decision-making application from different business domains.
机译:我们提出了一种基于概念化和系统化领域知识的决策支持系统的新方法,以减少多种数据资源之间的语义异质性和认知偏差,并实现矿山企业的空间数据集成,交换和共享。首先,利用形式化的地理语义知识建立了数据仓库的体系结构和设计思想。然后根据采矿术语,概念,实体和特征,提出了混合地质学模型和目标驱动的建模方法,涵盖了采矿过程的静态知识,动态事件和人类行为者。最后,根据OWL和XML之间的映射规则,给出了自动构建多维模型的算法和示例。测试表明,该方法具有较高的可用性,可以实现标准化和共享的多维数据仓库模型,并为来自不同业务领域的数据集成和决策应用提供了新的途径。

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