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引用次数: 12
摘要
实际上,任何公司都需要与他人合作来提高他们的绩效和生产力。本体可以提供一种促进公司之间协作的方法。它们有助于减少协作过程中可能发生的语法和语义冲突。数据仓库技术是可以在合作公司中使用的数据共享体系结构的重要候选。一些社区对领域本体的广泛采用促进了语义数据库源(SDB)的爆炸式增长,这些数据源成为构建语义数据仓库(SDW)的候选对象。这种情况促使我们深入形式化语义源的结构,以提出语义数据仓库SDW的自动构建。在本文中,我们首先提出了一个处理语义源的通用框架。其次,将通用ETL步骤合并到我们的框架中。我们的建议通过一个案例研究得到了验证,考虑到Oracle SDB,其中每个源都引用了Lehigh University Bench Mark的全局本体。
Generic Methodology for Semantic Data Warehouse Design: From Schema Definition to ETL
Actually, any company needs to collaborate with others to improve their performance and productivity. Ontologies can provide a way to promote collaboration between companies. They contribute on reducing the syntax and semantic conflicts that may occur during the collaboration process. Data warehouse technology is a serious candidate for data-sharing architecture that may be employed within the collaborating companies. The spectacular adoption of domain ontologies by several communities facilitates the explosion of semantic databases sources (SDB) that become candidate for building the semantic data warehouses (SDW). This situation motivates us to deeply formalize the structure of semantic sources in order to propose an automatic construction of a semantic data warehouse SDW. In this paper, we first proposed a generic framework for handling semantic sources. Secondly, the generic ETL steps are incorporated to our framework. Our proposal is validated through a case study, considering Oracle SDB, where each source references a global ontology of the Lehigh University Bench Mark.