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Ontologies and summarizability in OLAP

机译:OLAP中的本体和可概括性

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Summarizability, i.e. the correctness of aggregation operations, is essential for OLAP analysis. Summarizability has commonly been studied in the context of dimension hierarchies, but the role of semantics of measure attributes and aggregation functions (sum, avg, min, max, count) has received less research interest. In this paper, we focus on the relationship between measure and dimension attributes and its effect on summarizability. We define the concept of measure-dimension consistency and show how it can be concluded from an OLAP ontology constructed by using Semantic Web technologies. Measure-dimension consistency can be used both for OLAP cube construction and queries and it is also very useful when integrating data over the internet.
机译:可汇总性(即聚合操作的正确性)对于OLAP分析至关重要。可汇总性通常是在维层次结构的上下文中进行研究的,但是度量属性和聚合函数(求和,平均,最小值,最大值,计数)的语义作用受到了较少的研究兴趣。在本文中,我们关注度量和维度属性之间的关系及其对可汇总性的影响。我们定义度量维一致性的概念,并说明如何从使用语义Web技术构建的OLAP本体中得出结论。度量维一致性可用于OLAP多维数据集构建和查询,并且在通过Internet集成数据时也非常有用。

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