基于描述逻辑的CWM元数据冲突的检测和消解

Inconsistency Checking and Resolving of CWM Metadata Based on Description Logics

元数据内容的冲突能够对数据仓库系统的稳定性和可靠性造成极大影响。在基于公共仓库元模型(CWM)建立元数据的过程中,参与建立元数据的团体的不同经验以及描述数据的不同视角不可避免地会带来元数据的这些冲突。然而,CWM的图形化特点导致了它缺乏精确的语义,所以如何自动检测和消解这些冲突,至今没有得到很好的解决。首先提出了一种支持概念之上的同一性约束的描述逻辑,用来对CWM元模型和元数据进行描述,然后阐述了利用该描述逻辑形式化CWM元模型和元数据的方法,接着研究了利用描述逻辑的查询推理能力检测元数据冲突的方法,最后研究了通过在知识库中定义冲突消解规则,消解元数据冲突的方法。利用推理引擎RACER所进行的实验结果表明提出的方法是可行的。

The inconsistencies in metadata have remarkable influence on the stability and reliability of data warehouse system.During the metadata creation based on Common Warehouse Metamodel（CWM）,the different experiences and views of describing data of organizations involved in metadata creation bring metadata inconsistencies inevitably.However,detecting and resolving these inconsistencies in CWM metadata automatically is difficult because CWM metamodel and metadata are rendered to users by graphs,which lack precise semantics.In this paper,we researched how to check and resolve CWM metadata inconsistencies in terms of a logic belonging to Description Logics.First,how to formalize CWM metamodel and metadata by means of the presented Description Logic DLidwhich supports identification constraints on concepts was researched.Then the approach for checking metadata inconsistencies by query and reasoning mechanism of DLidwas researched.At last,the approach for resolving inconsistencies through defining inconsistency resolution rules in DLidknowledge base was proposed.The results of the experiments with reasoning engine RACER are encouraging.