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DECLARATIVE DATA MERGING WITH CONFLICT RESOLUTION

机译:与冲突解决的陈述数据合并

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Database integration is a growing and increasingly important field in both research and industry. Integration requires many steps from initial schema integration and schema mapping, to data scrubbing and cleansing, and finally to data merging. While much research has concentrated on the first steps performed at schema level, there are only few publications about actual, practical merging of the data in an integrated database or in a query against multiple databases. When merging data, especially data from autonomous sources, there is a large potential for decreasing the quality of the merged data, even below the level of the original sources. The main reasons for decreased quality are data conflicts among the sources. To address this problem, we define resolution functions merging conflicting data. We present several alternatives of merging relational data sources with common queries through grouping & aggregating and through partitioning & joining. The resulting queries use resolution functions and can be used to migrate data from multiple sources to a target database, or to define an integrating view on multiple sources. We describe and analyze the advantages of the different approaches, and describe our practical solution in the framework of a schema mapping and data transformation tool.
机译:数据库集成是研究和行业的一个日益增长,越来越重要的领域。集成需要从初始架构集成和模式映射到数据擦洗和清理的许多步骤,最后进行数据合并。虽然在架构级别执行的第一个步骤上集中了很多研究,但只有很少有关于集成数据库中数据的实际合并的出版物,或者在对针对多个数据库的查询中的数据。在合并数据,尤其是来自自主源的数据时,甚至低于原始源的水平,甚至可以减少合并数据的质量的大可能性。质量下降的主要原因是源之间的数据冲突。要解决此问题,我们定义了合并冲突数据的解析功能。我们通过分组和聚合以及通过分区和加入提供几种合并关系数据来源的替代方法。由此产生的查询使用分辨率函数,并且可用于将数据从多个源迁移到目标数据库,或者在多个源上定义积分视图。我们描述并分析了不同方法的优势,并描述了我们在模式映射和数据转换工具的框架中的实用解决方案。

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