2005-09-01Konferenzveröffentlichung DOI: 10.18452/9232
Automatic Data Fusion with HumMer
Mathematisch-Naturwissenschaftliche Fakultät II
Heterogeneous and dirty data is abundant. It is stored under different, often opaque schemata, it represents identical real-world objects multiple times, causing duplicates, and it has missing values and conflicting values. The Humboldt Merger (HumMer) is a tool that allows ad-hoc, declarative fusion of such data using a simple extension to SQL. Guided by a query against multiple tables, HumMer proceeds in three fully automated steps: First, instance-based schema matching bridges schematic heterogeneity of the tables by aligning corresponding attributes. Next, duplicate detection techniques find multiple representations of identical real-world objects. Finally, data fusion and conflict resolution merges duplicates into a single, consistent, and clean representation.
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