SDD-matcher: a semantic-driven data matching framework

A generic semantic-driven data matching framework (SDD-Matcher) has been designed and developed for matching data objects across organizations. It contains matching algorithms at three different levels: string, lexical and graph. The level of graph is also called ontological or conceptual level. Those matching algorithms are the basic building blocks of an SDDMatcher matching strategy, each of which contains at least a graph matching algorithm. In principle, we can freely choose the matching algorithms when composing a matching strategy. In this article, we focus on a full engineering cycle of SDDMatcher, which includes five phases – framework design, use case design, implementation, evaluation and strategy enhancement. Lexon Matching Strategy (LexMA) and Controlled, Fully Automated, Ontology-based Matching Strategy (C-FOAM) are revised and refined in SDD-Matcher. We will also illustrate a new SDD-Matcher strategy – Ontology Graph Measuring Strategy (OntoGraM) – in this paper. Semantic decision tables are used as a means to easily configure the matching strategies. In the phases of use case design, evaluation and strategy enhancement, we use real case data from a large enterprise in the fields of human resource management (HRM) and eLearning/training.