Automatic direct and indirect schema mapping: Experiences and lessons learned

Abstract

Schema mapping produces a semantic correspondence between two schemas. Automating schema mapping is challenging. The existence of l:n (or n:l) and n:m mapping cardinalities makes the problem even harder. Recently, we have studied automated schema mapping techniques (using data frames and domain ontology snippets) that not only address the traditional 1:1 mapping problem, but also the harder l:n and n:m mapping problems. Experimental results show that the approach can achieve excellent precision and recall. In this paper, we share our experiences and lessons we have learned during our schema mapping studies.