In schema matching, even experts are human: Towards expert sourcing in schema matching

Abstract

Schema matching problems have been historically defined as a semi-automated task in which correspondences are generated by matching algorithms and subsequently validated by a single human expert. Emerging alternative models are based upon piecemeal human validation of algorithmic results and the usage of crowd based validation. We propose an alternative model in which human and algorithmic matchers are given more symmetric roles. Under this model, better insight into the respective strengths and weaknesses of human and algorithmic matchers is required. We present initial insights from a pilot study conducted and outline future work in this area.