Schema matching is a critical problem for integrating heterogeneous information sources. Traditionally, the problem of matching multiple schemas has essentially relied on finding pairwise-attribute correspondences in isolation. In contrast, we propose a new matching paradigm, holistic schema matching, to match many schemas at the same time and find all matchings at once. By handling a set of schemas together, we can explore their context information that reflects the semantic correspondences among attributes. Such information is not available when schemas are matched only in pairs. As the realizations of holistic schema matching, we develop two alternative approaches: global evaluation and local evaluation. Global evaluation exhaustively assesses all possible "models," where a model expresses all attribute matchings. In particular, we propose the MGS framework for such global evaluation, building upon the hypothesis of the existence of a hidden schema model that probabilisti...