The rapid growth of distributed data at enterprises and on the WWW has fueled significant interest in building data integration systems. Such a system provides users with a uniform query interface (called mediated schema) to a multitude of data sources, thus freeing them from manually querying each individual source. To address some problems in the MOBS (Mass Collaboration to Build Systems) project at the University of Illinois, we develop solutions that learn from the multitude of users in the integration environment to improve the accuracy of integration tools. The improved accuracy in turn can significantly reduce the workload of the system builder. In developing MOBS we address the following key challenges: (i) obtaining user participation, (ii) learning from user participation, and (iii) combining user answers.