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When integrating data from multiple sources, a key task that online communities often face is to match the schemas of the data sources. Today, such matching often incurs a huge workload that overwhelms the relatively small set of volunteer integrators. In such cases, community members may not even volunteer to be integrators, due to the high workload, and consequently no integration systems can be built. To address this problem, we propose to enlist the multitude of users in the community to help match the schemas, in a Web 2.0 fashion. We discuss the challenges of this approach and provide initial solutions. Finally, we describe an extensive set of experiments on both real-world and synthetic data that demonstrate the utility of the approach.