Aggregating Web Services with Active Invocation and Ensembles of String Distance Metrics

The adoption of standards for exchanging information across the web could present a new world of opportunities for data integration and aggregation systems, the deployment of which could be greatly simplified using Web Service protocols. Although Web Services simplify the discovery and access of information sources, the problem of semantic heterogeneity remains: how to find semantic correspondences within the data being integrated. In this paper, we propose OATS, a novel algorithm for schema matching that is specifically suited to Web Service data aggregation. We show how probing Web Services with a small set of related queries results in contextually similar data instances which greatly simplifies the matching process, and demonstrate that the use of an ensemble of string distance metrics in matching data instances performs better than individual metrics. We also propose a method for adaptively combining distance metrics, and evaluate OATS on a large number of real-world Web Service operations.