Large amount of experts are key asset that universities hold. In order to increase people's awareness of experts and foster collaborative opportunities, it is necessary to help users to locate experts with required expertise. This paper proposes a methodology for ontology-based expertise locator, a Semantic Web application that integrates pieces of relevant expertise information from heterogeneous data sources. We present the integration processes and ranking algorithm based on voting technique. Tests on the prototype system demonstrate that our system provides better performance on MAP and precision.