: This talk describes a research project exploring new ways for augmenting search using multiple types and sources of social information. Our goal is to allow searching for all object types such as documents, persons and tags, while also retrieving related objects of all types. To realize this goal, we implemented a social-search engine using a unified approach. In this approach, the search space is expanded to represent heterogeneous information objects that are interrelated by several relation types. Our novel solution is based on multifaceted search and it provides an efficient update mechanism for relations between objects, as well as efficient search over the heterogeneous data. We describe a social search engine positioned within a large enterprise, applied over social data gathered from several Web 2.0 applications. We conducted a large user study with over 600 people to evaluate the contribution of social data for search. Our results demonstrate the high precision of social sea...