This an article that summarizes the presentation that was done in Madrid 2009. In recent years we have witnessed tremendous interest and substantial economic exploitation of search technologies, both at web and enterprise scale. However, the representation of user queries and resource content in existing search appliances is still almost exclusively achieved by simple syntax‐based descriptions of the resource content and the information need such as in the predominant keyword-centric paradigm (i.e. keyword queries matched against bag‐of‐words document representation). On the other hand, recent advances in the field of semantic technologies have resulted in tools and standards that allow for the articulation of domain knowledge in a formal manner at a high level of expressivity. At the same time, semantic repositories and reasoning engines have only now advanced to a state where querying and processing of this knowledge can scale to realistic IR scenarios. In parallel to these developments, in the past years we have also seen the emergence of important results in adapting ideas from IR to the problem of search in RDF/OWL data, folksonomies, microformat collections or semantically tagged natural text. Common to these scenarios is that the search is focused not on a document collection, but on metadata (which may be possibly linked to or embedded in textual information). Search and ranking in metadata stores is another key topic addressed by the workshop. As such, semantic technologies are now in a state to provide significant contributions to IR problems. In this context, several challenges arise for Semantic Search systems. These include, among others: How can semantic technologies be exploited to capture the information need of the user? How can the information need of the user be translated to expressive formal queries without enforcing the user to be capable of handling the difficult query syntax? How can expressive resource descriptions be extracted (acquired) from documents (users)? How can expressive resource descriptions be stored and queried efficiently on a large scale? How can vague information needs and incomplete resource descriptions be handled? How can semantic search systems be evaluated and compared with standard IR systems?