Researcher community produces a vast of content on the Web. We assume that every researcher interest oneself in events, persons and findings of other related community members who share the same interest. Although research related archives give access to their content most of them lack on analytic services and adequate visualizations for this data. This work resides on our previous achievements[1,2,3,4] we made on semantically and Linked Data driven search and user interfaces for Research 2.0. We show how researchers can find and visually explore commonalities between each other within their interest domain, by introducing for this matter the user interface of "ResXplorer", and underlying search infrastructure operating over Linked Data Knowledge Base of research resources. We discuss and test most important components of "ResXplorer" relevant for detecting commonalities between researchers, closing up with conclusions and outlook for future work.