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Based upon findings and results from our recent research we propose a generic frame-
work concept for researcher profiling with appliance to the areas of ”Science 2.0” and ”Research 2.0”. Intensive growth of users in social networks, such as Twitter generated a vast amount of information. It has been shown in many previous works that social networks users produce valuable content for profiling and recommendations. Our research focuses on identifying and locating experts for specific research area or topic. In our approach we apply semantic technologies like (RDF, SPARQL), common vocabularies (SIOC , FOAF, MOAT, Tag Ontology) and Linked Data (GeoNames , COLINDA).