Application of semantic technology for social network analysis in the sciences

The use of electronic data is steadily gaining ground in the study of the social organization of scientific and research communities, decreasing the researcher's reliance on commercial databases of bibliographic entries, patents grants and other manually constructed records of scientific works. In our work we provide a methodological innovation based on semantic technology for dealing with heterogeneity in electronic data sources. We demonstrate the use of our electronic system for data collection and aggregation through a study of the Semantic Web research community. Using methods of network analysis, we confirm the effect of Structural Holes and provide novel explanations of scientific performance based on cognitive diversity in social networks.