SGER: Mapping Nanotechnology Development Based on the ISI Literature-Citation Database

University Of Arizona, Tucson AZ

Investigators

Abstract

The proposed research plans to assess and map the development of NSE through the analysis of published papers indexed in the Thompson ISI literature-citation database. The effort will plan to conduct bibliographic analysis on NSE-related papers and citations. In addition the effort plans to analyze the impact of NSF funding on NSE research from the perspective of paper publication. Finally the effort plans to identify and visualize the themes covered by the NSE literature. Intellectual merit: The U.S. government has an explicit interest in monitoring global development of NSE both to ensure that adequate funding is being provided by sponsors to ensure U.S. preeminence in this field, and that industry investment is also kept competitive Monitoring global development means understanding the impact of the funding in the field, and examining as well the research and development status in industry and academic institutions. NSE patents and literatures are informative in representing NSE development. The University of Arizona Artificial Intelligence Lab has already achieved a successful research record in conducting analyses of NSE developments, developed several tools suitable for the proposed project, accumulated extensive implementation experience, and attained fruitful results in using citation analysis and other techniques to address the problem of understanding NSE development. Broader impact: Research results will be reported to the National Science Foundation for use in making decisions about future NSF programs and funding. Results will also be published in diverse media (e.g., journal papers, conference proceedings, and websites) to reach as broad an audience as possible in industry and academia. Finally, this project will provide numerous opportunities for training Ph.D. and Master's students in the areas of citation analysis, text mining, visualization, and statistical hypothesis testing.