Ai and Global Science and Technology Assessment in This Issue

the international intellectual landscape. For example , Figure 1 shows some results from a biblio-metric study that my colleagues and I conducted at the University of Arizona's AI Lab. 1 The study was based on academic nanotechnology papers published in the Thomson Science Citation In-dex's (SCI) Web of Sciences and the UK were the major countries publishing nanotechnology research. After 1991, several additional countries joined them. By 2003, China was the second most productive country. South Korea also showed rapid development after 2000. In four years, its output exceeded Italy, Rus-sia, and England to become the sixth most productive country in 2004. 2 S&T strength is the foundation of a nation's economic power, so an effective, automated means of continually assessing this strength is critical to understanding a country's economic status. Such assessments require investigations in several dimensions: Participants •. Who are the scientists and developers involved in R&D, and which institutions and companies ultimately benefi t from these activities? Processes •. What are the funding models/pro-grams, and how are the participants linked together and organized around research initiatives? Output •. What ideas, inventions, and innovations result, in which areas of technology and with what quality? Benefi ts •. What are the economic and military advantages obtained from participation in and outputs from technology development? Barriers •. Do any cultural or political factors hinder the effectiveness of a country's R&D in its quest to become a power in the global econ-omy? (For a discussion of recent US regulations and their potential to restrict global S&T, see the " Regulatory Restrictions on Global S&T " sidebar on p. 70.) Global S&T analytics addresses many such questions. AI, knowledge mapping, and content-analysis research contribute signifi cantly to the answers. In addition to analytics, global S&T assessment requires advances in several data collection and computational research areas, such as multilingual query and translation support, multimedia and unstructured data collection and management, and content analysis and visualization. These areas also benefi t from AI, knowledge mapping, and content-analysis research. For instance, Nano Mapper (http://nanomapper. eller.arizona.edu) is a knowledge mapping system that integrates the analysis of nanotechnology patents and grants into a Web-based platform. The Nano Mapper system contains nanotechnology-related patents from the US, European, and Jap-anese patent offi ces as well as information from the US National Science Foundation (NSF) grant documents. It provides simple search functional-ities and a set of analysis and visualization …