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Measuring the Global Research Environment: Information Science Challenges for the 21st CenturyAnderson, Caryn; Bammer, Gabriele; Grove, Andrew (ASIST, 2005)“What does the global research environment look like?” This paper presents a summary look at the results of efforts to address this question using available indicators on global research production. It was surprising how little information is available, how difficult some of it is to access and how flawed the data are. The three most useful data sources were UNESCO (United Nations Educational, Scientific and Cultural Organization) Research and Development data (1996-2002), the Institute of Scientific Information publications listings for January 1998 through March 2003, and the World of Learning 2002 reference volume. The data showed that it is difficult to easily get a good overview of the global research situation from existing sources. Furthermore, inequalities between countries in research capacity are marked and challenging. Information science offers strategies for responding to both of these challenges. In both cases improvements are likely if access to information can be facilitated and the process of integrating information from different sources can be simplified, allowing transformation into effective action. The global research environment thus serves as a case study for the focus of this paper – the exploration of information science responses to challenges in the management, exchange and implementation of knowledge globally.
The Shift from Information Retrieval to Information SynthesisBlake, Catherine; Anderson, Caryn (2005)Grand challenges such as public health, security, genomics, environmental protection, education, and economics, are characterized by complexity, interdependence, globalization, and unpredictability. Although the unprecedented quantity of information surrounding these challenges can provide users with a new perspective on solutions, the data surrounding complex systems vary with respect to levels of structure and authority, and include vastly different contexts and vocabularies. To be successful in this domain we must extend our models of information science such that they operate successfully in environments where the quantity of relevant information far exceeds our human processing capacity. For example, the well-accepted precision and recall metrics break down when hundreds of thousands of documents are relevant. Solutions to grand challenges require that information scientists shift their focus from information retrieval towards information synthesis.