Exploring the e-science knowledge base through co-citation analysis

E-Science is the sciensce of this age; it is realized thorough collaborative scientific enquiry which requires utilization of non-trivial amounts of computing resources and massive data sets. In this paper we explore the e-Science knowledge base through co-citation analysis of extant literature. Our objective is to use the knowledge domain visualization software CiteSpace to identifying the turning point articles and authors. In other words, our analysis is not solely based on tabulating the frequency of co-cited articles and authors, but the identification of landmark articles and authors irrespective of their co-citation count. The dataset for this analysis is downloaded from the ISI Web of Science and includes approx. 1000 articles. It is expected that this paper will be an important source of reference for academics and researchers working in the area of e-Science and its three technology enablers - grid computing, desktop grids and cloud computing.