Korea Institute of Science and Technology Information
Methods and Material: The PubMed database was used for retrieving data on ‘cancer biology.’ Articles were downloaded from the years 2000 to 2011. The articles were classified chronologically and transferred to a spreadsheet application for analysis of the data as per the objectives of the study. Statistical Method: To investigate the nature of growth of articles via exponential, linear, and logistics tests. Result: The year wise analysis of the growth of articles output shows that for the years 2000 to 2005 and later there is a sudden increase in output, during the years 2006 to 2007 and 2008 to 2011. The high productivity of articles during these years may be due to their significance in cancer biology literature, having received prominence in research. Conclusion: There is an obvious need for better compilations of statistics on numbers of publications in the years from 2000 to 2011 on various disciplines on a worldwide scale, for informed critical assessments of the amount of new knowledge contributed by these publications, and for enhancements and refinements of present Scientometric techniques (citation and publication counts), so that valid measures of knowledge growth may be obtained. Only then will Scientometrics be able to provide accurate, useful descriptions and predictions of knowledge growth.
Scientometric; Cancer biology; PubMed; Relative growth rate; Exponential trend
Journal of Information Science Theory and Practice