ABSTRACT
With the developments in the cyberworld, where online data resources have become more common, accessible and available than before, the scope of scientometric research has grown exponentially in the last few years. A spectrum of data sources is now available at the disposal of researchers. Web of Science, Scopus, Google Scholar and SCImago are prominent and extensively used. Some recent additions have also appeared on the market. Data in these repositories is massive. Databases now store millions of data records and their capacity is increasing year by year, making scientometrics an effective tool for big data analysis. In view of the possibilities of the scientific indicators that can be developed from millions of records, scientometrics serves as an attractive method for researchers. The challenge for students, researchers and practitioners, however, is to choose appropriate data sources that meet the objectives of their research. In this chapter, major databases such as Web of Science, Scopus and Google Scholar are examined in detail for their uses, relevance, appropriateness and inadequacies. The reliability of data is also discussed. Databases alone are not the sources for scientometric research, as publication data can also be collected directly from the websites of journals. A major drawback of scientometrics is that it does not sufficiently tap into the rich source of descriptive data. This is vital for the study of the disciplines and subjects in the humanities and social sciences domain. The chapter shows the relatively untouched qualitative data in scientometrics and explains how it can be sourced from citation indexes and other sources for a more rigorous and in-depth analysis.
