A scientometric analysis of health and population research in South Asia: focus on two research organizations

Asian University for Women, 4000, Chittagong, BANGLADESH; Antwerp University (UA), IBW, B-2000, Antwerpen, BELGIUM; KHBO (Association K.U.Leuven), Dept. of Industrial Sciences & Technology Zeedijk 101, B-8400, Oostende, BELGIUM; Dept. of Mathematics, K.U.Leuven, B-3000, Leuven (Heverlee), BELGIUM; Division of Publications & Information, Indian Council of Medical Research, INDIA
Malaysian Journal of Library and Information Science (Impact Factor: 0.38). 01/2011; 15:135-147.

ABSTRACT In this article we provide a scientometric comparison between two health and population research organizations, namely the International Centre for Diarrhoeal Disease Research in Bangladesh (ICDDR,B) and the National Institute of Cholera and Enteric Diseases (NICED) in India, during the period 1979-2008. We study these two institutes because they conduct similar research and because of their collaboration ties. Data are collected from the Web of Science (WoS) as well as from official records of these two organizations. The analysis presents the evolution of publication activities. Special attention is given to research impact through time series of the institutional h-and R-indices, as well as to the trend in yearly citations received. Types of publications, international collaboration with other countries, top scientists and most cited articles co-authored by scientists from these institutions are highlighted. It is observed that female scientists play a minor role in these two institutes.

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    ABSTRACT: Introducing and studying two types of time series, referred to as R1 and R2, we try to enrich the set of time series available for time dependent informetric studies. In a first part we focus on mathematical properties, while in a second part we check if these properties are visible in real data. This practical application uses data in the social sciences related to top Chinese universities. R1 sequences always increase over time, tending relatively fast to one, while R2 sequences have a decreasing tendency tending to zero in practical cases. They can best be used over relatively short periods of time. R1 sequences can be used to detect the rate with which cumulative data increase, while R2 sequences detect the relative rate of development.The article ends by pointing out that these time series can be used to compare innovative activities in firms. Clearly, this investigation is just a first attempt. More studies are needed, including comparisons with other related sequences.
    Journal of Informetrics 07/2013; 7(3):603–610. · 4.23 Impact Factor

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