Complementing Bibliometrics with Network Visualization to Support Scientific Spheres

作者
N. Singh
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摘要

Science evaluation in both quantitative and qualitative terms is imperative to ascertain the growth and trends in a knowledge domain, strengths and gaps in research, symbiotic collaboration opportunities at national and international level, and impact of research reflected in terms of quality and performance indicators, viz. h-index, impact factor, number of citations, etc. Bibliometrics and its alternatives including scientometrics, altmetrics, webometrics, and librametrics are being widely used as tools for exploring the growth and structure of scholarly communications in different forms and formats encompassing various disciplines. The Library and Information Science Professionals (LISPs) have experience and expertise in bibliographic data handling. Therefore, LISPs can actively execute bibliometric studies. However, the volume and complexity of datasets in science disciplines have grown so enormous that use of special tools has become essential for inferring from the data available in form of various units of analysis. Network visualization software is used as supplemental aid to support bibliometrics in an interactive mode. These software usually have text mining functionality to facilitate the construction and visualization of network maps based on the co-occurrence of key terms extracted from a body of scholarly communication, viz. co-authorship, co-occurrence of institutions, bibliographic coupling and co-citation links. This paper discusses as detailed below the need for scientific evaluation, application of bibliometrics in science evaluation, role of data/network visualization in complimenting bibliometrics and various network visualization software.

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