Enrollment End Date
Created byRavichandra I K Rao
The objective of the course is to impart in-depth knowledge on Scientometrics; it includes scope and definition, computational aspects of certain parameters and indicators. Another objective of the course is to instil skills in learners that would enable them to collect and analyse Scientometrics data; finally, this course will help you to read and understand the scientific literature in the field of Scientometrics.
The course elaborates on methodology and techniques involved in the analysis of Scientometric data. The course is designed for the students of library and information science as well as for professionals working in library and information centres. However, anyone who wishes to learn about Scientometrics is welcome to join the course.
The learner should have basic knowledge of computers, acquaintance with traditional libraries using manual processes as well as computerized library operations and services offered by both types of libraries.
The course is designed for the students of library and information science as well as for professionals working in library and information centres. Other learners interested in digital libraries may also take up the course.
After successful completion of the course, you will gain in-depth knowledge about Scientometrics. You will develop skills to collect, analyse and evaluate Scientometric data. You will be able to read and understand Scientometric literature; further, you will able to carry out research in Scientometrics.
The course consists of 10 parts and is deliverable in a time span of 10 weeks as per the course layout is given below.
Week 1: Introduction to Scientometrics
Librametry, Bibliometrics, Scientometrics, Informetrics and Webometrics: Historical Development
Data Sources and Software Tools for Bibliometric Studies
Week 2: Classical Laws of Bibliometrics
Classical Law of Bibliometrics
Bradford Distributions: an Overview
Week 3: Use Studies
Library Use Studies
Analysis of Circulation data, including the quantitative methods to evaluate a collection
Week 4: Obsolescence of Literature
Obsolescence factor: Definition and Calculation
Week 5: Growth of Literature
Growth of Literature
Week 6: Scientometric Indicators
Week 7: Citation Analysis and Collaboration in Science
Collaboration in Science
Week 8: National Mapping and role of Scientometrics in Science Policy
National Mapping of Science
Scientometrics as a Policy and Strategic Tool
Week 9: Research Methodology
Basics of Research Methodology
Week 10: Testing of Hypothesis
Basics of Testing of Hypotheses
To access the content, please enroll in the course.
Course Syllabus & Schedule
Prof. I.K. Ravichandra Rao was working as Visiting Scientist at Centre for Knowledge Analytics and Ontology Engineering, PES Institute of Technology, Bangalore; formerly from Sept 13 to Dec 16;he was Head of the Indian Statistical Institute, Bangalore Centre from Oct 2002 to Sept 2007 and also he was Head of Documentation Research and Training Centre for more than fifteen years, from March 1996 to Nov 2010. He was retired from Indian Statistical Institute in December 2011. He was also the Editor of SRELS Journal of Information management for more than five years. At present, he is the Chief Editor of the COLLNET journal Scientometrics and Information Management.
He was awarded the Fellowship of the Society of Information Science, New Delhi, in 1996 for his contribution to Information Science. Prof. Rao joined DRTC in 1970. Since then he is involved in teaching and research in applied statistics, (-- bibliometrics / informetrics and scientometrics), programming, library automation, information retrieval, information management and DBMS with special emphasis on bibliographical databases.
He worked as Visiting Professor at Limburgs University, Diepenbeek, Belgium in 1990, 2001 and also in 2007 and at Addis Ababa University in 1990. In Addis Ababa University, Prof. Rao was responsible for designing and implementing the curriculum in the area of bibliometrics & scientometrics, IT and its applications for the MS programme, sponsored by the IDRC for African Region. His research interests include growth and obsolescence of literature, library statistics, theories of bibliometrics, scientometrics and informetrics; Library automation information retrieval, information management, in addition to the development of software for library applications. Based on his research and teaching experience, he has authored three books (-- Quantitative Methods Library and Information Science, Library Automation (it has been translated into Portuguese language.) and Growth of Literature and Measures of Scientific Productivity: Scientometric Models.) All the three books have been recognized as textbooks for students at the post-graduate level in some of the Indian and foreign Universities. He has edited a number of seminar volumes both at the national and international levels and also was a Guest Editor for a few journals in Information field in India. He has more than sixty research papers to his credit and has reviewed a number of books and articles. Some of his major research findings are:
i) Success-breeds-success phenomenon explains the law of scientific productivity;
ii) Negative binomial model can appropriately be applied to explain the distribution of scientific papers as well as the library circulation data; Good fit of negative binomial distribution to the library circulation data may be found if the time gap between the current use and the last use of the documents (or by the users) is not very large;
iii) It is only those documents which are circulated/used are likely to be circulated/used again and again;
iv) It is only those users who borrow documents are likely to borrow documents again and again;
v) 80-20 rule confirms well to the library use data – 80% of the documents contribute only 20% of the total use of the collection and vice-versa;
vi) Higher the growth of the literature, faster the obsolescence of the literature (less the half-life of documents) and vice versa;
vii) The Bradford multiplier (n) is unlikely to be a constant;
viii) Exponential distribution does not necessarily always explain the growth of the literature; depending on the subjects, period covered, kind of data, one may have to choose a model –exponential, logistic, Gompertz, linear, etc.
He has travelled widely both in India and abroad in connection with professional activities.