Science Communication: Research Productivity and Data Analytics using Open Source Software

By Prof. Nabi Hasan, Prof. Mohit Garg | IIT Delhi

Learners enrolled: 2584 | Exam registration: 515

ABOUT THE COURSE:
Scientists, researchers, academicians and students are involved in extensive research and publication work to produce new knowledge or a new interpretation of the existing knowledge base. The quality and quantity of this knowledge is popularly evaluated by using various quantitative metrics known as mapping tools and technologies. Many organisations, policy makers, and government agencies regularly conduct such analyses for various reasons, like ranking, funding, evaluations, project awards, rewards, etc. The evaluation process includes extracting large-scale research data, pre-processing and analysing. It requires both mathematical and computer skills to do effective analysis and presentation. This course has been developed, keeping all these parameters in mind, targeting people working or interested in the areas of Mapping Science/Scientometrics/Humanities & Social Sciences/Library & Information Science, Information Systems & Services professionals and the practitioners who are involved and aiming to do so such analysis. The course will introduce the concepts of various assessment metrics of research output, data extraction, pre-processing, different visualisation tools, ethics of analysis, software for extraction, refining and analysis of data, etc.

The course also includes various case studies on quantitative assessment of Institutions, Authors, Journals, Domains, and Countries. Prior knowledge of mathematics, statistics, or programming is optional to take advantage of the contents of the course as it starts with the basics and helps understand the advanced concepts with easily understandable day-to-day examples. Some of the practical aspects of each concept covered in the course will be delivered in the RStudio. Other software like VOSviewer, Citespace, etc., will also be covered.

After successfully completing the course, the learners will be able to understand the concept as above. They will also be able to conduct and publish the assessment studies in reputed journals, conferences or as research reports or manuscripts in any other form. The course aims to give learners the skills necessary to utilise open-source environments like R to evaluate and map the scientific knowledge generated by researchers.

INTENDED AUDIENCE: Faculty, Researchers, Post Graduate Students, Administrators, Policy Makers, Information Professionals, Library Science Professionals, etc.

PREREQUISITES: Undergraduate in any discipline

INDUSTRY SUPPORT: CFTIs/HEIs/Universities R&D organizations Ranking & Accreditation Agencies/Customers Publishing Industry Policy-making and evaluation organizations Library and Information Centres & Departments

Summary

Course Status :	Ongoing
Course Type :	Elective
Duration :	12 weeks
Category :	Humanities and Social Sciences
Credit Points :	3
Level :	Postgraduate
Start Date :	22 Jan 2024
End Date :	12 Apr 2024
Enrollment Ends :	05 Feb 2024
Exam Registration Ends :	16 Feb 2024
Exam Date :	21 Apr 2024 IST

Note: This exam date is subjected to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1: Science Communication
I. Introduction to Science Communication,
II.Channels of Science Communication
III. Open Science and Open Access,
IV.Open Research Data and Open Peer Review ,

Week 2: Academic Visibility and Research Impact
I. Overview of Tools for Maximizing Academic Visibility and Impact of Research Output ,
II. Understanding Research Metrics: Author, Journal and Article Level Metrices

Week 3 : Data Sources and Extraction
I. Abstract and Citation Database: Scopus
II. Abstract and Citation Database: Web of Science
III. Health Science Database: PubMed,
IV. Free Academic Search Engine: Google Scholar ,

Week 4: Working with R: Installation of R and RStudio, Basic Operations, data types, etc.
I. Installation of R
II. Installation of RStudio
III.Object and Different types
IV. Vector and Data Frame
V. Lists, Matrices, Factor, Array
VI. Packages and Help

Week 5: Introduction and application of bibliometrics and laws of scientometrics in mapping of science communications
I. Science Communication and Different Metrices
II. Lotka's Law
III.Bradford's Law
IV.Zipf's Law

Week 6: Descriptive Analysis: Publication and Citation related metrics
I. Descriptive Analysis - I
II.Descriptive Analysis - II
III.Descriptive Analysis – III
IV.Analysis of Bradford and Lotka Law

Week 7: Science Mapping: Co-citation, bibliographic coupling, co-authorship, PageRank, etc.
I. Science Mapping - I
II.Science Mapping - II

Week 8: Data Visualization
I. Data visualization: an overview, history, and skills for researchers
II.Data visualization: types, tools, and technologies
III.Visualization of scientific research with VOSviewer and CiteSpace

Week 9: Text Mining: Topic Modelling of research productivity
I. Text Mining - Introduction
II.Regular Expression
III.Text Pre-processing
IV.Topic Modeling

Week 10: Best Practices in Academic Rankings in reference to Times Higher Education (THE), QS, Sanghai (ARWU) and National Institutional Ranking Framework (NIRF) Ranking

Week 11: Ethical Guidelines, Academic Integrity in Science Communication
I. Academic Integrity and Ethical Guidelines in Science Communication: Ensuring Credibility and Honesty
II. IPR/Copyright Issues and Practices in Print & Digital Environment
III. Predatory Publishing: issues, challenges, and the road ahead

Week 12: Case Studies
I. Case Study - I (Domain)
II. Case Study – II (Author)
III.Case Study – III (Journal & Institution)

Books and references

1.Andrés, A. (2009). Measuring academic research: How to undertake a bibliometric study. Elsevier.
2. Gingras, Y. (2016). Bibliometrics and research evaluation: Uses and abuses. MIT Press.
3. Ball, R. (2017). An introduction to bibliometrics: New development and trends. Chandos Publishing.
4. Cronin, B., & Sugimoto, C. R. (Eds.). (2014). Beyond bibliometrics: Harnessing multidimensional indicators of scholarly impact. MIT press.
5. Teetor, P. (2011). R Cookbook: Proven recipes for data analysis, statistics, and graphics. " O'Reilly Media, Inc.".
6. Ahmi, A. (2022). Bibliometric Analysis using R for Non-Coders: A practical handbook in conducting bibliometric analysis studies using Biblioshiny for Bibliometrix R package.
7. Tattersall, A. (Ed.). (2016). Altmetrics: A practical guide for librarians, researchers, and academics. Facet Publishing.

Instructor bio

Prof. Nabi Hasan

IIT Delhi

Dr. NABI HASAN is the Librarian & Head of the Central Library, Indian Institute of Technology Delhi. Earlier, he served as the University Librarian at Aligarh Muslim University. He is the First Norman E. Borlaug Fellow from India in Library Information Systems, trained at Cornell University, New York, USA. Dr. Hasan has been honoured with the Fellow of the Special Libraries Association Award 2022 (FSLA). He won the SLA Engineering Librarian of the Year Award 2021, the Bonnie Hilditch International Librarian Award 2018, the SLP-SLA Asian Fellow Award 2019, and the SLA Presidential Citation 2021. Dr. Hasan has been conferred with the Royal Society of Chemistry's Librarians' Choice Award 2019 and won the SLA Overall Best Poster Award 2020. He is the recipient of the Vice-Chancellor Appreciation Award 2003 HP Agriculture University Palampur, Appreciation from the Chairman, Board of Governors, IIT Delhi 2012, Appreciation from the Vice-Chancellor of the Aligarh Muslim University 2018, Appreciation Certificate from IEEE twice, Lifetime Achievement Award 2015, and SALIS-Dr. Harish Chandra-Sushila Chandra National Best Librarian Award on Oct. 14, 2022. Earlier, Dr. Hasan served as President of SLA Asia and the Academic & Education Community of the SLA-USA. Dr. Hasan has 17 Books and over 175 articles to his credit. He is the 2024 President of the SLA Engineering Community, served as Co-Chair of the Annual Conference Advisory Council 2022-23 (ACS) and is a Joint-Chair of the 2024 SLA Annual Conference. More recently, he was awarded the Outstanding Academic Librarian Award 2023, conferred on National Librarians Day 2023 by the Social Development Federation, India and the 2023 Elsevier Library Stellar Club Membership on successfully completing its certification program. He headed the National Resource Centre in Library and Information Sciences of the Ministry of Education, Govt. of India, under its ARPIT MOOCs Program 2019-21. More details about him are available at: https://web.iitd.ac.in/~hasan

Prof. Mohit Garg

Prof. Mohit Garg is working as an Assistant Librarian at Central Library, Indian Institute of Technology Delhi. Before joining the IIT Delhi, he worked as Assistant Librarian at Indira Gandhi National Tribal University (A Central University), Amarkantak, Madhya Pradesh. He has qualified for UGC-NET-JRF and has submitted Ph.D. from IGNOU, New Delhi. He holds B.Tech (IT) from GGSIPU, New Delhi, and MS-LIS from Indian Statistical Institute Bangalore. He is a two continuous term (2017-2021, 2021-2025) Standing Committee Member of the IFLA Indigenous Matter Section, Netherlands, and other international and national associations. He has published Research papers in Scopus Indexed, and UGC CARE Listed Journals. His areas of interest are the Application of ICT, Research Methodology, Information Retrieval, Data Science, and Machine learning.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.

The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).

Date and Time of Exams: 21 April 2024 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.

Registration url: Announcements will be made when the registration form is open for registrations.

The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.

Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Madras. It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team