Rajesh Das

Bio: Rajesh Das is an academic researcher from University of Burdwan. The author has contributed to research in topics: Metadata & Entropy (arrow of time). The author has an hindex of 2, co-authored 10 publications receiving 7 citations.

Integration of Domain-Specific Metadata Schema for Cultural Heritage Resources to DSpace: A Prototype Design

Abstract: This article highlights the practical experiences about the implementation of LIDO metadata schema in DSpace for managing museum and cultural resources. LIDO is a domain specific metadata schema fo...

Website of High Courts in India: a Webometric Study

Abstract: Website is an electronic information wall of an organization. This paper highlights the various web impact factors, scores and ranking of the websites of high courts in India. The study also found the other important outputs like page size of the websites, access speed score of websites, load time and daily page use time of the website have been reflected in this study and give idea about quality of the websites. The webometric tools like Alexa, Google page rank, Neil Patel SEO analysis, Google search engine and SocScibot4 are used for data collection and designing In-link, Out-link and mapping visualization of this sites.

Evaluation of Online Learning Repositories: A Comparative Study

Abstract: Many online learning repositories available around the world This paper provides a comparative analysis among selected online learning repositories (eGyankosh, ePG pathshala, MIT resources and Sodhganga) for learning resources The comparative study is based on some analytical parameters, like generic, content related, retrieval related, post processing, interface related, etc The collected data have been analysed on the basis of parameters The results have been displayed through different types of diagrams like multiple bar diagrams, pie diagram, etc It was found that none of the selected online learning repositories achieved the full score And also found that Sodhganga ranked the highest position among them

Visualizing the Knowledge Structure and Evolution of Entropy: A Scientometric Analysis

Abstract: The purpose of this article is to map the state-of-art of entropy, a knowledge domain which has drawn a great interest of researchers from a variety of academic fields in modern times. The journal Entropy, which focuses completely on entropy and is therefore regarded as the most prominent journal, has been purposefully chosen for this study in order to examine the intellectual structure of the field. Data from the Web of Science database for the years 2008 through 2021 were gathered. Scientometric indicators, literature growth, co-authorship, co-citation, keyword co-occurrences, co-word, citation, and bibliographic coupling, are studied using VOS Viewer. Highly cited papers, most prolific authors, countries and institutions are also identified. The results of the study admit that the linear growth trend of entropy articles has increased over the course of the investigation. Highest number of the publications were contributed from China, and the institution that contributed the most articles was the Chinese Academy of Sciences. A cluster analysis of the keywords shows that the research hotspots are primarily focused on “entropy,” with the highest frequency and link strength. The high density of the co-words of “entropy,” “information,” “model” and “Shannon entropy” has also proved them to be the most mature and centralized area of entropy field.

Perspectives of the Teachers on Challenges and Possibilities to Online System of Education amid COVID-19 Outbreak in Balochistan, Pakistan

Abstract: The study investigates the issues of access, quality, and other major challenges to the online system of education for students in Balochistan during this pandemic of Covid-19. Using the mixed-method design, 100 participants from schools and 7 curriculum experts responded to the survey and the interview questions. Survey results suggested that majority of the schools have enough digital devices, and teachers, to some extent, have skills to use technology in teaching, but limited electricity, funds, weak internet connections, and teacher training were some of the major challenges for them. In interviews, the participants showed disappointment in terms of responsiveness of the curriculum because the textbooks have manifold deficiencies in responding to online education. Considering these deficiencies, proposals were suggested to cope with the existing situation. The findings of the study call for the need on the part of the academia, educational stakeholders, and elected representatives to start joint efforts with national and international donor agencies, technology benefactors and telecommunication operators in developing digital infrastructure to provide students with access to education, quality, and lifelong learning through various pathways. The findings can be generalized to other underdeveloped regions both within and across the country, as the public schools are confronting the same issues and the online system of education has not yet been initiated.

Research Contribution to the Progress of Digital Learning in India

Abstract: In the era of Information and Communication Technology (ICT), E-learning and digitalization of education are considered to deliver a wide array of benefits that enhance knowledge and performance of the teaching and learning process in higher education institutes, leading to improved learning and teaching efficiency. Integration of digital technologies in education reduces barriers to access education and provides an opportunity for all. In this connection, the Government of India has taken several initiatives to integrate ICT in education, such as online teaching-learning programs through various platforms and organizations. While digital learning breaks several barriers of access to education for all, there are several limitations and issues to access digital education such as poor internet connectivity and bandwidth, lack of digital infrastructure, cost implications, training and development, and unfavorable study environment to address. It is in this regard, to better understand the state of digital education in India, the state of knowledge of research over the years, particularly the implications and impacts of digital education in India, is essential. In this regard, the aim of the study is to know the trends and progress of research in digital education in India. The bibliometric analysis of digital education research in India provides a better understanding of the trends and state of the art of research both for researchers and practitioners. In doing so, authors conducted a bibliometric analysis of digital education research in India terms year-wise and journal-wise publication output, productive authors, country-wise contribution, subject area-wise and funding sponsor-wise publication output, keyword and citation analysis. The study was conducted using the online Scopus database of the documents published on digital education till 2020. The study result shows that the progress of digital education research in India has increased over the years the research output published in top-tier journals was limited. Authors who have been affiliated to Indian universities contributed the most. Major research themes were E-learning, distance education, digital literacy, medical education, mobile learning, digital India, simulation, virtual labs, MOOCS, and COVID-19 pandemic.

Evaluation of Usability on Dataverse in Repositori Ilmiah Nasional (RIN) at the Indonesian Institute of Sciences

Abstract: Repositori Ilmiah Nasional/RIN (The National Scientific Repository) is a means to share, preserve, explore and analyze research data, developed by the Center for Scientific Data and Documentation-Indonesian Institute of Sciences (PDDILIPI). This study aimed to evaluate RIN at LIPI by using Usability with heuristic evaluation. The method used was descriptive with a quantitative approach. The technique of collecting data used a questionnaire as a research instrument; the population of this study was researchers at the LIPI. Determination of the sample was taken using the Solvin formula, obtained a sample of 17 respondents. The results showed that there were 7 (seven) variables that were in the Agree category including Visibility Status, Match Between System and The Real World, User Control and Freedom, Consistency and Standards, Prevention Error System, Recognition Rather Than Recall, Aesthetic Design. Then 2 (two) in the category of Strongly Agree including Flexibility and Efficiency of Use, and Help and Documentation. Finally, there was one variable that fell into the Neutral category, Recovery and System. The usability level of RIN LIPI dataverse website was 75.44% which was in the Agree/High category. Keywords—usability, dataverse, Repositori Ilmiah Nasional (RIN), PDDI-LIPI, evaluation

Analysing and Examining Taxonomy and Folksonomy Terms in the Hybrid Subject Device using Machine Learning Techniques

Abstract: The information retrieval system contains either a list of subject terms (taxonomy) or a list of collaborative tags (folksonomy) or both. The taxonomy and folksonomy come together as called hybrid subject devices. The main purpose of this paper is to apply machine learning techniques in the dataset from the library domain like others and analyse a large quantity of data for critical problems with accuracy. This research reveals to perform EDA (Exploratory data analysis), prediction analysis, and similarity measurement between folksonomy and taxonomy terms with new emerging technologies. Data science deals with big data that means unstructured data, messy data, a large volume of data. The size is of a large amount of data in terms of GB, TB. Machine learning tools manage this type of data. Usually, the Excel, or other spreadsheets package could not manage the file size in GB or TB, and that’s why ML tools, and techniques are applied. At present, the library science domain also contains a large amount of data like 20/30 years of circulation data or subject descriptors, collaborative tags etc. Library professionals can apply machine learning tools for analysing this kind of data in the library domain. In this paper, the authors have introduced the applications of tools and techniques in the library domain and they have tested with 2642 taxonomy and folksonomy terms. This research work includes – EDA, prediction analysis, and similarity measurement of a folksonomy and taxonomy dataset. In the EDA part, the research work has performed a lot of analysis that includes frequency of LCSH (Library of Congress Subject Heading - taxonomy) terms, pair plots, joint plots, and heat map of LCSH and folksonomy terms. The logistic regression (LR) model for prediction analysis has been used in the folksonomy and taxonomy dataset. These 2642 terms of folksonomy and taxonomy both terms are taken as data for this research work. The EDA has been performed with the attributes in the dataset. The accuracy value of logistic regression (f1- score) is 0.37 at the training percentage of 69. The percentage of similarity between LCSH terms and folksonomy terms is 30 per cent (0.30151134), and the angle between these two vectors is 27 degrees. The novelty of this research work is that library data has been analysed using machine learning techniques the ever used before.