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    <dc:date>2026-10-10T09:33:55Z</dc:date>
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  <item rdf:about="http://nopr.niscpr.res.in/handle/123456789/60549">
    <title>Immersive services in libraries: perspectives and views of library professionals</title>
    <link>http://nopr.niscpr.res.in/handle/123456789/60549</link>
    <description>Title: Immersive services in libraries: perspectives and views of library professionals
Authors: Roy, Samrat Guha; Kanjilal, Uma
Abstract: The paper aims to determine whether AR and VR library services are useful and, if so, what are the associated opportunities and challenges. Based on the literature review, 40 libraries that have implemented augmented virtual reality services were identified. An online survey of library professionals belonging to the 40 identified libraries was conducted. Sixty-nine percent of libraries use HTC Vive as their preferred VR headset device. Further, 54 percent of the respondents stated the circulation of VR devices as a new service. Findings show that libraries are offering new services such as 3D Model Gallery, 3D Scanning, 3D Printing, and Data Visualization. SWOT analysis of immersive services in libraries identified VR content archiving, copyrighting of 3D content, and constructing metadata schemas for virtual content as the challenging areas that need further research. The study will be useful to library professionals who plan to introduce or experiment with augmented virtual reality services.
Page(s): 183-190</description>
    <dc:date>2022-09-01T00:00:00Z</dc:date>
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  <item rdf:about="http://nopr.niscpr.res.in/handle/123456789/60548">
    <title>Using text analysis to study doctoral-level library and information science research trends in India</title>
    <link>http://nopr.niscpr.res.in/handle/123456789/60548</link>
    <description>Title: Using text analysis to study doctoral-level library and information science research trends in India
Authors: Kumar, Vinit; Thaku, Khusbu
Abstract: This study attempts to identify research trends in doctoral-level library and information science research in India. The&#xD;
study uses topic modelling with Latent Dirichlet Allocation to identify research trends by collecting relevant sections from&#xD;
the full-text of theses awarded in the last ten years by Indian universities in the discipline of library and information science.&#xD;
The topic modelling results show that the entire corpus can be classified into ten topics, including information&#xD;
communication technology and its application in libraries. The topic-wise trends indicate that ‘ICT and its application&#xD;
in libraries’ are still the prime themes of choice among doctoral-level research in Indian LIS schools, followed by studies&#xD;
on ‘Information seeking behaviour’. The growth-wise trend analysis suggests the decline in the interest in&#xD;
‘Bibliometrics/Scientometrics’ and ‘Webometrics/Website evaluation studies’. The findings of the study will be of help to&#xD;
academics studying the development of LIS research, as well as aspiring doctoral-level scholars who are to identify a topic&#xD;
for their research work.
Page(s): 191-202</description>
    <dc:date>2022-09-01T00:00:00Z</dc:date>
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  <item rdf:about="http://nopr.niscpr.res.in/handle/123456789/60547">
    <title>Reinventing acquisition process of print books in university libraries</title>
    <link>http://nopr.niscpr.res.in/handle/123456789/60547</link>
    <description>Title: Reinventing acquisition process of print books in university libraries
Authors: Kumar, Naresh
Page(s): 203-207</description>
    <dc:date>2022-09-01T00:00:00Z</dc:date>
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  <item rdf:about="http://nopr.niscpr.res.in/handle/123456789/60546">
    <title>A survey and classification of publicly available COVID-19 datasets</title>
    <link>http://nopr.niscpr.res.in/handle/123456789/60546</link>
    <description>Title: A survey and classification of publicly available COVID-19 datasets
Authors: Dutta, Biswanath; Das, Puranjani; Mitra, Sushmita
Abstract: The current study curates a list of authentic and open-access sources of alphanumeric COVID-19 pandemic data. We have gathered 74 datasets from 42 sources, including sources from 18 countries. The datasets are searched through the Kaggle and GitHub repositories besides Google, providing a representation of varieties of pandemic-related datasets. The datasets are categorized according to their sources- primary and secondary, and according to their geographical distribution. While analyzing the dataset, we came across some classes in which the datasets can be categorized. We present the categorization in the form of taxonomy and highlight the present COVID-19 data collection and use challenges. The study will help researchers and data curators in the identification and classification of pandemic data.
Page(s): 208-220</description>
    <dc:date>2022-09-01T00:00:00Z</dc:date>
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