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World Digital Libraries
Year : 2023, Volume : 16, Issue : 2
First page : ( 135) Last page : ( 148)
Print ISSN : 0974-567X. Online ISSN : 0975-7597.
Article DOI : 10.18329/09757597/2023/16210

Technological Framework for Searching Journals from an Aggregated Database

Chaubey S.1,*, Dr Mathur K.2, Dr Taneja D.3

1Research Scholar, Dr B.R. Ambedkar University Delhi, School of Business, Public Policy and Social Entrepreneurship (SBPPSE), Delhi – 110006, (E): schaubey.20@stu.aud.ac.in

2Assistant Professor, Dr B.R. Ambedkar University Delhi, School of Business, Public Policy and Social Entrepreneurship (SBPPSE), Delhi – 110006, (E): kritika@aud.ac.in

3Director (IT), Dr B.R. Ambedkar University Delhi, Delhi – 110006, (E): dtaneja@aud.ac.in

*Corresponding author, schaubey.20@stu.aud.ac.in

Online Published on 20 January, 2024.

Abstract

The researchers are generally curious about the key indicators regarding the suitability of journals for the publication purposes. The information about the journals is available with multiple sources, therefore the researchers perform rigorous searches in multiple data sources and spend significant time and efforts to get the key indicators about journals such as ratings, impact factors, cite scores, present listing status, ranking, and so forth. The present article is dedicated towards discussion on technological framework to aid researchers by aggregating critical information about the journals at one place, thus, resulting in reducing search time and getting consolidated information. Data aggregation methodology is applied to aggregate the data from citation index databases to create a master index, and then a search engine is developed to perform the search the aggregated database. It is observed that the overall efficiency of journal search significantly increases when using the technological framework as compared to the usual method of searching repositories on individual websites.

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Keywords

Scopus, Web of Science, UGC CARE, ABDC, Scientific journal ranking, Aggregation of journals’ data.

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