Mining of Data in Real Time to build an Interactive Research Analytics Dashboard
DOI:
https://doi.org/10.17821/srels/2024/v61i4/171468Keywords:
Bibliographic Data Mining, Data Analytics, Data Mining, Research ProductivityAbstract
The paper discusses the process of building a web-based interactive platform to assess the research productivity of the individual faculty of an institution. The application harvests the bibliographic data of researchers’ publications from the Scopus database and visualises it in real-time. The open-source environment R with different packages like the shiny, shiny dashboard for building web apps and dashboard designing; httr for data harvesting through API, jsonlite for parsing JSON data, tm for text mining, wordcloud for visualising wordcloud, textstem for lemmatization of text strings, dplyr for data manipulation, etc. were used. The data was harvested at the backend using Scopus API. The user interface of the application’s front end is the default design of the shiny dashboard, with some limited customization using CSS. The system tracks and visualizes the research productivity of the faculty. The application provides the total number of publications, citations, H Index, open access information, number of publications in open access, and closed access, in an assessment year rather than a calendar year, source-wise differentiation of publications, annual distribution of publications, common themes of the research, etc.
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