From Warrant to Forecast: Rethinking Scholarly Classification with ‘Data Science' - Roy, Aditi; Ghosh, Saptarshi (Journal of Information and Knowledge, 2025)
This paper incorporates the Time Series Forecasting Method to Libraries as a means of choosing documents for users and to examine the growth pattern that supports Literary Warrant as well as User Warrant. Based on a study of the growth of literature in Data Science, the study suggests that a data-driven approach ensures libraries remain relevant and responsive in a constantly evolving information landscape. It argues that literary warrant serves as a useful principle for library services, and when applied, coupled with forecasting techniques, empowers librarians to anticipate user needs.