Real-Time Bibliometrics: Dimensions as a Resource for Analyzing Aspects of COVID-19

Area of Science:

• Bibliometrics
• Scholarly Communication
• Data Science

Background:

• Dimensions platform facilitates research object analysis through linked data and machine learning.
• Existing features support traditional analytical use cases for researchers.
• The COVID-19 pandemic revealed a need for analyzing scholarly trends in real-time.

Purpose of the Study:

• To introduce and illustrate the potential of real-time bibliometrics.
• To discuss emerging capabilities of the Dimensions platform for time-sensitive analysis.
• To present basic analyses demonstrating real-time bibliometric applications.

Main Methods:

• Utilizing the Dimensions platform with features like full-text search and daily data updates.
• Incorporating a broad range of scholarly objects, including pre-prints.
• Leveraging enhanced data fields for in-depth analysis.

Main Results:

• Demonstrated the feasibility of real-time bibliometric analysis.
• Presented three illustrative examples of emerging analytical capabilities.
• Highlighted the platform's capacity for timely scholarship trend analysis.

Conclusions:

• The Dimensions platform's features enable a new style of real-time bibliometric analysis.
• Real-time bibliometrics offers valuable insights into emerging scholarly trends.
• The platform's capabilities are crucial for understanding scholarship during crises.