Connecting Scientometrics: Dimensions as a Route to Broadening Context for Analyses

Area of Science:

• Bibliometrics and Scientometrics
• Data Science
• International Relations

Background:

• Cloud computing democratizes access to scientometric data and computational resources.
• Unique identifiers enable the integration of diverse datasets for comprehensive analysis.
• Practitioners can leverage enhanced data capabilities for informed decision-making.

Purpose of the Study:

• To explore the potential of cloud-based data infrastructures for scientometric analysis.
• To investigate international scientific collaboration patterns by integrating diverse data sources.
• To demonstrate the value of connecting scientometric data with broader world data.

Main Methods:

• Utilized Google BigQuery for data warehousing and analysis.
• Integrated data from Dimensions (scientometric data) and the World Bank (economic data).
• Focused on analyzing international collaboration between countries of varying economic classifications.

Main Results:

• Demonstrated the feasibility of connecting disparate datasets within a cloud environment.
• Provided insights into the structure of international scientific collaboration.
• Highlighted the potential for new discoveries by linking scientometric and economic data.

Conclusions:

• Cloud-based infrastructures significantly enhance the accessibility and utility of scientometric data.
• Integrating diverse datasets, such as those from Dimensions and the World Bank, offers a richer understanding of global research.
• This approach empowers policymakers and strategists with advanced tools for analyzing international scientific partnerships.