COVID-19 Knowledge Resource Categorization and Tracking: Conceptual Framework Study

Area of Science:

• Information Science
• Public Health Informatics
• Data Management

Background:

• The COVID-19 pandemic spurred extensive global research and information generation.
• A lack of structured organization for these diverse COVID-19 information resources hinders accessibility and utilization.
• Existing information technology efforts require a defined framework for categorization and workflow tracking.

Purpose of the Study:

• To develop a structured categorization system for COVID-19 information resources.
• To facilitate easy identification, tracking of information workflows, and contextual dashboard development.
• To provide a guide for organizing and managing global COVID-19 knowledge assets.

Main Methods:

• Action research methodology was employed, reviewing global COVID-19 initiatives from 2020.
• Data were collected and categorized into primary, secondary, and tertiary levels.
• Descriptive statistical analysis was used to develop a conceptual framework for resource organization.

Main Results:

• A three-level conceptual framework was developed to categorize COVID-19 information resources.
• The framework enables enriched metadata access and tracking of information workflows from tertiary to primary levels.
• Mapping of initiatives demonstrated clear pathways to firsthand data, research, and trials.

Conclusions:

• The proposed three-level structure offers a consistent method for organizing and managing COVID-19 knowledge resources.
• This framework serves as a roadmap for classifying current and future information assets.
• Implementation can lead to applications like interactive dashboards for contextual identification and tracking of interdependent resources.