BACKGROUND
Declaring the COVID-19 disease a global pandemic by the World Health Organization (WHO), it gained momentum as every day passed, and private and government sectors of different countries pushed funding towards research in various capacities. A great portion of efforts is devoted to information technology and service infrastructure development, including research to develop intelligent models and techniques for alerts, monitoring, early diagnosis, prevention, and other relevant services. As a result, tons of information resource have been created in the global space and are available for use. However, there is lack of a defined structure to organize these resources into categories or classes based on the nature as well the origin of data.
OBJECTIVE
This study aims to organize COVID-19 information resources into a well-defined structure to facilitate easy identification of a resource, tracing information workflows, and a guide for contextual dashboards design and development.
METHODS
A sequence of action research was performed that involve a review of COVID-19 efforts and initiatives on a global scale during the year 2020. Data is collected according to a defined structure of primary, secondary, and tertiary categories. Various descriptive statistical analysis techniques were employed to get insights of the data to help in developing a conceptual framework underlining the organization of resources and interactions among different resources.
RESULTS
In this paper, we present a three-level structure of resource categorization that provides a gateway to access the global initiatives with enriched metadata, assists users in tracing the workflow of tertiary, secondary, and primary resources with relationships among various fragments of information. The results comprise mapping initiatives at the tertiary level to secondary and then to the primary level to reach the firsthand resource of data, research, and trials.
CONCLUSIONS
Adopting the proposed three-level structure enables a consistent organization and management of existing COVID-19 knowledge resources and provides a roadmap for classifying the futuristic resources. This study is one of the earliest studies to introduce an organized structure and demonstrate the placement of COVID-19 resources at the right place. By implementing the proposed framework according to the stated guidelines, this study facilitates the development of applications such as interactive dashboards to facilitate the contextual identification and tracking of interdependent COVID-19 information resources.