Managing, Analyzing and Sharing Research Data with Gen3 Data Commons

Area of Science:

• Biotechnology
• Bioinformatics
• Data Science

Background:

• Research communities require robust platforms for managing and sharing large datasets.
• Existing data platforms often lack standardization and interoperability.
• The need for cloud-based solutions to facilitate data commons creation is growing.

Purpose of the Study:

• To introduce Gen3, an open-source data platform for building data commons.
• To highlight Gen3's capabilities in data management, analysis, and sharing.
• To emphasize Gen3's role in fostering interoperability within research ecosystems.

Main Methods:

• Gen3 utilizes a data model to autogenerate a data portal for data exploration.
• It provides a separate portal for data submission into the data commons.
• Gen3 exposes FAIR APIs for programmatic data access.
• The platform is built on standards-based software services for interoperability.

Main Results:

• Gen3 has been successfully implemented to build over 30 data commons globally.
• The platform facilitates the creation of user-friendly data portals.
• FAIR APIs enable efficient and standardized data access.
• Gen3's architecture supports integration with other data platforms.

Conclusions:

• Gen3 offers a scalable and flexible solution for establishing data commons.
• The platform promotes data sharing and collaboration among research communities.
• Gen3's standards-based approach enhances data interoperability and future-proofing.