Journeying towards best practice data management in biodiversity genomics

Area of Science:

• Biodiversity Genomics
• Data Management
• Bioinformatics

Background:

• Increasing accessibility of large-scale biodiversity genomic datasets due to advances in sequencing technologies and cost reduction.
• Existing uncertainty within the research community regarding best practices for managing these complex datasets.
• Need for comprehensive data management guidance to minimize data loss, enhance reuse, and support Indigenous data sovereignty.

Purpose of the Study:

• To identify data management challenges across the biodiversity genomics research ecosystem.
• To provide realistic considerations, compromises, and actions for effective biodiversity genomic data management.
• To support researchers in embedding data management throughout the research lifecycle for maximized impact.

Main Methods:

• Development of four fictional personas representing diverse user experiences with data management.
• Utilizing these personas to analyze and highlight data management challenges.
• Launching the Biodiversity Genomics Data Management Hub as a resource repository.

Main Results:

• Identification of specific data management challenges faced by biodiversity genomics researchers.
• Demonstration of practical approaches and compromises for managing biodiversity genomic data.
• Establishment of the Biodiversity Genomics Data Management Hub with practical resources and guidance.

Conclusions:

• Comprehensive data management is essential for maximizing the impact of biodiversity genomic data.
• The developed personas and resources aim to guide researchers, especially those new to data management, towards best practices.
• The Biodiversity Genomics Data Management Hub serves as a valuable tool for the community, promoting data sharing and reuse.