Increased interactivity and improvements to the GigaScience database, GigaDB

Area of Science:

• Data science
• Bioinformatics
• Scientific data archiving

Background:

• The GigaScience Database (GigaDB) has experienced significant growth in data volume and types since its 2011 inception.
• Assessing user patterns and data metrics is crucial for adapting to evolving research needs.

Purpose of the Study:

• To evaluate the metrics and user patterns of GigaDB to identify key areas for improvement.
• To present an overview of current GigaDB practices, including biocurational roles and platform enhancements.
• To outline future directions for the GigaDB resource.

Main Methods:

• Analysis of GigaDB usage metrics and user interaction patterns.
• Review of current platform practices and biocurational workflows.
• Implementation of front-end developments and codebase enhancements.

Main Results:

• Significant improvements in user experience through enhanced interactivity and functionality.
• Overhauled platform codebase for improved stability and performance.
• Detailed insights into GigaDB dataset usage metrics.

Conclusions:

• The GigaDB platform has been successfully updated to meet current and future demands.
• Enhanced features and stability ensure a better user experience for researchers.
• Ongoing development will continue to support the GigaDB resource.