The iPlant Collaborative: Cyberinfrastructure for Enabling Data to Discovery for the Life Sciences

Area of Science:

• Life Sciences
• Computational Biology
• Bioinformatics

Background:

• Life science research generates vast datasets requiring advanced computational resources.
• Distributed research teams face challenges in data management, collaboration, and computational analysis.
• Existing infrastructure may not be scalable or cohesive to meet diverse research needs.

Purpose of the Study:

• To introduce the iPlant Collaborative as a comprehensive computational infrastructure for life scientists.
• To highlight iPlant's role in facilitating data management, identity management, collaboration, and computing resources.
• To emphasize iPlant's commitment to researcher training and best practices for data and computational skill development.

Main Methods:

• Providing scalable and cohesive computational infrastructure.
• Offering identity management and collaboration tools.
• Delivering cloud, high-performance, and high-throughput computing capabilities.
• Developing training materials and best practice resources.

Main Results:

• Enhanced access to computational infrastructure for life science research communities.
• Improved data management, sharing, and computational analysis capabilities.
• Increased researcher skill sets in data and computation for distributed teams.

Conclusions:

• The iPlant Collaborative empowers life scientists with essential computational tools and training.
• The platform fosters collaboration and enhances the reproducibility of research.
• iPlant facilitates the effective use and reuse of data and computational analyses within the scientific community.