Introduction of the Capsules environment to support further growth of the SBGrid structural biology software collection
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Summary
This summary is machine-generated.Scientific software management is complex. The SBGrid team developed Capsules to provide isolated, reproducible software environments, enhancing research reproducibility and FAIR data principles across diverse computing platforms.
Area Of Science
- Scientific software engineering
- Computational biology
- Bioinformatics
Background
- The vast scientific software ecosystem presents challenges for research reproducibility and provenance tracking.
- Diverse applications, versions, and platforms complicate software management and usage.
- Ensuring consistent software environments is critical for reliable scientific outcomes.
Purpose Of The Study
- To address the complexities of managing a large scientific software collection.
- To develop a transparent, cross-platform solution for scientific software execution.
- To enhance the findability, accessibility, interoperability, and reusability (FAIR) of scientific software.
Main Methods
- Development of the Capsule Software Execution Environment (Capsules) using programmatically generated bash scripts.
- Isolation of application runtime environments to prevent conflicts.
- Centralized management and distribution of over 530 specialized structural biology applications.
- Integration of Capsules with the SBGrid platform for on-premises and cloud computing.
Main Results
- Capsules provide a modular, secure, and conflict-free software distribution method.
- The solution offers transparent cross-platform functionality without requiring elevated privileges.
- The SBGrid platform, utilizing Capsules, demonstrably improves software findability, accessibility, interoperability, and reusability.
- Successful application in structural biology with potential for broader scientific fields.
Conclusions
- Capsules offer a robust solution for managing complex scientific software environments.
- The SBGrid platform enhances research reproducibility and adherence to FAIR principles.
- The developed methodology is adaptable for diverse scientific domains beyond structural biology.
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