Library of Tasks
Overview
The Library of Tasks is one of the two primary strategic projects of the TTF-DDG. It serves as a centralized platform for managing, sharing, and implementing computer-based research tasks across all work packages of the NCCR Evolving Language project.
Purpose & Goals
Vision
To create a comprehensive, accessible repository of research tasks that enables:
- Efficient Collaboration: Work packages can share methodologies and implementations
- Rapid Development: Researchers can build upon existing tasks rather than starting from scratch
- Standardization: Common approaches to similar research challenges
- Quality Assurance: Vetted, tested task implementations
- Knowledge Preservation: Long-term sustainability of research software
Key Objectives
- Provide a single source of truth for task implementations
- Enable easy viewing, editing, and sharing of tasks
- Facilitate cross-work package collaboration
- Reduce duplication of technical effort
- Ensure reproducibility of research tasks
Access
The Library of Tasks is accessible via a dedicated subdomain:
Features
Browse & Discover
- Searchable catalog of available tasks
- Filtering by research area, technology, or work package
- Detailed documentation for each task
- Usage examples and implementation guides
View & Understand
- Source code access
- Technical specifications
- Dependencies and requirements
- Deployment instructions
Edit & Customize
- Fork existing tasks for specific research needs
- Adapt parameters and configurations
- Extend functionality while maintaining compatibility
Share & Contribute
- Submit new tasks to the library
- Contribute improvements to existing tasks
- Share best practices and lessons learned
- Collaborate on common challenges
Task Categories
The library includes tasks spanning various research domains:
- Behavioral Tasks: Experimental paradigms for behavioral studies
- Cognitive Tasks: Tasks measuring cognitive processes
- Linguistic Tasks: Language-specific experimental tasks
- Data Collection Tools: Instruments for various data types
- Analysis Pipelines: Common analysis workflows
Technical Infrastructure
Architecture
- Modern web-based platform
- Version control integration
- Automated testing and validation
- Documentation generation
- Dependency management
Standards
All tasks in the library adhere to:
- Code quality standards
- Documentation requirements
- Testing coverage minimums
- Accessibility guidelines
- Cross-platform compatibility
Current Contents
The library currently includes implementations from:
- ✅ Meaning Task (with Jodie Franco)
- ✅ LEAPS System tasks (Zurich tablet-based - https://www.leaps-zh.ch/)
- ✅ Unity Crab Battery components
- 🔄 MEG-based tasks (in development)
- 🔄 Eye-tracking tasks for great apes (in development)
[Detailed listings of available tasks]
Contributing to the Library
For Researchers
If you have developed a task that could benefit other work packages:
- Contact the TTF-DDG team
- Discuss standardization and documentation needs
- Work with us to prepare the task for the library
- Submit for review and inclusion
For Developers
Technical contributors can help by:
- Improving existing task implementations
- Enhancing documentation
- Expanding test coverage
- Optimizing performance
- Adding new features
Support & Documentation
Getting Started
Contact the TTF-DDG team for:
- Library user guidance and onboarding
- Task development guidelines and best practices
- API documentation and integration support
Technical Support
The TTF-DDG team provides ongoing support for:
- Task implementation assistance
- Troubleshooting and debugging
- Customization consultation
- Integration with existing systems
Roadmap
Current Phase
- Expanding task collection
- Improving discoverability features
- Enhancing documentation
- Building community of contributors
Future Development
- Advanced search and filtering
- Automated compatibility testing
- Integration with data management systems
- Expanded analysis tool integration
- Multi-language support
Impact
The Library of Tasks enables:
- Faster Research: Build on proven implementations
- Higher Quality: Benefit from peer-reviewed, tested code
- Better Collaboration: Share methodologies seamlessly
- Resource Efficiency: Avoid duplicating technical work
- Reproducibility: Use standardized, documented tasks