Published

Contributing to Chess Multiverse Error Explorer

Sparsh Varshney
Sparsh Varshney
0

The definitive research platform for analyzing human decision errors, time pressure blunders, and opening complexities across elite chess.

Contributing to Chess Multiverse Error Explorer

Thank you for your interest in contributing to the Chess Multiverse Error Explorer.

This project is part of the broader Chess Multiverse Lab initiative and aims to provide reproducible, open research infrastructure for studying human chess errors, decision-making, time-pressure effects, and behavioral analytics.

We welcome contributions from:

  • Software developers
  • Data scientists
  • Chess researchers
  • Open-science contributors
  • UX/UI designers
  • Documentation writers
  • Students and independent researchers

Guiding Principles

Contributions should support one or more of the following goals:

  • Reproducibility
  • Transparency
  • Analytical correctness
  • Research usability
  • Open science
  • Long-term maintainability

The project prioritizes research quality over feature quantity.

Ways to Contribute

Bug Reports

If you discover a bug:

  1. Search existing issues first.

  2. Create a new issue if none exists.

  3. Include:

    • Browser version
    • Operating system
    • Steps to reproduce
    • Expected behavior
    • Actual behavior
    • Screenshots if applicable

Feature Requests

Feature proposals should:

  • Clearly describe the problem
  • Explain the research value
  • Provide a proposed implementation approach
  • Consider reproducibility implications

Examples:

  • New analytical metrics
  • Additional export formats
  • Dashboard enhancements
  • Query optimization
  • Accessibility improvements

Code Contributions

Workflow

  1. Fork the repository.
  2. Create a feature branch.
git checkout -b feature/my-improvement
  1. Commit changes using descriptive messages.
git commit -m "Add opening volatility metric"
  1. Push your branch.
git push origin feature/my-improvement
  1. Open a Pull Request.

Development Guidelines

JavaScript

Please follow existing coding conventions:

  • Use descriptive variable names.
  • Prefer explicit logic over clever shortcuts.
  • Keep analytical calculations readable.
  • Comment non-obvious mathematical operations.
  • Avoid introducing unnecessary dependencies.

SQL

Generated SQL should:

  • Remain reproducible.
  • Avoid browser-blocking queries.
  • Be compatible with DuckDB WASM.
  • Prioritize analytical clarity.

User Interface

UI contributions should:

  • Remain responsive.
  • Support mobile devices.
  • Preserve accessibility.
  • Avoid unnecessary visual complexity.

Research Metrics

Several metrics implemented in the platform are research constructs.

Examples include:

  • Expected Score Loss (ESL)
  • Opening Danger Index (ODI)
  • Panic Index

Changes affecting these metrics should:

  1. Include methodological justification.
  2. Include validation examples.
  3. Update documentation.
  4. Preserve reproducibility.

Testing Requirements

All contributions should pass the automated verification framework.

Current validation coverage includes:

  1. Parquet ingestion
  2. DuckDB projections
  3. SQL filter generation
  4. Expected Score Loss calculations
  5. Opening Danger Index calculations
  6. Panic Index calculations
  7. Material-signature search
  8. State serialization
  9. Export systems
  10. Dashboard synchronization
  11. Position replay validation
  12. Performance benchmarks

Where applicable, new features should include additional tests.

Documentation Contributions

Documentation improvements are highly encouraged.

Examples:

  • Correcting inaccuracies
  • Improving tutorials
  • Expanding methodology explanations
  • Enhancing installation instructions
  • Adding reproducibility examples

Dataset Contributions

The Chess Multiverse Error Explorer depends on the Chess Multiverse Error & Evaluation Dataset (CMEED).

If contributing dataset improvements:

  • Preserve schema compatibility whenever possible.
  • Document structural changes.
  • Maintain reproducibility.
  • Provide migration notes when necessary.

Pull Request Checklist

Before submitting a pull request:

  • Code compiles successfully
  • Existing tests pass
  • Documentation is updated
  • New functionality is explained
  • No unnecessary dependencies added
  • Reproducibility is preserved

Citation

If your contribution results in a publication, please cite:

Chess Multiverse Error Explorer

and

Chess Multiverse Error & Evaluation Dataset (CMEED v1.0)

as described in the project README.

Questions

For questions, discussions, or research collaboration ideas, please open a GitHub Issue.

Constructive feedback, reproducible research practices, and open collaboration are always welcome.

Thank you for helping improve open chess research infrastructure.