Reproducible Research

A computational approach

January 2026

Content

• Fundamentals of computational reproducibility

• Containerization

• Binder

• Docker containers

Goal

Computational reproducibility means that research results obtained through computation can be consistently re-produced by others given the same inputs and methods.

Benefits of Computational Reproducibility

1. Integrity and Trust

2. Efficiency and Reuse

3. Collaboration and Transparency

4. Long-term Preservation

5. Scalability and Generalization

6. Policy and Funding Compliance

The Pillars

• Code

• Data

• Environment

• Documentation

• Workflows

The Challenges

• Software root

• Data availability

• Complexity

• Human factors

Tools for Computational Reproducibility

• Version control

• Containerization

• Workflow systems

• Data repositories

• Notebooks and literate programming

• Community standards

Spectrum of reproducibility