Reproducibility in ESIA Analyses: Why It Matters
The Reproducibility Problem in EIA
Environmental and Social Impact Assessments are critical decision-making documents, yet the analytical workflows behind them are often opaque: Excel spreadsheets passed between teams, manual copy-paste of results, and no version control. This makes it nearly impossible to verify, update, or audit the analyses that inform environmental decisions.
A Better Approach
At Kwiz Computing Technologies, we advocate for reproducible ESIA workflows built on R and Quarto. This means version-controlled code, automated data pipelines, parameterised reports, and transparent methodology that any qualified reviewer can verify.
Our kenyaEIAFetcher package is one step in this direction — providing programmatic access to Kenya’s EIA database so that researchers and practitioners can work with structured data rather than manual downloads.
Key Principles
The same engineering discipline we apply to our trading systems serves environmental data science: test your code, document your methods, version your analyses, and make your work reproducible by default.
Reproducibility isn’t just good science — it’s good engineering.