The goal of {ftsAnalysis} is to provide a comprehensive toolkit for
analyzing humanitarian funding flows using open data from the OCHA
Financial Tracking Service (FTS). It offers a
set of metrics, indices, analysis, and visualizations to generate
insights about funding dynamics.
Language Models are used to automatically generate narrative and reports from three key perspectives:
- Donors: Analyze funding behavior, consistency, and strategic alignment.
- Recipients: Evaluate funding stability, diversification, and dependency.
- Destinations: Assess funding coverage, gaps, and risks for specific crises or locations.
This package is built with the help of
{fusen} package which allows to
maintain consistent documentation through notebooks ( cf dev folder).
You can install it from GitHub with:
# install.packages("pak")
pak::pak("Edouard-Legoupil/ftsAnalysis")
# Report generation examplke
ftsAnalysis::generate_report(type = "donor", name = "Switzerland, Government of")To leverage the AI-powered data storytelling features (automated
narrative generation for plots), you need to set API keys in your
environment (e.g., in your .Renviron file) to configure access to
Large Language Models through Azure, OpenAI, Gemini or Anthropic.
Alternatively, you can use Ollama for local
inference, leveraging Open Source & Reasoning Small Language Models like
Gemma3 or
DeepSeek-R1.