Data and Innovation
At ATNi (Access to Nutrition initiative), we believe that data is a powerful lever for transforming food systems. Our data and innovation workstream is designed to break siloes, foster transparency, and accelerate access to nutritious food through evidence-based tools and experimentation.
What we do
1. Increase access to packaged food data with a focus on LMICs to support better nutrition monitoring and analysis.
2. Promote transparency and open access to data by sharing analyses as open datasets, in standardized, human- and machine-readable formats, in accordance with FAIR data sharing principles.
3. Make data actionable through visual dashboards in a user-friendly manner to maximize the value and relevance of its data for the broader nutrition community, in consulation with established user groups.
Our core values
- Transparency: We make nutrition-related data publicly available to empower stakeholders across the food system.
- Interoperability: We design tools and datasets that can be integrated across platforms and geographies.
- Impact: We focus on data that drives measurable change in market behavior, policy, and product development.
Open Access Datasets
We host a growing collection of public datasets on our GitHub repository. These include:
- Nutrient profiling data from countries like Kenya, Nigeria, and India.
- Scoring tools for Nutri-Score, Health Star Rating, and WHO Nutrient Profile Model.
- Methodology documentation and transparency reports.
All materials are shared under a Creative Commons license to encourage reuse and collaboration.
Innovation
We actively test new approaches to nutrition assessment and stakeholder engagement. Current experiments include:
- NutriScore Self-Assessment Tool: A pilot app that allows SMEs and other stakeholders to bulk-calculate NutriScore values for their products. Developed using open data and hosted on Streamlit. The prototype is shared openly to invite feedback and foster co-creation.
In addition, ATNi published foundational guidance on the use of AI in nutrition research and applied these advances to the development of an AI‑enabled prototype of the Nutrition Transformation Hub.
