Food System Value Analytics (FSVC)

Food System Value Analytics (FSVC) is a production-ready platform that combines structured data collection with built-in analytics for food-system research, value chain analysis, and agricultural surveys. Researchers design studies, invite field teams, collect responses offline on tablets, and run statistical analysis from a single tool.

The platform is built for real field conditions: poor connectivity, multi-enumerator teams, mixed question types including GPS and images, and the need to merge responses cleanly when devices reconnect. It ships with role-based project collaboration and a deployment-ready backend so research groups can stand up studies without engineering overhead.

Offline-First Data Capture

The React Native client stores responses locally and syncs in the background when connectivity returns. Timestamp-based conflict resolution reconciles edits across devices, so teams can work in the field without risking data loss or duplication.

Form Builder and Validation

Researchers compose questionnaires using 12+ question types (text, numeric, single and multiple choice, rating scales, date and datetime, GPS location, images, and more), with drag-and-drop ordering, conditional logic, and validation rules. Auto-generated respondent IDs and real-time validation keep incoming data clean.

Analytics Microservice

A dedicated FastAPI analytics service runs beside the Django core. It auto-detects variable types and suggests appropriate analyses, then runs descriptive statistics, inferential tests, text analysis (NLTK-backed), and visualizations, all without leaving the platform.

Collaboration and Security

Projects use role-based access with five roles across ten permissions, plus expiring invitation tokens. Authentication is JWT with encrypted token storage on device and automatic refresh, following standard security practices for sensitive research data.