Mobile Collaboration Platform for Dataset Annotation Teams

Added Nov 2025 3 design docs

Every supervised machine-learning effort and many research studies depend on humans labeling data, and coordinating a distributed annotation team quickly becomes the bottleneck: who labels what, whose work gets reviewed, and how far along the dataset is. Purpose-built annotation platforms solve this, and building one exercises nearly every full-stack skill. The intern creates a mobile-first platform where teams upload datasets, split them into annotation tasks, and work through them collaboratively. A Spring Boot backend manages user roles, task assignment and distribution, submission review queues, and data integrity guarantees so that no item is labeled twice or lost. The React Native app gives annotators a fast interface for tagging and validating items, while leads monitor real-time progress, reassign work, and review submissions. Key flows include dataset upload, task claiming, annotation submission, reviewer approval or rejection, and live progress tracking across the team. The project teaches mobile development against a substantial backend, careful workflow and state modeling, and the operational realities of data quality. The intern finishes with a genuinely useful tool and demonstrable full-stack range.

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