A step-by-step walkthrough for requesters—from scoping tasks and setting budgets to reviewing submissions and releasing payout.
Launching your first project on DataW does not require a large ops team. Start with a narrow, measurable brief: what data you need, in what format, and what “done” looks like for each submission.
Define clear acceptance criteria before you post. Collectors work faster when instructions, examples, and rejection reasons are explicit. Use milestones or batch sizes if your dataset is large—you can scale collectors once quality is stable.
Budget for validation time, not just collection. Built-in quality checks and requester approval protect spend: payment releases only after work meets spec. Review a pilot batch, give feedback, then widen the pool.
When results look good, approve and release funds through the wallet flow. Export structured deliverables for your ML pipeline or research notebook, and iterate on the next wave with the same collector cohort if retention matters.
Written by
Maya Chen
Product Lead