Quality Flow Projects provides you with enhanced quality assurance methodology along with highly flexible data annotation workflow capabilities.
Guide to: Quality Flow Project Set-up
Fig. 1: Example Quality Flow
In a Quality Flow project you can:
- perform ongoing quality assurance on all or a sample of your data
- communicate feedback to contributors in-tool, and optionally allow them the right of reply
- investigate in detail the quality of each contributor’s work
- filter and sort your data based on responses, qa results, unit history and more
- put your data through various different operations (or jobs), without downloading and uploading
- break larger files into smaller segments but keep them together in groups, so that contributors can work on them in sequence and retain context
Fig. 2: Example dataset actions
Fig. 3: Example Quality Metrics