Use Self-Contained Projects: For each distinct study or dataset, create a self-contained project to keep your data, annotations, and reports coherently organized. This ensures each dataset remains contextually bounded and prevents mixing materials from different studies.
Document Your Research: Use descriptive project names and detailed descriptions to document your research questions, corpus source, and other contextual details. This practice turns your project into a “digital lab notebook” that supports later interpretation and reproducibility.
Prepare Data Correctly: Ensure your data is in a CSV file with exactly two columns, labeled precisely ErrorText for the original version and CorrectedText for the revised version. This structure is required for the application to properly import and align text pairs.
Backup and Share Your Work: Regularly export entire projects as .zip archives. This practice serves as a secure backup and allows you to share your complete work—including texts, annotations, and tag schemas—with colleagues for collaboration or replication.