A workflow that guides users from survey design to data validation, analysis, and reporting. Each phase supports a transparent, repeatable process designed for accuracy, collaboration, and long-term usability.

Users begin by creating a new survey or importing an existing template through the Survey Designer interface.

• Create or Import Survey: Users begin by creating a new survey or importing an existing template through the Survey Designer interface.

• Hierarchical Entity Modeling: Define entities such as plots, subplots, trees, or soil samples, and their relationships within the survey.

• Variables & Code Lists: Establish variables, classifications, and lookup tables (e.g., species codes, land classes) to ensure harmonization across datasets.

• Validation Logic: Set up range checks, required fields, logical constraints, and custom code lists to prevent data inconsistencies.

• Documentation: All survey definitions are stored in IDML (Inventory Data Management Language), ensuring full traceability and compatibility with other Open Foris tools.

Once the survey structure is defined, authorized users can enter data through a guided, responsive interface optimized for large datasets.

• Role-Based Access: Permissions define who can view, edit, or approve specific survey components.

• Assisted Data Entry: Auto-complete fields, lookup popups, and contextual help texts support fast and accurate input.

• Instant Validation: Automated checks provide real-time feedback, flagging errors and warnings directly in the form.

Supervisors review and refine data using integrated tools for validation, correction, and communication with field teams.

• Validation Dashboards: Summaries highlight flagged records, missing values, and inconsistencies.

• Supervisor Review Mode: Filter records by status, user, or error type for targeted quality control.

• Batch & Manual Editing: Apply corrections, add notes, or temporarily exclude records for further review.

• Iterative Cleansing: Multi-cycle validation allows continuous improvement and dialogue between data collectors and supervisors.

• Preparation for Export: Once quality checks are complete, datasets can be locked or marked as final to prevent further edits.

• Multi-Format Export: Cleaned datasets are exportable in standard formats (CSV for tabular data, XML for structured records, or database dumps for larger projects).

• External Integration: Exported data can be fed into geographic information systems (GIS), statistical analysis software, or national reporting templates to meet reporting requirements.