Documentation Chapters

Segmented Data Export

The Segmented Data Export pipeline serializes raw eye-tracking vectors into structured CSV files meticulously formatted for advanced manipulation in spreadsheet software (Excel, Google Sheets) or command-line scripting architectures (Python, R).

Data Structure

Segmented CSV file outputs contain highly granular, row-level sequential eye-tracking logic exposing:

  • Unified participant identifiers.
  • Stimulus metadata connections.
  • Raw fixation coordinates (X, Y) and localized duration metrics.
  • Hardcoded AOI collision assignments.
  • Absolute micro-second timestamp delineations.
  • Computed gaze event classifications.

Export Configuration

To generate segmented CSV files, you can configure several parameters to filter and format the output.

Global Settings

  • Export Type: Choose between Single CSV File (monolithic) or Individual CSV Files (Zipped) (sharded by participant).
  • File name: Specify the root output filename.
  • Delimiter: Choose between Comma (,) or Semicolon (;).
  • Decimal Separator: Choose between Dot (.) or Comma (,).

Data Filtering

  • Stimuli: Select one or more specific stimuli to include in the export.
  • Fixations Only: Enable this filter to exclude saccades, blinks, and other non-fixation gaze movements from the output.

Execution Workflow

  1. Access Export: Click the Export workspace or data button in the Workspace Toolbar.
  2. Select Format: In the Research Data Formats section, click on the Segmented Data (CSV) card.
  3. Configure Settings: Select your preferred Export Type, File name, Delimiter, and Decimal Separator.
  4. Target Data: Select the target Stimuli and apply any Filters (e.g., Export only fixations).
  5. Download: Click the Export Data button. A success toast will confirm the file generation.

Analytical Use Cases

  • Single CSV: Best for programmatic ingestion (R, Python pandas) where algorithmic filtering of monolithic dataframes is required.
  • Zipped Individual CSVs: Optimal for manual spreadsheet analysis or when research protocols require isolation of subject data arrays.