Guidelines & Standards

A multilingual eye-tracking data collection for human and machine language processing research

To ensure consistency, transparency, and reusability of eye-tracking datasets, EyeStore follows a structured framework for data submission, metadata documentation, and quality control. This page provides researchers with essential guidelines for preparing their datasets for inclusion in EyeStore.

• Data Submission Guidelines: Step-by-step instructions on how to contribute datasets, including required file formats, documentation, and metadata standards.
• Metadata Standards: A detailed overview of the standardized metadata schema used in EyeStore, covering dataset-, session-, and trial-level information to facilitate searchability and interoperability.
• Quality Control Measures: Criteria for assessing data quality, including calibration accuracy, validation performance, and preprocessing requirements.
• Best Practices for Data Documentation: Recommendations for ensuring comprehensive and transparent dataset descriptions, facilitating long-term usability and reproducability.