MultiplEYE: Creating a multilingual eye-tracking-while-reading corpus

Eye-tracking-while-reading data provide valuable insights across multiple disciplines, including psychology, linguistics, natural language processing, education, and human-computer interaction. Despite its potential, the availability of large, high-quality, multilingual datasets remains limited, hindering both foundational reading research and advancements in applications. The MultiplEYE project addresses this gap by establishing a large-scale, international eye-tracking data collection initiative. It aims to create a multilingual dataset of eye movements recorded during natural reading, balancing linguistic diversity, while ensuring methodological consistency for reliable cross-linguistic comparisons. The dataset spans numerous languages and follows strict procedural, documentation, and data pre-processing standards to enhance eye-tracking data transparency and reproducibility. A novel data-sharing framework, integrated with data quality reports, allows for selective data filtering based on research needs. Researchers and labs worldwide are invited to join the initiative. By establishing and promoting standardized practices and open data sharing, MultiplEYE facilitates interdisciplinary research and advances reading research and gaze-augmented applications.