On 17 January, Alessandra Rampinini, post doctoral fellow at the Brain and Language Lab, University of Geneva, will talk about "Leveraging Open Data in Neurolinguistics: Challenges in the Age of Reproducible Science".

Abstract

In the rapidly evolving landscape of neuroscience and linguistics, open data practices are becoming pivotal for advancing reproducible and transparent science. This talk explores the opportunities and obstacles associated with implementing open data principles in neurolinguistics research. Open data can accelerate discovery, foster interdisciplinary collaboration, and enhance the reliability of findings by enabling independent validation. However, navigating ethical considerations, data standardization, cultural and technical barriers remains a significant challenge, particularly when dealing with sensitive information such as brain imaging and language performance data. 

In the second part of the talk, I will introduce the Nebula101 dataset, a rich multimodal resource designed to advance research in neurolinguistics. Nebula101 integrates behavioral, neuroimaging, and phenotypic data, annotated using standardized ontologies to ensure transparency, interoperability, and reusability. By adhering to open science principles such as the Brain Imaging Data Structure (BIDS), this dataset exemplifies how accessible, well-documented resources can facilitate interdisciplinary collaboration and reproducibility in neuroscience research. Through the lens of Nebula101, I will explore the ethical and practical challenges of sharing sensitive data while maintaining participant confidentiality and data integrity. Additionally, I will discuss how this dataset serves as a benchmark for validating neurolinguistic theories, fostering equitable access to data and empowering researchers to address critical questions about language and cognition. This section will demonstrate how resources such as Nebula101 represent a step forward in leveraging open data to enhance the impact of neurolinguistic research.