Learnings from Building Neuroinformatics Pipelines

Neuroinformatics plays a pivotal role in advancing our understanding of the brain by integrating various data acquisition modalities and facilitating the dissemination of these datasets through data sharing platforms [1]. This paper presents an overview of the neuroinformatics pipeline, detailing the workflow from data acquisition to data sharing from my experience setting it up at the new Cornell MRI Facility and learning from being a data curator at openneuro [19]. It discusses the evolution of data acquisition methods, standard data processing procedures, and the emergence of cloud-based data sharing platforms. Furthermore, a comparison of prominent data sharing tools, including XNAT and Flywheel [18], is provided to highlight their respective features and functionalities.