In Silico Neuroscience: Data Reproducibility and Reusability

This lecture covers the importance of data reproducibility and reusability in in silico neuroscience, focusing on neuroinformatics tools and methods. It discusses challenges in finding, storing, analyzing, and publishing neuroscience data, emphasizing the need for standardized metadata and controlled vocabularies. The lecture also explores the concepts of provenance, metadata quality, and the Minimal Information for Neuroscience Datasets (MINDS) standard. It highlights the significance of ontology, standard vocabulary, and the FAIR Guiding Principles for data findability, accessibility, interoperability, and reusability. The Blue Brain Project's efforts in simulation neuroscience and the integration of software and hardware ecosystems are also discussed.