Data should be FAIR, meaning they should be findable, accessible, interoperable, and reusable. Especially in complex scientific fields, such as neuroscience, graph databases, such as the EBRAINS Knowledge Graph, are particular suited to host FAIR data and exchange gathered knowledge. In this session you will learn how to prepare your data for sharing and how to represent those data and the knowledge they hold in a graph database. First, we will generally discuss good practices for data organizations, metadata annotations, and data descriptors. You will then learn how to represent your data in a graph database using the openMINDS metadata framework. Last we will explore the benefits of data shared through the EBRAINS Knowledge Graph.
Requirements: WiFi; Laptop; EBRAINS account (desired); Python basic knowledge (desired)
Lyuba Zehl
Institute for Neuroscience and Medicine,
Structural and functional organisation of the brain (INM-1)
Forschungszentrum Jülich
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