This workshop is organized by the German National Research Data Infrastructure Initiative Neuroscience (NFDI-Neuro). The initiative is community driven and comprises around 50 contributing national partners and collaborators. NFDI-Neuro partners with EBRAINS AISB, the coordinating entity of the EU Human Brain Project and the EBRAINS infrastructure. We will introduce common methods that enable digital reproducible neuroscience. Each class of research data management methods is first introduced conceptually, followed by a practical hands-on session. For hands-on sessions we will use the Collaboratory by EBRAINS as a joint digital workspace providing a range of functionalities including computing and storage resources.
Enabling Multi-Scale Data Integration: Turning Data to Knowledge
Course Features
Lectures
Tutorial
Videos
Lessons of this Course
1
1
Duration:
2:44
Speaker:
This lesson is a brief introduction to the course, reiterating the goals of the NFDI-Neuro: to advance and disseminate a federated interoperable ecosystem for data and for reproducible research.
2
2
Duration:
8:22
Speaker:
This talk covers EBRAINS, an open research infrastructure that gathers data, tools and computing facilities for brain-related research, built with interoperability at the core.
3
3
Duration:
21:56
Speaker:
In this lesson, attendees will learn about the data structure standards, specifically the Brain Imaging Data Structure (BIDS), an INCF-endorsed standard for organizing, annotating, and describing data collected during neuroimaging experiments.
4
4
Duration:
32:58
Speaker:
This lesson provides a hands-on tutorial for generating simulated brain data within the EBRAINS ecosystem.
5
5
Duration:
1:35:37
Speaker:
This lesson discusses the need for and approaches to integrating data across the various temporal and spatial scales in which brain activity can be measured.
6
6
Duration:
3:46:21
Speaker:
This lesson consists of lecture and tutorial components, focusing on resources and tools which facilitate multi-scale brain modeling and simulation.
7
6
Duration:
21:49
Speaker:
In this talk, challenges of handling complex neuroscientific data are discussed, as well as tools and services for the annotation, organization, storage, and sharing of these data.
8
6
Duration:
22:23
Speaker:
This lecture describes the neuroscience data respository G-Node Infrastructure (GIN), which provides platform independent data access and enables easy data publishing.
