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This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.

Difficulty level: Beginner
Duration: 1:16:04

This lesson contains both a lecture and a tutorial component. The lecture (0:00-20:03 of YouTube video) discusses both the need for intersectional approaches in healthcare as well as the impact of neglecting intersectionality in patient populations. The lecture is followed by a practical tutorial in both Python and R on how to assess intersectional bias in datasets. Links to relevant code and data are found below. 

Difficulty level: Beginner
Duration: 52:26

This lecture discusses what defines an integrative approach regarding research and methods, including various study designs and models which are appropriate choices when attempting to bridge data domains; a necessity when whole-person modelling. 

Difficulty level: Beginner
Duration: 1:28:14
Speaker: : Dan Felsky

This lecture will provide an overview of neuroimaging techniques and their clinical applications.

Difficulty level: Beginner
Duration: 45:29
Speaker: : Dafna Ben Bashat

This lesson discusses both state-of-the-art detection and prevention schema in working with neurodegenerative diseases. 

Difficulty level: Beginner
Duration: 1:02:29
Speaker: : Nir Giladi

In this lesson, you will learn about how genetics can contribute to our understanding of psychiatric phenotypes.

Difficulty level: Beginner
Duration: 55:15
Speaker: : Sven Cichon

This lesson gives an introductory presentation on how data science can help with scientific reproducibility.

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

This lesson discusses FAIR principles and methods currently in development for assessing FAIRness.

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

This lesson gives a primer to project management in a scientific context, with a particular neuroinformatic case study. 

Difficulty level: Beginner
Duration: 19:06
Speaker: : Kelly Shen

In this lesson, you will hear about the current challenges regarding data management, as well as policies and resources aimed to address them. 

Difficulty level: Beginner
Duration: 18:13
Speaker: : Mojib Javadi

This lesson provides an overview of how to manage relationships in a research context, while highlighting the need for effective communication at various levels.

Difficulty level: Beginner
Duration:
Speaker: : Helena Ledmyr

This lecture covers the needs and challenges involved in creating a FAIR ecosystem for neuroimaging research.

Difficulty level: Beginner
Duration: 12:26
Speaker: : Camille Maumet

This lecture covers the NIDM data format within BIDS to make your datasets more searchable, and how to optimize your dataset searches.

Difficulty level: Beginner
Duration: 12:33
Speaker: : David Keator

This lecture covers the processes, benefits, and challenges involved in designing, collecting, and sharing FAIR neuroscience datasets.

Difficulty level: Beginner
Duration: 11:35

This lecture covers positron emission tomography (PET) imaging and the Brain Imaging Data Structure (BIDS), and how they work together within the PET-BIDS standard to make neuroscience more open and FAIR.

Difficulty level: Beginner
Duration: 12:06
Speaker: : Melanie Ganz

This lecture covers the benefits and difficulties involved when re-using open datasets, and how metadata is important to the process.

Difficulty level: Beginner
Duration: 11:20
Speaker: : Elizabeth DuPre

This lecture provides guidance on the ethical considerations the clinical neuroimaging community faces when applying the FAIR principles to their research. 

Difficulty level: Beginner
Duration: 13:11
Speaker: : Gustav Nilsonne