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This is the first of two workshops on reproducibility in science, during which participants are introduced to concepts of FAIR and open science. After discussing the definition of and need for FAIR science, participants are walked through tutorials on installing and using Github and Docker, the powerful, open-source tools for versioning and publishing code and software, respectively.

Difficulty level: Intermediate
Duration: 1:20:58

Research Resource Identifiers (RRIDs) are ID numbers assigned to help researchers cite key resources (e.g., antibodies, model organisms, and software projects) in biomedical literature to improve the transparency of research methods.

Difficulty level: Beginner
Duration: 1:01:36
Speaker: : Maryann Martone

This video gives a short introduction to the EBRAINS data sharing platform, why it was developed, and how it contributes to open data sharing.

Difficulty level: Beginner
Duration: 17:32
Speaker: : Ida Aasebø

This video explains what metadata is, why it is important, and how you can organize your metadata to increase the FAIRness of your data on EBRAINS.

Difficulty level: Beginner
Duration: 17:23
Speaker: : Ulrike Schlegel

This video introduces the importance of writing a Data Descriptor to accompany your dataset on EBRAINS. It gives concrete examples on what information to include and highlights how this makes your data more FAIR.

Difficulty level: Beginner
Duration: 9:48
Speaker: : Ingrid Reiten
Course:

KnowledgeSpace (KS) is a data discoverability portal and neuroscience encyclopedia that was developed to make it easier for the neuroscience community to find publicly available datasets that adhere to the FAIR Principles and to provide an integrated view of neuroscience concepts found in Wikipedia and NeuroLex linked with PubMed and 17 of the world's leading neuroscience repositories. In short, KS provides a single point of entry where reseaerchers can search for a neuroscience concept of interest and receive results that include: i. a description of the term found in Wikipedia/NeuroLex, ii. links to publicly available datasets related to the concept of interest, and iii. up-to-date references that support the concept of interests found in PubMed. APIs are available so that developers of other neuroscience research infrastructures can integrate KS components in their infrastructures. If your repository or your favorite repository is not indexed in KS, please contact us.

 

Difficulty level: Beginner
Duration: 6:14
Speaker: : Heather Topple

In this lesson, users will learn about the importance of proper citation of software resources and tools used in neuroscientific research. 

Difficulty level: Beginner
Duration: 58:00
Course:

The Mouse Phenome Database (MPD) provides access to primary experimental trait data, genotypic variation, protocols and analysis tools for mouse genetic studies. Data are contributed by investigators worldwide and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD ensures rigorous curation of phenotype data and supporting documentation using relevant ontologies and controlled vocabularies. As a repository of curated and integrated data, MPD provides a means to access/re-use baseline data, as well as allows users to identify sensitized backgrounds for making new mouse models with genome editing technologies, analyze trait co-inheritance, benchmark assays in their own laboratories, and many other research applications. MPD’s primary source of funding is NIDA. For this reason, a majority of MPD data is neuro- and behavior-related.

Difficulty level: Beginner
Duration: 55:36
Speaker: : Elissa Chesler

This short video walks you through the steps of publishing a dataset on brainlife, an open-source, free and secure reproducible neuroscience analysis platform.

Difficulty level: Beginner
Duration: 1:18
Speaker: :

This video shows how to use the brainlife.io interface to edit the participants' info file. This file is the ParticipantInfo.json file of the Brain Imaging Data Structure (BIDS).

Difficulty level: Beginner
Duration: 0:34
Speaker: :

This video will document the process of running an app on brainlife, from data staging to archiving of the final data outputs.

Difficulty level: Beginner
Duration: 3:43
Speaker: :

This video will document the process of visualizing the provenance of each step performed to generate a data object on brainlife.

Difficulty level: Beginner
Duration: 0:21
Speaker: :

This video will document the process of downloading and running the "reproduce.sh" script, which will automatically run all of the steps to generate a data object locally on a user's machine.

Difficulty level: Beginner
Duration: 3:44
Speaker: :

This video will document the process of creating a pipeline rule for batch processing on brainlife.

Difficulty level: Intermediate
Duration: 0:57
Speaker: :

This video will document the process of launching a Jupyter Notebook for group-level analyses directly from brainlife.

Difficulty level: Intermediate
Duration: 0:53
Speaker: :

This brief video walks you through the steps necessary when creating a project on brainlife.io. 

Difficulty level: Beginner
Duration: 1:45
Speaker: :

This brief video rus through how to make an accout on brainlife.io.

Difficulty level: Beginner
Duration: 0:30
Speaker: :

This video will document how to run a correlation analysis between the gray matter volume of two different structures using the output from brainlife app-freesurfer-stats.

Difficulty level: Beginner
Duration: 1:33
Speaker: :

This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and goes through both the motivations and processes involved in moving your research computing to the cloud.

Difficulty level: Intermediate
Duration: 3:09:12

As a part of NeuroHackademy 2020, this lecture delves into cloud computing, focusing on Amazon Web Services. 

Difficulty level: Beginner
Duration: 01:43:59