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Difficulty level: Beginner
Duration: 1:03:29
Speaker: : Ruben Armananzas

A short reel on who we are, what we're doing and why we're doing it

Difficulty level: Beginner
Duration: 2:38
Speaker: :

In this webinar, educators currently implementing collaborative annotation in their classrooms discuss their experiences with collaborative annotation and using Hythothes.is and Canvas App.

Difficulty level: Beginner
Duration: 53:14
Speaker: : Jeremy Dean

Tutorial that provides an overview of how to use the feature of Hypothes.is.

Difficulty level: Beginner
Duration: 09:30
Speaker: :

A brief overview of the Hypothesis functionality from an end user's perspective.

Difficulty level: Beginner
Duration: 5:36
Speaker: : Heather Staines

This video will teach you the basics of navigating the OSF, a free research management tool, and creating your first projects.

Difficulty level: Beginner
Duration: 2:11
Speaker: :

This webinar walks you through the basics of creating an OSF project, structuring it to fit your research needs, adding collaborators, and tying your favorite online tools into your project structure.

Difficulty level: Beginner
Duration: 55:02
Speaker: : Ian Sullivan

This webinar will introduce how to use the Open Science Framework (OSF; https://osf.io) in a Classroom. The OSF is a free, open source web application built to help researchers manage their workflows. The OSF is part collaboration tool, part version control software, and part data archive. The OSF connects to popular tools researchers already use, like Dropbox, Box, Github and Mendeley, to streamline workflows and increase efficiency.

Difficulty level: Beginner
Duration: 32:01

Organizing related projects with Links, Forks, and Templates.

Difficulty level: Beginner
Duration: 51:14
Speaker: : Ian Sullivan

This webinar will introduce the integration of JASP Statistical Software (https://jasp-stats.org/) with the Open Science Framework (OSF; https://osf.io). The OSF is a free, open source web application built to help researchers manage their workflows

Difficulty level: Beginner
Duration: 30:56
Speaker: : Alexander Etz
  1. How keeping track of the different file versions is important for efficient reproducible research practices
  2. How version control works on the OSF
  3. How researchers can view and download previous versions of files
Difficulty level: Beginner
Duration: 22:07

The Identifiers.org system is a central infrastructure for findable, accessible, interoperable and re-usable (FAIR) data. It provides a range of services to generate, resolve and validate persistent Compact Identifiers to promote the citability of individual data providers and integration with e-infrastructures.

Difficulty level: Beginner
Duration: 36:41

Web annotation provides a powerful new capability to biomedicine. With Hypothes.is, any content on the web can be turned into an interactive forum for on-line discussions or annotated with additional information. Because Hypothes.is is engineered for the web, annotations can be replied to, shared and searched across contexts. Hypothesis supports public, private and group annotation.

Difficulty level: Beginner
Duration: 52:06
Speaker: : Maryann Martone

Next generation science with Jupyter. This lecture was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Intermediate
Duration: 50:28
Speaker: : Elizabeth DuPre

Introduction to reproducible research. The lecture provides an overview of the core skills and practical solutions required to practice reproducible research. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner
Duration: 1:25:17
Speaker: : Fernando Perez

Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience.  FAIR defines a set of high-level principles and practices for making digital objects, including data, software, and workflows, Findable, Accessible,  Interoperable, and Reusable.  But FAIR is not a specification;  it leaves many of the specifics up to individual scientific disciplines to define.  INCF has been leading the way in promoting, defining, and implementing FAIR data practices for neuroscience.  We have been bringing together researchers, infrastructure providers, industry, and publishers through our programs and networks.  In this session, we will hear some perspectives on FAIR neuroscience from some of these stakeholders who have been working to develop and use FAIR tools for neuroscience.  We will engage in a discussion on questions such as:  how is neuroscience doing with respect to FAIR?  What have been the successes?  What is currently very difficult? Where does neuroscience need to go? This lecture covers the biomedical researcher's perspective on FAIR data sharing and the importance of finding better ways to manage large datasets.

Difficulty level: Beginner
Duration: 10:51
Speaker: : Adam Ferguson

Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience.  FAIR defines a set of high-level principles and practices for making digital objects, including data, software, and workflows, Findable, Accessible,  Interoperable, and Reusable.  But FAIR is not a specification;  it leaves many of the specifics up to individual scientific disciplines to define.  INCF has been leading the way in promoting, defining, and implementing FAIR data practices for neuroscience.  We have been bringing together researchers, infrastructure providers, industry, and publishers through our programs and networks.  In this session, we will hear some perspectives on FAIR neuroscience from some of these stakeholders who have been working to develop and use FAIR tools for neuroscience.  We will engage in a discussion on questions such as:  how is neuroscience doing with respect to FAIR?  What have been the successes?  What is currently very difficult? Where does neuroscience need to go? This lecture covers multiple aspects of FAIR neuroscience data: what makes it unique, the challenges to making it FAIR, the importance of overcoming these challenges, and how data governance comes into play.

Difficulty level: Beginner
Duration: 14:56
Speaker: : Damian Eke

Over the last three decades, neuroimaging research has seen large strides in the scale, diversity, and complexity of studies, the open availability of data and methodological resources, the quality of instrumentation and multimodal studies, and the number of researchers and consortia. The awareness of rigor and reproducibility has increased with the advent of funding mandates, and with the work done by national and international brain initiatives. This session will focus on the question of FAIRness in neuroimaging research touching on each of the FAIR elements through brief vignettes of ongoing research and challenges faced by the community to enact these principles. This lecture covers the processes, benefits, and challenges involved in designing, collecting, and sharing FAIR neuroscience datasets.

Difficulty level: Beginner
Duration: 11:35

Over the last three decades, neuroimaging research has seen large strides in the scale, diversity, and complexity of studies, the open availability of data and methodological resources, the quality of instrumentation and multimodal studies, and the number of researchers and consortia. The awareness of rigor and reproducibility has increased with the advent of funding mandates, and with the work done by national and international brain initiatives. This session will focus on the question of FAIRness in neuroimaging research touching on each of the FAIR elements through brief vignettes of ongoing research and challenges faced by the community to enact these principles. 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

Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience.  FAIR defines a set of high level principles and practices for making digital objects, including data, software and workflows, Findable, Accessible,  Interoperable and Reusable.  But FAIR is not a specification;  it leaves many of the specifics up to individual scientific disciplines to define.  INCF has been leading the way in promoting, defining and implementing FAIR data practices for neuroscience.  We have been bringing together researchers, infrastructure providers, industry and publishers through our programs and networks.  In this session, we will hear some perspectives on FAIR neuroscience from some of these stakeholders who have been working to develop and use FAIR tools for neuroscience.  We will engage in a discussion on questions such as:  how is neuroscience doing with respect to FAIR?  What have been successes?  What is currently very difficult? Where does neuroscience need to go?

 

This lecture will provide an overview of Addgene, a tool that embraces the FAIR principles developed by members of the INCF Community. This will include an overview of Addgene, their mission, and available resources.

Difficulty level: Beginner
Duration: 12:05
Speaker: : Joanne Kamens