OPTION 2 :: Install software by hand.
Required software:
- Text editor (preferably with JSON syntax highlighting, like Atom)
Additional recommended software for individual tutorial parts
- dcm2niix https://github.com/neurolabusc/dcm2niix
- mridefacer https://github.com/hanke/mridefacer
(requires FSL, num-utils and help2man packages)
- git-annex
- Chrome web browser or installation of bids-validator https://github.com/INCF/bids-validator
The detailed instructions to create the setup on Ubuntu are available here: bit.ly/prni2016ubuntu
OPTION 1 :: Install Virtualbox and download and install the workshop virtual machine image. Due to its size, it is required to obtain the image prior to the workshop with a decent internet connection! The Virtualbox software and installations instructions are available for all operating systems at http://virtualbox.org
For the hands-on sessions attendees will need a reasonably modern and capable laptop with an OS of their choice, and enough free storage capacity to handle software and data for this workshop.
Download the reference data (ca. 1.4 GiB) at bit.ly/prni2016dicom
Two options for setting up the system:
Prerequisites
For additional information you may contact tutorial2@prni.org
Chris Gorgolewski
Michael Hanke
Vittorio Iacovella
Center for Reproducible Neuroscience
Stanford University
Psychoinformatics lab
Otto-von-Guericke-University Magdeburg
Neuroinformatics Laboratory
Center for Mind/Brain Science
University of Trento
PRNI 2016 - TUTORIAL 2
Brain Data Sharing
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Data sharing has finally become a thing in brain imaging research. Potential benefits of data re-use by neuroscientist and researchers in adjacent fields are beginning to become manifest in the literature, driven by large funded efforts, such as the Human Connection Project, but also an increasing number of individual labs that share their primary data (e.g. on OpenFMRI). Yet, data sharing is still largely perceived as time consuming, riddled with legal pitfalls, and a net cost for the one sharing the data.
This tutorial will touch upon every aspect of sharing primary brain imaging data, and shed light on technical and non-technical solutions to make data sharing a net benefit for the one sharing the data.
The tutorial will consist of lectures, guided demos, and hands-on sessions.
TUESDAY, JUNE 21st
08:30 :: Registration
09:00 :: Introduction to Data Sharing and Best Practices in Data Analysis and Sharing in Neuroimaging using MRI
Introductory lecture on the benefits of data sharing from the perspective of a small lab, and overview on available guidelines and best practises for acquiring and sharing brain imaging data
11:00 :: Hands-on BIDS
10:30 :: Coffee Break
12:30 :: Lunch Break
13:30 :: Survey of existing platform for data sharing
15:00 :: Coffee Break
15:30 :: Datalad and the futuure of data sharing
09:45 :: Introduction to BIDS
Brain Imaging Data Structure (BIDS - bids.neuroimaging.io) - is a new standard for organizing and describing neuroimaging data. This lecture will give a historical background on BIDS and explain how various neuroimaging modalities should be handled.
Introduction to the conceptual and practical issues of transforming raw collections of DICOM files into a BIDS - compliant dataset. Practical exercises in performing preliminary procedures, data transformations and final assessments of the dataset validity.
Overview of different repositories where you can share your neuroimaging data.
14:00 :: Publication venues for data papers
Brief overview of relevant publication venues to maximize the impact of a data sharing effort -- for the community and the own career
14:30 :: Hands-on uploading to databases
Introduction to a suite of advanced data management tools (git, git-annex, datalad) that facilitate data sharing and re-use, and data management workflows with local, and external collaborators.
16:30 :: Hands-on demo