# Sharing research products FAIRly

Camille Maumet

## ► To cite this version:

Camille Maumet. Sharing research products FAIRly. Educational course "Cultivating open science practices in academic research and culture" at OHBM 2022 - 28th Annual Meeting of the Organization of Human Brain Mapping, Jun 2022, Glasgow, United Kingdom. 2022. hal-03698730

HAL Id: hal-03698730

https://inria.hal.science/hal-03698730v1

Submitted on 18 Jun 2022

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
<figure><img src="image_2.png" /></figure>

Image credits: "use all the colors" by Laura Bundesen, OHBM Brain Art SIG 2020

# Sharing research products FAIRly

Camille Maumet

Univ Rennes, Inria, Inserm, CNRS, IRISA
# Why sharing different research products?
<figure><img src="image_3.png" /></figure>

Acquisition

<figure><img src="image_4.png" /></figure>

Data preparation

<figure><img src="image_5.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_6.png" /></figure>
<figure><img src="image_7.png" /></figure>

Acquisition

<figure><img src="image_8.png" /></figure>

Data preparation

<figure><img src="image_9.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>
# Why sharing research products?

Acquisition

<figure><img src="image_12.png" /></figure>

Data preparation

<figure><img src="image_13.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>
# Why sharing research products?

Acquisition

<figure><img src="image_17.png" /></figure>

Data preparation

<figure><img src="image_18.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>
# Why sharing research products?

Data

Analysis

Data

Analysis

<figure><img src="image_21.png" /></figure>

<figure><img src="image_22.png" /></figure>
# Why sharing research products?

<figure><img src="image_23.png" /></figure>
# Why sharing research products?

<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /></figure>
# Why sharing research products?

<figure><img src="image_26.png" /></figure>

<figure><img src="image_27.png" /></figure>

Which release of
SPM was used?
# Why sharing research products?

<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

Which release of
SPM was used?

Which registration
algorithm was
selected?
# Why sharing research products?

<figure><img src="image_30.png" /></figure>

<figure><img src="image_31.png" /></figure>

Which release of
SPM was used?

Which registration
algorithm was
selected?

How was the brain
mask computed?
# Why sharing research products?

<figure><img src="image_32.png" /></figure>

1. It is a lot of work to restart from zero when trying to build on the results of a scientific paper

<figure><img src="image_33.png" /></figure>

Which release of SPM was used?

Which registration algorithm was selected?

How was the brain mask computed?
# Why sharing research products?

<figure><img src="image_34.png" /></figure>

<figure><img src="image_35.png" /></figure>

1. It is a lot of work to restart from zero when trying to build on the results of a scientific paper

Which release of SPM was used?

Which registration algorithm was selected?

How was the brain mask computed?

Hum... I can't reproduce the original results...
# Why sharing research products?

<figure><img src="image_36.png" /></figure>

<figure><img src="image_37.png" /></figure>

1. It is a lot of work to restart from zero when trying to build on the results of a scientific paper

Which release of SPM was used?

Which registration algorithm was selected?

How was the brain mask computed?

Hum... I can't reproduce the original results...

Did I understand the method correctly?
# Why sharing research products?

<figure><img src="image_38.png" /></figure>

<figure><img src="image_39.png" /></figure>

1. It is a lot of work to restart from zero when trying to build on the results of a scientific paper

Which release of SPM was used?

Which registration algorithm was selected?

How was the brain mask computed?

Hum... I can't reproduce the original results...

Did I understand the method correctly?

... or is this due to my use of a different dataset?
# Why sharing research products?

<figure><img src="image_40.png" /></figure>

<figure><img src="image_41.png" /></figure>

1. It is a lot of work to restart from zero when trying to build on the results of a scientific paper

Which release of SPM was used?

Which registration algorithm was selected?

How was the brain mask computed?

Hum... I can't reproduce the original results...

Did I understand the method correctly?

... or is this due to my use of a different dataset?

... a different computing platform?
# Why sharing research products?

<figure><img src="image_42.png" /></figure>

<figure><img src="image_43.png" /></figure>

1. It is a lot of work to restart from zero when trying to build on the results of a scientific paper

Which release of SPM was used?

Which registration algorithm was selected?

How was the brain mask computed?

Hum... I can't reproduce the original results...

Did I understand the method correctly?

... or is this due to my use of a different dataset?

... a different computing platform?

... something else!?
# Why sharing research products?

<figure><img src="image_44.png" /></figure>

<figure><img src="image_45.png" /></figure>

1. It is a lot of work to restart from zero when trying to build on the results of a scientific paper

Which release of SPM was used?

Which registration algorithm was selected?

How was the brain mask computed?

Hum... I can't reproduce the original results...

Did I understand the method correctly?

... or is this due to my use of a different dataset?

2. When results cannot be reproduced, it is often very difficult to understand why this is happening

... a different computing platform?

... something else!?
# How to share research products FAIRly
# FAIR neuroimaging

Findable Accessible Interoperable Reusable

<figure><img src="image_46.png" /></figure>
# FAIR neuroimaging

## Findable Accessible Interoperable Reusable

**Technical solutions:** Standards, Databases, Good practices (version control, etc.)

<figure><img src="image_47.png" /></figure>
# FAIR neuroimaging

Findable Accessible Interoperable Reusable

<figure><img src="image_48.png" /></figure>

**Technical solutions:** Standards, Databases, Good practices (version control, etc.)

**A culture change: towards community-driven research**

* Making resources available to the scientific community

* Reusing existing resources (datasets, tools) that were created by others
# Sharing FAIR research products

Acquisition

<figure><img src="image_49.png" /></figure>

Data preparation

<figure><img src="image_50.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_51.png" /></figure>

<figure><img src="image_52.png" /></figure>

<figure><img src="image_53.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

Acquisition

<figure><img src="image_54.png" /></figure>

Data preparation

<figure><img src="image_55.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_56.png" /></figure>

<figure><img src="image_57.png" /></figure>

<figure><img src="image_58.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

Acquisition

<figure><img src="image_59.png" /></figure>

Data preparation

<figure><img src="image_60.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_61.png" /></figure>

<figure><img src="image_62.png" /></figure>

<figure><img src="image_63.png" /></figure>

<figure><img src="image_64.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_65.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

Acquisition

<figure><img src="image_66.png" /></figure>

Data preparation

<figure><img src="image_67.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_68.png" /></figure>

<figure><img src="image_69.png" /></figure>

<figure><img src="image_70.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_71.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

Acquisition

<figure><img src="image_72.png" /></figure>

Data preparation

<figure><img src="image_73.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_74.png" /></figure>

<figure><img src="image_75.png" /></figure>

<figure><img src="image_76.png" /></figure>

<figure><img src="image_77.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_78.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR datasets

<figure><img src="image_79.png" /></figure>
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_80.png" /></figure>

<figure><img src="image_81.png" /></figure>

OpenNEURO

<figure><img src="image_82.png" /></figure>

<figure><img src="image_83.png" /></figure>

LORIS

<figure><img src="image_84.png" /></figure>

SHANOIR
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_85.png" /></figure>

<figure><img src="image_86.png" /></figure>

OpenNEURO

<figure><img src="image_87.png" /></figure>

<figure><img src="image_88.png" /></figure>

LORIS

<figure><img src="image_89.png" /></figure>

SHANOIR

<figure><img src="image_90.png" /></figure>

**Findable** we can search
for open datasets in each
repository
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_91.png" /></figure>

<figure><img src="image_92.png" /></figure>

OpenNEURO

<figure><img src="image_93.png" /></figure>

XNAT

<figure><img src="image_94.png" /></figure>

LORIS

<figure><img src="image_95.png" /></figure>

SHANOIR

<figure><img src="image_96.png" /></figure>

**Findable** we can search for open datasets in each repository

<figure><img src="image_97.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_98.png" /></figure>

<figure><img src="image_99.png" /></figure>

OpenNEURO

<figure><img src="image_100.png" /></figure>

XNAT

<figure><img src="image_101.png" /></figure>

<figure><img src="image_102.png" /></figure>

LORIS

<figure><img src="image_103.png" /></figure>

SHANOIR

<figure><img src="image_104.png" /></figure>

## Interoperable?

<figure><img src="image_105.png" /></figure>

**Findable** we can search for open datasets in each repository

<figure><img src="image_106.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Standards for neuroimaging data sharing

* Data and **meta-data**

* A common “language”

<figure><img src="image_107.png" /></figure>
# Brain Imaging Data Structure

## my_dataset/

<figure><img src="image_108.png" /></figure>

### participants.tsv

<figure><img src="image_109.png" /></figure>

### sub-01/

#### anat/

<figure><img src="image_110.png" /></figure>

### sub-01_T1w.nii.gz

#### func/

<figure><img src="image_111.png" /></figure>

### sub-01_task-rest bold.nii.gz

<figure><img src="image_112.png" /></figure>

### sub-01_task-rest bold.json

#### dwi/

<figure><img src="image_113.png" /></figure>

### sub-01_dwi.nii.gz

<figure><img src="image_114.png" /></figure>

### sub-01_dwi.json

<figure><img src="image_115.png" /></figure>

### sub-01_dwi.bval

<figure><img src="image_116.png" /></figure>

### sub-01_dwi.bvec

<figure><img src="image_117.png" /></figure>

### sub-02/

<figure><img src="image_118.png" /></figure>

### sub-03/

<figure><img src="image_119.png" /></figure>

### sub-04/

<figure><img src="image_120.png" /></figure>

https://openneuro.org/

[Gorgolewski et. al, Scientific Data 2016]
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_121.png" /></figure>

<figure><img src="image_122.png" /></figure>

OpenNEURO

<figure><img src="image_123.png" /></figure>

XNAT

<figure><img src="image_124.png" /></figure>

LORIS

<figure><img src="image_125.png" /></figure>

SHANOIR

<figure><img src="image_126.png" /></figure>

## Interoperable?

<figure><img src="image_127.png" /></figure>

**Findable** we can search for open datasets in each repository

<figure><img src="image_128.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_129.png" /></figure>

<figure><img src="image_130.png" /></figure>

<figure><img src="image_131.png" /></figure>

<figure><img src="image_132.png" /></figure>

<figure><img src="image_133.png" /></figure>

OpenNEURO

<figure><img src="image_134.png" /></figure>

<figure><img src="image_135.png" /></figure>

LORIS

<figure><img src="image_136.png" /></figure>

SHANOIR

<figure><img src="image_137.png" /></figure>

**Interoperable** BIDS acts
as a common languages
across tools

<figure><img src="image_138.png" /></figure>

**Findable** we can search
for open datasets in each
repository

<figure><img src="image_139.png" /></figure>

**Accessible** Direct
download (e.g. Openneuro)
or with Data User
Agreement (e.g. Donders)
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_140.png" /></figure>

<figure><img src="image_141.png" /></figure>

<figure><img src="image_142.png" /></figure>

<figure><img src="image_143.png" /></figure>

<figure><img src="image_144.png" /></figure>

OpenNEURO

<figure><img src="image_145.png" /></figure>

<figure><img src="image_146.png" /></figure>

LORIS

<figure><img src="image_147.png" /></figure>

SHANOIR

<figure><img src="image_148.png" /></figure>

**Interoperable** BIDS acts as a common language for tools across the field.

<figure><img src="image_149.png" /></figure>

**Findable** we can search for open datasets in each repository.

<figure><img src="image_150.png" /></figure>

**Reusable** Metadata in BIDS were selected to enable reuse. e.g. *onsets of the task for task-based fMRI*.

<figure><img src="image_151.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Sharing FAIR datasets

Donders Repository

<figure><img src="image_152.png" /></figure>

<figure><img src="image_153.png" /></figure>

<figure><img src="image_154.png" /></figure>

<figure><img src="image_155.png" /></figure>

<figure><img src="image_156.png" /></figure>

OpenNEURO

<figure><img src="image_157.png" /></figure>

<figure><img src="image_158.png" /></figure>

LORIS

<figure><img src="image_159.png" /></figure>

SHANOIR

<figure><img src="image_160.png" /></figure>

**Interoperable** BIDS acts as a common language for tools across the industry.

<figure><img src="image_161.png" /></figure>

**Findable** we can search for open datasets in each repository

<figure><img src="image_162.png" /></figure>

**Reusable** Metadata in BIDS were selected to enable reuse. e.g. *onsets of the task for task-based fMRI*.

<figure><img src="image_163.png" /></figure>

**Accessible** Direct download (e.g. Openneuro) or with Data User Agreement (e.g. Donders)
# Sharing FAIR research products

Acquisition

<figure><img src="image_164.png" /></figure>

Data preparation

<figure><img src="image_165.png" /></figure>

Derived data

Statistical analysis

<figure><img src="image_166.png" /></figure>

<figure><img src="image_167.png" /></figure>

<figure><img src="image_168.png" /></figure>

<figure><img src="image_169.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_170.png" /></figure>

Credits: Parcels 1, 2 & 4 (CCO), Parcel 3 (CCO), Parcel 5 (CCO).
# Sharing FAIR research products

<figure><img src="image_171.png" /></figure>

Credits: Parcels 1, 2 & 4 (CC0), Parcel 3 (CC0), Parcel 5 (CC0).
# Sharing FAIR research products

Acquisition

<figure><img src="image_172.png" /></figure>

<figure><img src="image_173.png" /></figure>

<figure><img src="image_174.png" /></figure>

<figure><img src="image_175.png" /></figure>

<figure><img src="image_176.png" /></figure>

Data preparation

<figure><img src="image_177.png" /></figure>

<figure><img src="image_178.png" /></figure>

Derived data

<figure><img src="image_179.png" /></figure>

Statistical analysis

<figure><img src="image_180.png" /></figure>

<figure><img src="image_181.png" /></figure>

<figure><img src="image_182.png" /></figure>

<figure><img src="image_183.png" /></figure>

<figure><img src="image_184.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_185.png" /></figure>

OpenNEURO

<figure><img src="image_186.png" /></figure>

LORIS

Donders Repository

<figure><img src="image_187.png" /></figure>

<figure><img src="image_188.png" /></figure>

SHANOIR

<figure><img src="image_189.png" /></figure>
# Sharing FAIR research products

<figure><img src="image_190.png" /></figure>

Donders Repository

<figure><img src="image_191.png" /></figure>

<figure><img src="image_192.png" /></figure>

<figure><img src="image_193.png" /></figure>

SHANOIR

<figure><img src="image_194.png" /></figure>

LORIS

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_195.png" /></figure>

Credits: Parcels 1, 2 & 4 (CC0), Parcel 3 (CC0), Parcel 5 (CC0).
Sharing FAIR results

<figure><img src="image_196.png" /></figure>
Sharing FAIR results (task fMRI)

<figure><img src="image_197.png" /></figure>

<figure><img src="image_198.png" /></figure>

<figure><img src="image_199.png" /></figure>

**NEUROVAULT**
# Sharing FAIR results (task fMRI)

<figure><img src="image_200.png" /></figure>

<figure><img src="image_201.png" /></figure>

<figure><img src="image_202.png" /></figure>

**NEUROVAULT**

<figure><img src="image_203.png" /></figure>

**Findable** we can search
for datasets on
NeuroVault

<figure><img src="image_204.png" /></figure>

**Accessible** Direct
download
# Sharing FAIR results (task fMRI)

<figure><img src="image_205.png" /></figure>

<figure><img src="image_206.png" /></figure>

<figure><img src="image_207.png" /></figure>

Interoperable?

<figure><img src="image_208.png" /></figure>

Findable we can search
for datasets on
NeuroVault

<figure><img src="image_209.png" /></figure>

Reusable?

<figure><img src="image_210.png" /></figure>

Accessible Direct
download
# NIDM-Results pack

<figure><img src="image_211.png" /></figure>

<figure><img src="image_212.png" /></figure>

NIDM-Results

.nidm.zip

<figure><img src="image_213.png" /></figure>

ClusterLabels.nii.gz

<figure><img src="image_214.png" /></figure>

Contrast.nii.gz

<figure><img src="image_215.png" /></figure>

ContrastStandardError.nii.gz

<figure><img src="image_216.png" /></figure>

DesignMatrix.csv

<figure><img src="image_217.png" /></figure>

DesignMatrix.png

<figure><img src="image_218.png" /></figure>

ExcursionSet.nii.gz

<figure><img src="image_219.png" /></figure>

ExcursionSet.png

<figure><img src="image_220.png" /></figure>

GrandMean.nii.gz

<figure><img src="image_221.png" /></figure>

Mask.nii.gz

<figure><img src="image_222.png" /></figure>

nidm.json

<figure><img src="image_223.png" /></figure>

nidm.ttl

<figure><img src="image_224.png" /></figure>

ParameterEstimate_001.nii.gz

<figure><img src="image_225.png" /></figure>

ParameterEstimate_002.nii.gz

<figure><img src="image_226.png" /></figure>

ResidualMeanSquares.nii.gz

<figure><img src="image_227.png" /></figure>

SearchSpaceMask.nii.gz

<figure><img src="image_228.png" /></figure>

TStatistic.nii.gz

<figure><img src="image_229.png" /></figure>

ZStatistic.nii.gz

<figure><img src="image_230.png" /></figure>

<figure><img src="image_231.png" /></figure>

Design of the experiment, pre-processed data...

<figure><img src="image_232.png" /></figure>

Statistical estimation

<figure><img src="image_233.png" /></figure>

Effects, standard error and statistical maps...

<figure><img src="image_234.png" /></figure>

Inference

<figure><img src="image_235.png" /></figure>

Thresholded maps, list of peaks and clusters...

<figure><img src="image_236.png" /></figure>
# NIDM in SPM, FSL & NeuroVault

## SPM

<figure><img src="image_237.png" /></figure>

### 1. Export

<figure><img src="image_238.png" /></figure>

$ nidmfsl fsl_ds107_group 49 -g Control

### 2. Publication on NeuroVault

NIDM-Results

<figure><img src="image_239.png" /></figure>

<figure><img src="image_240.png" /></figure>
# Meta-analysis w/ NIDM-Results

<figure><img src="image_241.png" /></figure>

## Coordinate-based meta-analysis

<figure><img src="image_242.png" /></figure>

## Image-based meta-analysis

<figure><img src="image_243.png" /></figure>
# Sharing FAIR results (task fMRI)

<figure><img src="image_244.png" /></figure>

<figure><img src="image_245.png" /></figure>

<figure><img src="image_246.png" /></figure>

<figure><img src="image_247.png" /></figure>

<figure><img src="image_248.png" /></figure>

**NEUROVAULT**

<figure><img src="image_249.png" /></figure>

**Interoperable** NIDM-Results acts as a common languages across tools

<figure><img src="image_250.png" /></figure>

**Findable** we can search for datasets on NeuroVault

<figure><img src="image_251.png" /></figure>

**Reusable** Metadata in NIDM-Results selected to enable meta-analyses

<figure><img src="image_252.png" /></figure>

**Accessible** Direct download
# Sharing FAIR results (task fMRI)

<figure><img src="image_253.png" /></figure>

<figure><img src="image_254.png" /></figure>

<figure><img src="image_255.png" /></figure>

<figure><img src="image_256.png" /></figure>

<figure><img src="image_257.png" /></figure>

**NEUROVAULT**

<figure><img src="image_258.png" /></figure>

**Interoperable** NIDM-Results acts as a common languages across tools

<figure><img src="image_259.png" /></figure>

**Findable** we can search for datasets on NeuroVault

<figure><img src="image_260.png" /></figure>

**Reusable** Metadata in NIDM-Results selected to enable meta-analyses

<figure><img src="image_261.png" /></figure>

**Accessible** Direct download
# Sharing FAIR research products

<figure><img src="image_262.png" /></figure>

NEUROVAULT
# Sharing FAIR research products

<figure><img src="image_263.png" /></figure>

NEUROVAULT
# Sharing FAIR research products

Acquisition

<figure><img src="image_264.png" /></figure>

<figure><img src="image_265.png" /></figure>

<figure><img src="image_266.png" /></figure>

<figure><img src="image_267.png" /></figure>

<figure><img src="image_268.png" /></figure>

Data preparation

<figure><img src="image_269.png" /></figure>

Derived data

<figure><img src="image_270.png" /></figure>

Statistical analysis

<figure><img src="image_271.png" /></figure>

<figure><img src="image_272.png" /></figure>

<figure><img src="image_273.png" /></figure>

<figure><img src="image_274.png" /></figure>

LORIS

Donders Repository

<figure><img src="image_275.png" /></figure>

<figure><img src="image_276.png" /></figure>

SHANOIR

<figure><img src="image_277.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_278.png" /></figure>

<figure><img src="image_279.png" /></figure>

<figure><img src="image_280.png" /></figure>

NEUROVAULT
# Sharing FAIR intermediary datasets

<figure><img src="image_281.png" /></figure>

Derived data
# Sharing FAIR intermediary datasets

<figure><img src="image_282.png" /></figure>

Derived data

<figure><img src="image_283.png" /></figure>

NITRC

zenodo

General purpose repositories
# Sharing FAIR intermediary datasets

<figure><img src="image_284.png" /></figure>

Derived data

<figure><img src="image_285.png" /></figure>

NITRC

<figure><img src="image_286.png" /></figure>

zenodo

General purpose repositories

<figure><img src="image_287.png" /></figure>

**Findable** can search for open datasets (less specific queries)

<figure><img src="image_288.png" /></figure>

**Accessible** Direct download or Data User Agreement
# Sharing FAIR intermediary datasets

<figure><img src="image_289.png" /></figure>

Derived data

<figure><img src="image_290.png" /></figure>

NITRC

<figure><img src="image_291.png" /></figure>

zenodo

General purpose repositories

<figure><img src="image_292.png" /></figure>

**Findable** can search for
open datasets (less
specific queries)

<figure><img src="image_293.png" /></figure>

**Accessible** Direct
download or Data User
Agreement
# Sharing FAIR intermediary datasets

<figure><img src="image_294.png" /></figure>

Derived data

<figure><img src="image_295.png" /></figure>

<figure><img src="image_296.png" /></figure>

<figure><img src="image_297.png" /></figure>

<figure><img src="image_298.png" /></figure>

NITRC

zenodo

General purpose repositories

<figure><img src="image_299.png" /></figure>

**Interoperable?**

<figure><img src="image_300.png" /></figure>

**Findable** can search for
open datasets (less
specific queries)

<figure><img src="image_301.png" /></figure>

**Reusable?**

<figure><img src="image_302.png" /></figure>

**Accessible** Direct
download or Data User
Agreement
# Sharing other FAIR datasets

1. Look for existing standards and databases.

FAIR sharing.org
standards, databases, policies

2. You can help develop the next standards

## BIDS Derivatives

https://bids.neuroimaging.io/

Derivatives are outputs of common processing pipelines, capturing data and meta-data sufficient for a researcher to understand and (critically) reuse those outputs in subsequent processing.

Standardizing derivatives is motivated by use cases where formalized machine-readable access to processed data enables higher level processing.

* BEP011 The structural preprocessing derivatives

* BEP012 The functional preprocessing derivatives

* BEP013 The resting state fMRI derivatives

* BEP016 The diffusion weighted imaging derivatives

* BEP017 Generic BIDS connectivity data schema

* BEP021 Common Electrophysiological Derivatives

And more!
<figure><img src="image_303.png" /></figure>

Satra
Ghosh

# BIDS Provenance

<figure><img src="image_304.png" /></figure>

BIDS

BRAIN IMAGING DATA STRUCTURE

<figure><img src="image_305.png" /></figure>

A) fMRI preprocessing using SPM

<figure><img src="image_306.png" /></figure>

B) fMRI preprocessing using
fMRIPrep

<figure><img src="image_307.png" /></figure>

Two examples of BIDS-Prov graphs with A) a detailed and B) a compact graph representing the derived data provenance.

https://github.com/bids-standard/BEP028_BIDSprov
# Sharing FAIR research products

<figure><img src="image_308.png" /></figure>
# Sharing FAIR research products

Acquisition

<figure><img src="image_309.png" /></figure>

<figure><img src="image_310.png" /></figure>

<figure><img src="image_311.png" /></figure>

<figure><img src="image_312.png" /></figure>

<figure><img src="image_313.png" /></figure>

Data preparation

<figure><img src="image_314.png" /></figure>

<figure><img src="image_315.png" /></figure>

Derived data

<figure><img src="image_316.png" /></figure>

<figure><img src="image_317.png" /></figure>

Statistical analysis

<figure><img src="image_318.png" /></figure>

<figure><img src="image_319.png" /></figure>

OpenNEURO

<figure><img src="image_320.png" /></figure>

LORIS

Donders Repository

<figure><img src="image_321.png" /></figure>

<figure><img src="image_322.png" /></figure>

SHANOIR

<figure><img src="image_323.png" /></figure>

NITRC

<figure><img src="image_324.png" /></figure>

zenodo

<figure><img src="image_325.png" /></figure>

<figure><img src="image_326.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_327.png" /></figure>

<figure><img src="image_328.png" /></figure>

<figure><img src="image_329.png" /></figure>

<figure><img src="image_330.png" /></figure>

NEUROVAULT

<figure><img src="image_331.png" /></figure>
# Sharing FAIR research products

<figure><img src="image_332.png" /></figure>

NEUROVAULT
# Sharing FAIR research products

Acquisition

<figure><img src="image_333.png" /></figure>

<figure><img src="image_334.png" /></figure>

<figure><img src="image_335.png" /></figure>

<figure><img src="image_336.png" /></figure>

Data preparation

<figure><img src="image_337.png" /></figure>

Derived data

<figure><img src="image_338.png" /></figure>

Statistical analysis

<figure><img src="image_339.png" /></figure>

<figure><img src="image_340.png" /></figure>

<figure><img src="image_341.png" /></figure>

<figure><img src="image_342.png" /></figure>

<figure><img src="image_343.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_344.png" /></figure>

OpenNEURO

<figure><img src="image_345.png" /></figure>

LORIS

Donders Repository

<figure><img src="image_346.png" /></figure>

<figure><img src="image_347.png" /></figure>

SHANOIR

<figure><img src="image_348.png" /></figure>

NITRC

zenodo

<figure><img src="image_349.png" /></figure>

<figure><img src="image_350.png" /></figure>

NEUROVAULT
# Sharing analysis code

Data preparation

<figure><img src="image_351.png" /></figure>

GitLab

<figure><img src="image_352.png" /></figure>

Statistical analysis

<figure><img src="image_353.png" /></figure>

GitHub

<figure><img src="image_354.png" /></figure>

Software Heritage

<figure><img src="image_355.png" /></figure>

## Different requirements for sharing code compared to datasets

* Often already stored in **online repositories** (e.g. Github, Gitlab)

* Many versions (commits)

* Long term preservation is also important!

* Code structure, README

```
|-- CITATION
|-- README
|-- LICENSE
|-- requirements.txt
|-- data
|   `-- birds_count_table.csv
|-- doc
|   `-- notebook.md
|   `-- manuscript.md
|   `-- changelog.txt
|-- results
|   `-- summarized_results.csv
|-- src
|   `-- sightings_analysis.py
|   `-- runall.py
```
# Sharing FAIR research products

Acquisition

<figure><img src="image_356.png" /></figure>

Data preparation

<figure><img src="image_357.png" /></figure>

Derived data

<figure><img src="image_358.png" /></figure>

Statistical analysis

<figure><img src="image_359.png" /></figure>

<figure><img src="image_360.png" /></figure>

<figure><img src="image_361.png" /></figure>

<figure><img src="image_362.png" /></figure>

<figure><img src="image_363.png" /></figure>

<figure><img src="image_364.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_365.png" /></figure>

NITRC

zenodo

<figure><img src="image_366.png" /></figure>

<figure><img src="image_367.png" /></figure>

OpenNEURO

<figure><img src="image_368.png" /></figure>

LORIS

<figure><img src="image_369.png" /></figure>

Software Heritage

<figure><img src="image_370.png" /></figure>

Donders Repository

<figure><img src="image_371.png" /></figure>

<figure><img src="image_372.png" /></figure>

SHANOIR

<figure><img src="image_373.png" /></figure>

NEUROVAULT
# Sharing FAIR research products

<figure><img src="image_374.png" /></figure>

NEUROVAULT
# Sharing FAIR research products

Acquisition

<figure><img src="image_375.png" /></figure>

<figure><img src="image_376.png" /></figure>

<figure><img src="image_377.png" /></figure>

<figure><img src="image_378.png" /></figure>

Data preparation

<figure><img src="image_379.png" /></figure>

<figure><img src="image_380.png" /></figure>

Derived data

<figure><img src="image_381.png" /></figure>

<figure><img src="image_382.png" /></figure>

Statistical analysis

<figure><img src="image_383.png" /></figure>

<figure><img src="image_384.png" /></figure>

<figure><img src="image_385.png" /></figure>

<figure><img src="image_386.png" /></figure>

<figure><img src="image_387.png" /></figure>

<figure><img src="image_388.png" /></figure>

<figure><img src="image_389.png" /></figure>

Biorxiv, arxiv, HAL, Pubmed

<figure><img src="image_390.png" /></figure>

NITRC

<figure><img src="image_391.png" /></figure>

OpenNEURO

<figure><img src="image_392.png" /></figure>

LORIS

<figure><img src="image_393.png" /></figure>

Software Heritage

Donders Repository

<figure><img src="image_394.png" /></figure>

<figure><img src="image_395.png" /></figure>

SHANOIR

<figure><img src="image_396.png" /></figure>

zenodo

<figure><img src="image_397.png" /></figure>

<figure><img src="image_398.png" /></figure>

NEUROVAULT
Ready?
Let's get started!

* **You can choose.** Pick one or two research outputs for sharing (e.g. code, results).

* **You can share subparts.** Sharing only the code to build your figures or part of your results (e.g. manually delineated lesion masks).

* When you feel more comfortable, consider **'working open' all the way**, it will make sharing easier later on.

* Connect with the community and help advance FAIR research outputs on the topics you love.

Pick what you like the best!
## Sharing research products FAIRly

<figure><img src="image_399.png" /></figure>

Camille Maumet

Thank you!

<figure><img src="image_400.png" /></figure>

We are hiring! Join us to
investigate pipeline-induced
variability in an
#openscience-friendly environment

https://team.inria.fr/empenn/job-offers/