Modality agnostic files
Contents
Modality agnostic files#
Dataset description#
Templates:
dataset_description.json
README
CHANGES
LICENSE
dataset_description.json
#
The file dataset_description.json
is a JSON file describing the dataset.
Every dataset MUST include this file with the following fields:
Key name | Requirement Level | Data type | Description |
---|---|---|---|
{term}Name (metadata) |
REQUIRED | string | Name of the dataset. |
{term}BIDSVersion (metadata) |
REQUIRED | string | The version of the BIDS standard that was used. |
{term}HEDVersion (metadata) |
RECOMMENDED | string | If HED tags are used: The version of the HED schema used to validate HED tags for study. |
{term}DatasetType (metadata) |
RECOMMENDED | string | The interpretation of the dataset. For backwards compatibility, the default value is "raw" . Must be one of: "raw" , "derivative" . |
{term}License (metadata) |
RECOMMENDED | string | The license for the dataset. The use of license name abbreviations is RECOMMENDED for specifying a license (see Appendix II). The corresponding full license text MAY be specified in an additional LICENSE file. |
{term}Authors (metadata) |
OPTIONAL | array of strings | List of individuals who contributed to the creation/curation of the dataset. |
{term}Acknowledgements (metadata) |
OPTIONAL | string | Text acknowledging contributions of individuals or institutions beyond those listed in Authors or Funding. |
{term}HowToAcknowledge (metadata) |
OPTIONAL | string | Text containing instructions on how researchers using this dataset should acknowledge the original authors. This field can also be used to define a publication that should be cited in publications that use the dataset. |
{term}Funding (metadata) |
OPTIONAL | array of strings | List of sources of funding (grant numbers). |
{term}EthicsApprovals (metadata) |
OPTIONAL | array of strings | List of ethics committee approvals of the research protocols and/or protocol identifiers. |
{term}ReferencesAndLinks (metadata) |
OPTIONAL | array of strings | List of references to publications that contain information on the dataset. A reference may be textual or a URI. |
{term}DatasetDOI (metadata) |
OPTIONAL | string | The Digital Object Identifier of the dataset (not the corresponding paper). DOIs SHOULD be expressed as a valid URI; bare DOIs such as 10.0.2.3/dfjj.10 are DEPRECATED. |
{term}GeneratedBy (metadata) |
RECOMMENDED | array of objects | Used to specify provenance of the dataset. |
{term}SourceDatasets (metadata) |
RECOMMENDED | array of objects | Used to specify the locations and relevant attributes of all source datasets. Valid keys in each object include "URL" , "DOI" (see URI), and "Version" with string values. |
Each object in the GeneratedBy
array includes the following REQUIRED, RECOMMENDED
and OPTIONAL keys:
Key name |
Requirement level |
Data type |
Description |
---|---|---|---|
Name |
REQUIRED |
Name of the pipeline or process that generated the outputs. Use |
|
Version |
RECOMMENDED |
Version of the pipeline. |
|
Description |
OPTIONAL |
Plain-text description of the pipeline or process that generated the outputs. RECOMMENDED if |
|
CodeURL |
OPTIONAL |
URL where the code used to generate the dataset may be found. |
|
Container |
OPTIONAL |
Used to specify the location and relevant attributes of software container image used to produce the dataset. Valid keys in this object include |
Example:
{
"Name": "The mother of all experiments",
"BIDSVersion": "1.6.0",
"DatasetType": "raw",
"License": "CC0",
"Authors": [
"Paul Broca",
"Carl Wernicke"
],
"Acknowledgements": "Special thanks to Korbinian Brodmann for help in formatting this dataset in BIDS. We thank Alan Lloyd Hodgkin and Andrew Huxley for helpful comments and discussions about the experiment and manuscript; Hermann Ludwig Helmholtz for administrative support; and Claudius Galenus for providing data for the medial-to-lateral index analysis.",
"HowToAcknowledge": "Please cite this paper: https://www.ncbi.nlm.nih.gov/pubmed/001012092119281",
"Funding": [
"National Institute of Neuroscience Grant F378236MFH1",
"National Institute of Neuroscience Grant 5RMZ0023106"
],
"EthicsApprovals": [
"Army Human Research Protections Office (Protocol ARL-20098-10051, ARL 12-040, and ARL 12-041)"
],
"ReferencesAndLinks": [
"https://www.ncbi.nlm.nih.gov/pubmed/001012092119281",
"Alzheimer A., & Kraepelin, E. (2015). Neural correlates of presenile dementia in humans. Journal of Neuroscientific Data, 2, 234001. doi:1920.8/jndata.2015.7"
],
"DatasetDOI": "doi:10.0.2.3/dfjj.10",
"HEDVersion": "8.0.0",
"GeneratedBy": [
{
"Name": "reproin",
"Version": "0.6.0",
"Container": {
"Type": "docker",
"Tag": "repronim/reproin:0.6.0"
}
}
],
"SourceDatasets": [
{
"URL": "s3://dicoms/studies/correlates",
"Version": "April 11 2011"
}
]
}
Derived dataset and pipeline description#
As for any BIDS dataset, a dataset_description.json
file MUST be found at the
top level of every derived dataset:
<dataset>/derivatives/<pipeline_name>/dataset_description.json
.
In contrast to raw BIDS datasets, derived BIDS datasets MUST include a
GeneratedBy
key:
If a derived dataset is stored as a subdirectory of the raw dataset, then the Name
field
of the first GeneratedBy
object MUST be a substring of the derived dataset directory name.
That is, in a directory <dataset>/derivatives/<pipeline>[-<variant>]/
, the first
GeneratedBy
object should have a Name
of <pipeline>
.
Example:
{
"Name": "FMRIPREP Outputs",
"BIDSVersion": "1.6.0",
"DatasetType": "derivative",
"GeneratedBy": [
{
"Name": "fmriprep",
"Version": "1.4.1",
"Container": {
"Type": "docker",
"Tag": "poldracklab/fmriprep:1.4.1"
}
},
{
"Name": "Manual",
"Description": "Re-added RepetitionTime metadata to bold.json files"
}
],
"SourceDatasets": [
{
"DOI": "doi:10.18112/openneuro.ds000114.v1.0.1",
"URL": "https://openneuro.org/datasets/ds000114/versions/1.0.1",
"Version": "1.0.1"
}
]
}
README
#
A REQUIRED text file, README
, SHOULD describe the dataset in more detail.
The README
file MUST be either in ASCII or UTF-8 encoding and MAY have one of the extensions:
.md
(Markdown),
.rst
(reStructuredText),
or .txt
.
A BIDS dataset MUST NOT contain more than one README
file (with or without extension)
at its root directory.
BIDS does not make any recommendations with regards to the
Markdown flavor
and does not validate the syntax of Markdown and reStructuredText.
The README
file SHOULD be structured such that its contents can be easily understood
even if the used format is not rendered.
A guideline for creating a good README
file can be found in the
bids-starter-kit.
CHANGES
#
Version history of the dataset (describing changes, updates and corrections) MAY
be provided in the form of a CHANGES
text file. This file MUST follow the
CPAN Changelog convention.
The CHANGES
file MUST be either in ASCII or UTF-8 encoding.
Example:
1.0.1 2015-08-27
- Fixed slice timing information.
1.0.0 2015-08-17
- Initial release.
LICENSE
#
A LICENSE
file MAY be provided in addition to the short specification of the
used license in the dataset_description.json
"License"
field.
The "License"
field and LICENSE
file MUST correspond.
The LICENSE
file MUST be either in ASCII or UTF-8 encoding.
Participants file#
Template:
participants.tsv
participants.json
The purpose of this RECOMMENDED file is to describe properties of participants
such as age, sex, handedness, species and strain.
If this file exists, it MUST contain the column participant_id
,
which MUST consist of sub-<label>
values identifying one row for each participant,
followed by a list of optional columns describing participants.
Each participant MUST be described by one and only one row.
The RECOMMENDED species
column SHOULD be a binomial species name from the
NCBI Taxonomy
(for examples homo sapiens
, mus musculus
, rattus norvegicus
).
For backwards compatibility, if species
is absent, the participant is assumed to be
homo sapiens
.
Commonly used optional columns in participants.tsv
files are age
, sex
,
handedness
, strain
, and strain_rrid
. We RECOMMEND to make use
of these columns, and in case that you do use them, we RECOMMEND to use the
following values for them:
Throughout BIDS you can indicate missing values with n/a
(for “not
available”).
participants.tsv
example:
participant_id age sex handedness group
sub-01 34 M right read
sub-02 12 F right write
sub-03 33 F n/a read
It is RECOMMENDED to accompany each participants.tsv
file with a sidecar
participants.json
file to describe the TSV column names and properties of their values (see also
the section on tabular files).
Such sidecar files are needed to interpret the data, especially so when
optional columns are defined beyond age
, sex
, handedness
, species
, strain
,
and strain_rrid
, such as group
in this example, or when a different
age unit is needed (for example, gestational weeks).
If no units
is provided for age, it will be assumed to be in years relative
to date of birth.
participants.json
example:
{
"age": {
"Description": "age of the participant",
"Units": "years"
},
"sex": {
"Description": "sex of the participant as reported by the participant",
"Levels": {
"M": "male",
"F": "female"
}
},
"handedness": {
"Description": "handedness of the participant as reported by the participant",
"Levels": {
"left": "left",
"right": "right"
}
},
"group": {
"Description": "experimental group the participant belonged to",
"Levels": {
"read": "participants who read an inspirational text before the experiment",
"write": "participants who wrote an inspirational text before the experiment"
}
}
}
Samples file#
Template:
samples.tsv
samples.json
The purpose of this file is to describe properties of samples, indicated by the sample
entity.
This file is REQUIRED if sample-<label>
is present in any filename within the dataset.
Each sample MUST be described by one and only one row.
samples.tsv
example:
sample_id participant_id sample_type derived_from
sample-01 sub-01 tissue n/a
sample-02 sub-01 tissue sample-01
sample-03 sub-01 tissue sample-01
sample-04 sub-02 tissue n/a
sample-05 sub-02 tissue n/a
It is RECOMMENDED to accompany each samples.tsv
file with a sidecar
samples.json
file to describe the TSV column names and properties of their values
(see also the section on tabular files).
samples.json
example:
{
"sample_type": {
"Description": "type of sample from ENCODE Biosample Type (https://www.encodeproject.org/profiles/biosample_type)",
},
"derived_from": {
"Description": "sample_id from which the sample is derived"
}
}
Phenotypic and assessment data#
Template:
phenotype/
<measurement_tool_name>.tsv
<measurement_tool_name>.json
Optional: Yes
If the dataset includes multiple sets of participant level measurements (for
example responses from multiple questionnaires) they can be split into
individual files separate from participants.tsv
.
Each of the measurement files MUST be kept in a /phenotype
directory placed
at the root of the BIDS dataset and MUST end with the .tsv
extension.
File names SHOULD be chosen to reflect the contents of the file.
For example, the “Adult ADHD Clinical Diagnostic Scale” could be saved in a file
called /phenotype/acds_adult.tsv
.
The files can include an arbitrary set of columns, but one of them MUST be
participant_id
and the entries of that column MUST correspond to the subjects
in the BIDS dataset and participants.tsv
file.
As with all other tabular data, the additional phenotypic information files MAY be accompanied by a JSON file describing the columns in detail (see Tabular files).
In addition to the column descriptions, the JSON file MAY contain the following fields:
As an example, consider the contents of a file called
phenotype/acds_adult.json
:
{
"MeasurementToolMetadata": {
"Description": "Adult ADHD Clinical Diagnostic Scale V1.2",
"TermURL": "https://www.cognitiveatlas.org/task/id/trm_5586ff878155d"
},
"adhd_b": {
"Description": "B. CHILDHOOD ONSET OF ADHD (PRIOR TO AGE 7)",
"Levels": {
"1": "YES",
"2": "NO"
}
},
"adhd_c_dx": {
"Description": "As child met A, B, C, D, E and F diagnostic criteria",
"Levels": {
"1": "YES",
"2": "NO"
}
}
}
Please note that in this example MeasurementToolMetadata
includes information
about the questionnaire and adhd_b
and adhd_c_dx
correspond to individual
columns.
In addition to the keys available to describe columns in all tabular files
(LongName
, Description
, Levels
, Units
, and TermURL
) the
participants.json
file as well as phenotypic files can also include column
descriptions with a Derivative
field that, when set to true, indicates that
values in the corresponding column is a transformation of values from other
columns (for example a summary score based on a subset of items in a
questionnaire).
Scans file#
Template:
sub-<label>/
[ses-<label>/]
sub-<label>[_ses-<label>]_scans.tsv
sub-<label>[_ses-<label>]_scans.json
Optional: Yes
The purpose of this file is to describe timing and other properties of each imaging acquisition sequence (each run file) within one session.
Each neural recording file SHOULD be described by exactly one row.
Some recordings consist of multiple parts, that span several files,
for example through echo-
, part-
, or split-
entities.
Such recordings MUST be documented with one row per file.
Additional fields can include external behavioral measures relevant to the
scan.
For example vigilance questionnaire score administered after a resting
state scan.
All such included additional fields SHOULD be documented in an accompanying
_scans.json
file that describes these fields in detail
(see Tabular files).
Example _scans.tsv
:
filename acq_time
func/sub-control01_task-nback_bold.nii.gz 1877-06-15T13:45:30
func/sub-control01_task-motor_bold.nii.gz 1877-06-15T13:55:33
meg/sub-control01_task-rest_split-01_meg.nii.gz 1877-06-15T12:15:27
meg/sub-control01_task-rest_split-02_meg.nii.gz 1877-06-15T12:15:27
Sessions file#
Template:
sub-<label>/
sub-<label>_sessions.tsv
Optional: Yes
In case of multiple sessions there is an option of adding additional
sessions.tsv
files describing variables changing between sessions.
In such case one file per participant SHOULD be added.
These files MUST include a session_id
column and describe each session by one and only one row.
Column names in sessions.tsv
files MUST be different from group level participant key column names in the
participants.tsv
file.
_sessions.tsv
example:
session_id acq_time systolic_blood_pressure
ses-predrug 2009-06-15T13:45:30 120
ses-postdrug 2009-06-16T13:45:30 100
ses-followup 2009-06-17T13:45:30 110
Code#
Template: code/*
Source code of scripts that were used to prepare the dataset MAY be stored here. Examples include anonymization or defacing of the data, or the conversion from the format of the source data to the BIDS format (see source vs. raw vs. derived data). Extra care should be taken to avoid including original IDs or any identifiable information with the source code. There are no limitations or recommendations on the language and/or code organization of these scripts at the moment.