Validation

Introduction

The validation module provides a way to validate data against a set of rules.

Methods

The following methods are available in the validate module. Each method is described in detail below.

Validate Folder Structure

You can call the validate_folder_structure method to validate the data needed to create a dataset_description file.

Required or optional files

Following files are required to have inside the directory path:

• dataset_description.json
• participants.json
• participants.tsv
• README.md
• CHANGELOG.md
• LICENSE.md

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Returns

Field	Type	Description
valid	Boolean	Returns True if the dataset is valid, False otherwise.
errors	List	List of validation errors (blocking issues).
warnings	List	List of validation warnings (non-blocking issues).

How to use

from pyfairdatatools import validate

folder_path = "/dataset_path"

output = validate.validate_folder_structure(folder_path=folder_path)

print(output)  # True

Validate Dataset Description

You can call the validate_dataset_description method to validate the data needed to create a dataset_description file.

Parameters

data

Provide the data required for your dataset_description file in this paramater.

Type	Default value	Required	Accepted values
Object	{}	yes	Data object following the required schemas

More information about the required data can be found in the dataset_description schema.

You can the hosted validator here if you want a better understanding or visualization of the schema for the input.

Returns

Type	Description
Boolean	Returns True if the data is valid, False otherwise.

How to use

from pyfairdatatools import validate

data  = {
    "title": "My Dataset",
    "identifier": "10.5281/zenodo.1234567",
    "identifierType": "DOI"
}

output = validate.validate_dataset_description(data = data)

print(output)  # True

Validate Study Description

You can call the validate_study_description method to validate the data needed to create a study_description file.

Parameters

data

Provide the data required for your study_description file in this paramater.

Type	Default value	Required	Accepted values
Object	{}	yes	Data object following the required schemas

More information about the required data can be found in the study_description schema.

You can host the validator here if you want a better understanding or visualization of the schema for the input.

Returns

Type	Description
Boolean	Returns True if the data is valid, False otherwise.

How to use

from pyfairdatatools import validate

data  = {
    "Title": "My Dataset",
    "Identifier": "10.5281/zenodo.1234567",
    "IdentifierType": "DOI"
}

output = validate.validate_study_description(data = data)

print(output)  # True

Validate Readme

You can call the validate_readme method to validate the data needed to create a README file.

Parameters

data

Provide the data required for your README file in this paramater.

Type	Default value	Required	Accepted values
Object	{}	yes	Data object following the required schemas

More information about the required data can be found in the README schema.

You can host the validator here if you want a better understanding or visualization of the schema for the input.

Returns

Type	Description
Boolean	Returns True if the data is valid, False otherwise.

How to use

from pyfairdatatools import validate

data  = {
    "title": "My Dataset",
    "identifier": "10.5281/zenodo.1234567",
    "version": "1.0.0",
}

output = validate.validate_readme(data = data)

print(output)  # True

Validate License

You can call the validate_license method to validate the data needed to create a LICENSE file.

Parameters

identifier

Provide the identifier of the license you want to validate.

Type	Default value	Required	Accepted values
String	""	yes	SPDX license identifier

For a list of all SPDX license identifiers, see here.

Returns

Type	Description
Boolean	Returns True if the data is valid, False otherwise.

How to use

from pyfairdatatools import validate

identifier = "CC-BY-4.0"

output = validate.validate_license(identifier = identifier)

print(output)  # True

Validate Participants

You can call the validate_participants method to validate the data needed to create a participants.tsv file.

Parameters

data

Provide the data required for your participants.tsv file in this paramater.

Type	Default value	Required	Accepted values
Object	{}	yes	Data object following the required schemas

More information about the required data can be found in the participants schema.

You can host the validator here if you want a better understanding or visualization of the schema for the input.

Returns

Type	Description
Boolean	Returns True if the data is valid, False otherwise.

How to use

from pyfairdatatools import validate

data = {
    "participant_id": 'sub-id1',
    "species": 'rattus norvegicus',
    "age": 2
}

output = validate.validate_participants(data = data)

print(output)  # True