FAIR-Aware

FAIR-Aware

The purpose of this page is to show how ODAM combined with a reference data repository such as French Research Data Warehouse (FRDW) based on Dataverse can answer all the essential questions that data curators must ask themselves. All these questions (i.e. vigilance points) are gathered in the FAIR-Aware questionnaire designed in the framework of the FAIR-FAIR project.

Findable

Vigilance points	At what level	How to respond
A data(set) should be assigned a globally unique persistent and resolvable identifier when deposited with a data repository	Dataverse	Once the data set is created, FRDW generates a DOI.
When you deposit a data(set) in a data repository, you will need to provide discovery metadata in order to make the data(set) findable, understandable and reusable to others	Dataverse	FRDW allows you to describe many metadata that can be used as search criteria to find the dataset
The data repository providing access to your data(set) should make the metadata describing your data(set) available in a format readable by machines as well as humans	Dataverse ODAM	Both repository allow you to export metadata in JSON format and in TSV format (ODAM) for structural metadata

Accessible

Vigilance points	At what level	How to respond
Access to your data(set) may need to be controlled and that metadata should include licence information under which the data(set) can be reused	Dataverse ODAM	Both repository allow you to control the access of the dataset (see Authorization mechanism). Idem for the licence information.
Metadata should remain available over time, even if the data(set) is no longer accessible	Dataverse	This is why it is preferable to deposit the structural metadata file (datapackage.json) instead of the data, which can be accessed directly from the ODAM API or via its dataexplorer.

Interoperable

Vigilance points	At what level	How to respond
The metadata describing your data(set) should use controlled vocabularies	Dataverse ODAM	FRDW proposes to annotate descriptive metadata using controlled vocabularies based on ontologies. In the same way ODAM allows the annotation of each data subset as well as each variable by open vocabulary (thesaurus and/or ontologies). (See Data preparation).

Reusable

Vigilance points	At what level	How to respond
Provenance information about the collection and/or generation of data should be included in the metadata	ODAM	ODAM allows you to add additional information either as text in markdown format or as PDF files (see Additional information)
Metadata describing your data(set) should follow the specifications of a community-endorsed standard	Dataverse ODAM	FRDW follows the JSON-LD specification for descriptive metadata while ODAM follows the Data Packages specification for structural metadata.
Your data(set) should be deposited preferably in a file format that is open and supported by the data repository for long-term preservation	ODAM	The data must have been recorded in TSV format as well as the structural metadata. (See Data preparation).
Keeping your data(set) FAIR over time requires professional data curation and digital preservation	Dataverse ODAM	FRDW is managed by a service directly attached to the management of the institute (DipSO). It is also preferable to install the ODAM application on an institutional server. Nevertheless, it is better if you can rely on people with data management skills i.e knowing how to collect data and information from producers and then how to prepare them for publication according to FAIR principles.