FAIR data

rdf:langString FAIR data

rdf:langString GO FAIR

rdf:langString font-style:italic

rdf:langString Findable The first step in using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services, so this is an essential component of the FAIRification process. F1. data are assigned a globally unique and persistent identifier F2. Data are described with rich metadata F3. Metadata clearly and explicitly include the identifier of the data they describe F4. data are registered or indexed in a searchable resource Accessible Once the user finds the required data, they need to know how they can be accessed, possibly including authentication and authorisation. A1. data are retrievable by their identifier using a standardised communications protocol A1.1 The protocol is open, free, and universally implementable A1.2 The protocol allows for an authentication and authorisation procedure, where necessary A2. Metadata are accessible, even when the data are no longer available Interoperable The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing. I1. data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. data use vocabularies that follow FAIR principles I3. data include qualified references to other data Reusable The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings. R1. data are richly described with a plurality of accurate and relevant attributes R1.1. data are released with a clear and accessible data usage license R1.2. data are associated with detailed provenance R1.3. data meet domain-relevant community standards The principles refer to three types of entities: data , metadata , and infrastructure. For instance, principle F4 defines that both metadata and data are registered or indexed in a searchable resource .

rdf:langString FAIR Principles

rdf:langString FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability (FAIR). The acronym and principles were defined in a March 2016 paper in the journal Scientific Data by a consortium of scientists and organizations. The FAIR principles emphasize machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data. The abbreviation FAIR/O data is sometimes used to indicate that the dataset or database in question complies with the FAIR principles and also carries an explicit data‑capable open license.