Table 5.

The FAIR Guiding Principles (from Wilkinson et al.).

Guiding Principle/Attribute	Definition	Adaptive trial example
Findable:	F1. (meta)data are assigned a globally unique and persistent identifier F2. data are described with rich metadata (defined by R1 below) F3. metadata clearly and explicitly include the identifier of the data it describes F4. (meta)data are registered or indexed in a searchable resource	After completion and publication of an adaptive trial, data are anonymized and deposited in a public repository (e.g. TCIA (64, 65)), and labeled with a permanent digital object identifier (DOI)(144). The DOI/repository and a data summary are then submitted as a data descriptor to a relevant journal (such as Medical Physics or Nature Scientific Data) and PubMed-indexed for easy searchability.
Accessible	A1. (meta)data are retrievable by their identifier using a standardized communications protocol A1.1 the protocol is open, free, and universally implementable A1.2 the protocol allows for an authentication and authorization procedure, where necessary A2. metadata are accessible, even when the data are no longer available	Other investigators, having located the data from PubMed or journal sites, can readily download the dataset from TCIA using the NBIA Data Retriever app (145) to query the permanent repository and download the anonymized image and dose data.
Interoperable	I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (meta)data use vocabularies that follow FAIR principles I3. (meta)data include qualified references to other (meta)data	Data from the adaptive trial, including all images, dose, and adaptive plans are stored using the DICOM-RT standard(146, 147). Additional clinical data and is either embedded within the DICOM header, referenced with relevant files/systems(140, 141), associated with semantic data (e.g. Resource Description Framework via the Radiation Oncology Ontology (48, 50, 51)framework) to allow the data to be used across multiple vendor and vendor neutral software(s) or for distributed learning.
Reusable	R1. meta(data) are richly described with a plurality of accurate and relevant attributes R1.1. (meta)data are released with a clear and accessible data usage license R1.2. (meta)data are associated with detailed provenance R1.3. (meta)data meet domain-relevant community standard	Using the aforementioned data, the adaptive protocol is reconstructed in silico, and used by several other sites to benchmark their internal adaptive processes and develop new segmentation and automated replanning approaches; the original data are cited in subsequent publications(148), and are widely a performance estimator for a new adaptive trial workflow development.