In the Netherlands, women aged 50-75 years are invited to receive breast cancer screening every two years. The PRISMA (Personalised RISk-based MAmmascreening) study was designed to investigate the added value of risk-based mammography screening. 43,000 screened women completed a web-based questionnaire comprising established risk factors and PROMs for breast cancer. There is no universally accepted data model for the collection of breast cancer risk factors. Objective: To reduce unambiguity of data schemas in the domain To contribute to global efforts to increase secondary use of patient-reported outcomes through FAIRification Solution: Step 1. 43,000 screened women completed a web-based questionnaire comprising established risk factors and PROMs for breast cancer. Step 2. After several inventory meetings with different stakeholders, a consensus was reached on which data elements were important criteria to discover, share and reuse the PRISMA data. The resulting 70 data elements were grouped into 17 main classes Linked Data representations for each CDE were constructed, by mapping to existing ontological terms Step 3. The data elements identified in the PRISMA study can be instantiated according to the core elements (role, entity, process, measurement, attribute) in SIO and connected using the established property. Added Value: FAIR data model, a potential template for breast cancer research groups to other PROMs and Real-World Experience questionnaires. Next steps: create use cases that the PRISMA semantic data schema can support consider the interoperability with other standard, like the electronic health record (EHR)

Funding: 1. The Netherlands X-omics Initiative is (partially) funded by the Dutch Research Council (NWO), project 184.034.019. 2. The PRISMA Studies is partially funded by the Dutch Cancer Society (KWF; Grant 12522).