A FOXS stack assembles HL7 FHIR, openEHR, IHE XDS and SNOMED CT as an operational clinical data platform to build digital systems. This paper analyses its applicability for FAIR-enabled medical research based on a summary of key principles. It highlights the benefit of the blended approach to operational technology stacks for health systems, and a need for industry standard technologies to enable greater semantic coherence for primary/secondary data use.
Magnetic flux leakage (MFL) is a technique commonly used to inspect storage tank floors. This paper describes a practical evaluation of the effect of scanning velocity on defect detection in mild steel plates with thicknesses of 6 mm, 12 mm and 16 mm using a fixed permanent magnetic
yoke. Each plate includes four semi-spherical defects ranging from 20% to 80% through-wall thickness. It was found that scanning velocity has a direct effect on defect characterisation due to the distorted magnetic field resulting from induced eddy currents that affect the MFL signal amplitude.
This occurs when the inspection velocity is increased and a reduction in the MFL signal amplitudes is observed for far-surface defects. The opposite applies for the top surface, where an increase is seen for near-surface MFL amplitudes when there is insufficient flux saturating the inspection
material due to the concentration of induced flux near the top surface. These findings suggest that procedures should be altered to minimise these effects based on inspection requirements. For thicker plates and when far-surface defects are of interest, inspection speeds should be reduced.
If only near-surface defects are being considered then increased speeds can be used, provided that the sensor range is sufficient to cope with the increased signal amplitudes so that signal clipping does not become an issue.
Background: FAIR Guiding Principles present a synergy with the use cases for digital health records, in that clinical data needs to be found, accessible within a range of environments, data must interoperate between systems and subsequently reused. The use of HL7 FHIR, openEHR, IHE XDS and SNOMED CT (FOXS) together represent a specification to create an open digital health platform for modern healthcare applications.
Objectives: To describe where logical FOXS components align to the European Open Science Cloud Interoperability Framework (EOSC-IF) reference architecture for semantic interoperability. This should provide a means of defining if FOXS aligns to FAIR principles and establish the data models and structures that support longitudinal care records as being fit to underpin scientific research.
Methods: The EOSC-IF Semantic View is a representation of semantic interoperability where meaning is preserved between systems and users. This was analysed and cross referenced with FOXS architectural components, mapping concepts and objects that describe content such as catalogues and semantic artefacts.
Results: Majority of conceptual Semantic View components were featured within FOXS architecture. Semantic Business Objects are composed of a range of elements such as openEHR archetypes and templates, FHIR resources and profiles, SNOMED CT concepts and XDS document identifiers. Semantic Functional Content comprises of catalogues of metadata were also supported by openEHR and FHIR tools.
Conclusions: Despite some elements of EOSC-IF being vague (e.g., FAIR Digital Object), there was a broad conformance to the framework concepts and the components of a FOXS platform. This work supports a health domain specific view of semantic interoperability, and how this may be achieved to support FAIR data for health research via a standardised framework.
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