Simulation models in respiratory research are increasingly used for medical product development and testing, especially because in-vivo models are coupled with a high degree of complexity and ethical concerns. This work introduces a respiratory simulation system, which is bridging the gap between the complex, real anatomical environment and the safe, cost-effective simulation methods. The presented electro-mechanical lung simulator, xPULM, combines in-silico, ex-vivo and mechanical respiratory approaches by realistically replicating an actively breathing human lung. The reproducibility of sinusoidal breathing simulations with xPULM was verified for selected breathing frequencies (10–18 bpm) and tidal volumes (400–600 ml) physiologically occurring during human breathing at rest. Human lung anatomy was modelled using latex bags and primed porcine lungs. High reproducibility of flow and pressure characteristics was shown by evaluating breathing cycles (n_Total = 3273) with highest standard deviation |3σ| for both, simplified lung equivalents ( $${{\boldsymbol{\mu }}}_{\dot{{\bf{V}}}}$$µV̇ = 23.98 ± 1.04 l/min, μ_P = −0.78 ± 0.63 hPa) and primed porcine lungs ( $${{\boldsymbol{\mu }}}_{\dot{{\bf{V}}}}$$µV̇ = 18.87 ± 2.49 l/min, μ_P = −21.13 ± 1.47 hPa). The adaptability of the breathing simulation parameters, coupled with the use of porcine lungs salvaged from a slaughterhouse process, represents an advancement towards anatomically and physiologically realistic modelling of human respiration.

Interoperability in the Energy System is an important topic for the development of Smart Grids. In this paper we introduce a structured approach to solve the complex interoperability issues of connected systems and sub-systems based on experiences from the healthcare enterprise, where formerly rather closed systems were successfully migrated towards more open system. This approach combines well-established use case methodologies from the software development domain with benefits of the concept of integration profiles which can be found in the healthcare domain. The combination of the two methods is demonstrated by developing an integration profile for an application example from the Smart Grid domain; the virtual power plant operation use case. Using the presented method, a step-by-step guideline for implementers could be created. The profiling methodology seems to be an appropriate method to approach complex interoperability issues of Energy Systems and may be expanded to other fields.

The harmonization of the OMOP Common Data Model (CDM) with HL7 FHIR aims to enhance interoperability in clinical research by harmonizing diverse healthcare datasets. This process, referred to as OMOP-on-FHIR, leverages FHIR Bundles for real-time clinical data exchange and transforms these resources into OMOP CDM format using an ETL process. The ETL pipeline, facilitated by tools like XSLT, enables the extraction, transformation, and loading of data while maintaining semantic consistency. By bridging these two standards, OMOP-on-FHIR promotes the seamless exchange of data across clinical systems and research-oriented databases, supporting global health studies, advanced analytics, and personalized medicine. This methodology advances cross-border research by providing a standardized approach to data management and analysis, thereby improving healthcare outcomes.

EHealth (electronic health) and mHealth (mobile health) have been rapidly evolving in recent years, offering innovative solutions to healthcare challenges

BACKGROUND Standards for the secondary use of health data are still under development and do not comprehensively address specific categories of health data. Existing health data and interoperability standards are primarily designed for the primary use of healthcare, leaving gaps in their applicability for research, regulatory and decision-making. This research is part of the IDERHA project, which creates a federated processing environment for secondary healthcare use cases aligned with EHDS regulations. OBJECTIVE This study aims to recommend a set of standards and tools to support harmonization objectives in the secondary use of health data. The proposed standards establish a shared representation model for data providers and stakeholders, improving data FAIRness and interoperability. METHODS A comprehensive review and selection of standards and harmonization tools were performed across major health-data categories. Standards from OHDSI/OMOP, HL7 FHIR, DICOM, DCAT-AP/HealthDCAT-AP, GA4GH, INSPIRE, CDISC, and others were evaluated based on community adoption, technical suitability, and alignment with EHDS requirements. Data-harmonization tools were tested in a pilot experiment using synthetic OMOP-CDM based data to assess readiness, quality, and feasibility of applying harmonization workflows within IDERHA. We also assessed the inherent FAIRness of OMOP CDM, identifying its strengths in semantic interoperability and data reuse, while addressing limitations related to metadata discoverability, global identifiers, access control, and licensing through complementary mechanisms implemented in IDERHA. RESULTS In this research, we recommend a set of standards to support the secondary use of heterogeneous health data across clinical, imaging, genomic, socioeconomic, environmental, and PROM/PREM domains. This standards collection, centered on OMOP CDM and complemented by established domain-specific specifications, was paired with selected harmonization and quality-assessment tools from the OHDSI and EHDEN ecosystems. Feasibility testing on synthetic OMOP data confirmed the suitability of tools for evaluating data quality, mapping accuracy, and ETL. A lung-cancer use case demonstrated how diverse datasets can be harmonized and prepared for federated analysis. FAIR-DSM evaluation showed that integrating OMOP data into the IDERHA environment substantially improved FAIRness—particularly in metadata completeness, interoperability, and hosting capabilities—supporting enhanced discoverability, accessibility, and reuse of standardized health data. CONCLUSIONS By strengthening adherence to FAIR principles, this research facilitates the broader integration of standardized health data for regulatory processes and health technology assessment (HTA) applications. The proposed set of standards and tools provides a comprehensive overview of existing approaches, while offering solutions that can be applied to other scenarios involving the secondary use of health data.