

de Recherche et d’Innovation
en Cybersécurité et Société
Fareedi, A. A.; Gagnon, S.; Ghazawneh, A.; Valverde, R.
Semantic Fusion of Health Data: Implementing a Federated Virtualized Knowledge Graph Framework Leveraging Ontop System Journal Article
In: Future Internet, vol. 17, no. 6, 2025, ISSN: 19995903 (ISSN), (Publisher: Multidisciplinary Digital Publishing Institute (MDPI)).
Abstract | Links | BibTeX | Tags: Data integration, Data interoperability, Federated information systems, Federated ontology, Graph framework, Interoperability, Knowledge graphs, Knowledge management, Medical computing, Ontology, Ontology's, Ontop, Query processing, Semantic interoperability, Semantic Web, Semantics, Virtual knowledge, virtual reality, Virtualization, Virtualized knowledge graph
@article{fareedi_semantic_2025,
title = {Semantic Fusion of Health Data: Implementing a Federated Virtualized Knowledge Graph Framework Leveraging Ontop System},
author = {A. A. Fareedi and S. Gagnon and A. Ghazawneh and R. Valverde},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105009278332&doi=10.3390%2ffi17060245&partnerID=40&md5=72bd14d033887f72e7e0c8a6a1451415},
doi = {10.3390/fi17060245},
issn = {19995903 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Future Internet},
volume = {17},
number = {6},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
abstract = {Data integration (DI) and semantic interoperability (SI) are critical in healthcare, enabling seamless, patient-centric data sharing across systems to meet the demand for instant, unambiguous access to health information. Federated information systems (FIS) highlight auspicious issues for seamless DI and SI stemming from diverse data sources or models. We present a hybrid ontology-based design science research engineering (ODSRE) methodology that combines design science activities with ontology engineering principles to address the above-mentioned issues. The ODSRE constructs a systematic mechanism leveraging the Ontop virtual paradigm to establish a state-of-the-art federated virtual knowledge graph framework (FVKG) embedded virtualized knowledge graph approach to mitigate the aforementioned challenges effectively. The proposed FVKG helps construct a virtualized data federation leveraging the Ontop semantic query engine that effectively resolves data bottlenecks. Using a virtualized technique, the FVKG helps to reduce data migration, ensures low latency and dynamic freshness, and facilitates real-time access while upholding integrity and coherence throughout the federation system. As a result, we suggest a customized framework for constructing ontological monolithic semantic artifacts, especially in FIS. The proposed FVKG incorporates ontology-based data access (OBDA) to build a monolithic virtualized repository that integrates various ontological-driven artifacts and ensures semantic alignments using schema mapping techniques. © 2025 by the authors.},
note = {Publisher: Multidisciplinary Digital Publishing Institute (MDPI)},
keywords = {Data integration, Data interoperability, Federated information systems, Federated ontology, Graph framework, Interoperability, Knowledge graphs, Knowledge management, Medical computing, Ontology, Ontology's, Ontop, Query processing, Semantic interoperability, Semantic Web, Semantics, Virtual knowledge, virtual reality, Virtualization, Virtualized knowledge graph},
pubstate = {published},
tppubtype = {article}
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Lopes, M. K. S.; Falk, T. H.
Generative AI for Personalized Multisensory Immersive Experiences: Challenges and Opportunities for Stress Reduction Proceedings Article
In: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW, pp. 143–146, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 979-833151484-6 (ISBN), (Journal Abbreviation: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW).
Abstract | Links | BibTeX | Tags: Artificial intelligence tools, Environment personalization, Forest bathing, Generative AI, Immersive, Multi-Sensory, Multi-sensory virtual reality, Multisensory, Personalizations, relaxation, virtual reality, Virtualization
@inproceedings{lopesGenerativeAIPersonalized2025,
title = {Generative AI for Personalized Multisensory Immersive Experiences: Challenges and Opportunities for Stress Reduction},
author = {M. K. S. Lopes and T. H. Falk},
url = {https://www.scopus.com/pages/publications/105005149501?origin=resultslist},
doi = {10.1109/VRW66409.2025.00036},
isbn = {979-833151484-6 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW},
pages = {143–146},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Stress management and relaxation are critical areas of interest in mental health and well-being. Forest bathing is a practice that has been shown to have a positive effect on reducing stress by stimulating all the senses in an immersive nature experience. Since access to nature is not universally available to everyone, virtual reality has emerged as a promising tool to simulate this type of experience. Furthermore, generative artificial intelligence (GenAI) tools offer new opportunities to create highly personalized and immersive experiences that can enhance relaxation and reduce stress. This study explores the potential of personalized multisensory VR environments, designed using GenAI tools, to optimize relaxation and stress relief via two experiments that are currently underway. The first evaluates the effectiveness of non-personalized versus personalized VR scenes generated using AI tools to promote increased relaxation. The second explores the potential benefits of providing the user with additional personalization tools, from adding new virtual elements to the AI-generated scene, to adding AI-generated sounds and scent/haptics customization. Ultimately, this research aims to identify which customizable elements may lead to improved therapeutic benefits for multisensory VR experiences. © 2025 IEEE.},
note = {Journal Abbreviation: Proc. - IEEE Conf. Virtual Real. 3D User Interfaces Abstr. Workshops, VRW},
keywords = {Artificial intelligence tools, Environment personalization, Forest bathing, Generative AI, Immersive, Multi-Sensory, Multi-sensory virtual reality, Multisensory, Personalizations, relaxation, virtual reality, Virtualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Fareedi, A. A.; Gagnon, S.; Ghazawneh, A.; Valverde, R.
Semantic Fusion of Health Data: Implementing a Federated Virtualized Knowledge Graph Framework Leveraging Ontop System Journal Article
In: Future Internet, vol. 17, no. 6, 2025, ISSN: 19995903 (ISSN).
Abstract | Links | BibTeX | Tags: Data integration, Data interoperability, Federated information systems, Federated ontology, Graph framework, Interoperability, Knowledge graphs, Knowledge management, Medical computing, Ontology, Ontology's, Ontop, Query processing, Semantic interoperability, Semantic Web, Semantics, Virtual knowledge, virtual reality, Virtualization, Virtualized knowledge graph
@article{fareediSemanticFusionHealth2025a,
title = {Semantic Fusion of Health Data: Implementing a Federated Virtualized Knowledge Graph Framework Leveraging Ontop System},
author = {A. A. Fareedi and S. Gagnon and A. Ghazawneh and R. Valverde},
url = {https://www.scopus.com/pages/publications/105009278332?origin=resultslist},
doi = {10.3390/fi17060245},
issn = {19995903 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Future Internet},
volume = {17},
number = {6},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
abstract = {Data integration (DI) and semantic interoperability (SI) are critical in healthcare, enabling seamless, patient-centric data sharing across systems to meet the demand for instant, unambiguous access to health information. Federated information systems (FIS) highlight auspicious issues for seamless DI and SI stemming from diverse data sources or models. We present a hybrid ontology-based design science research engineering (ODSRE) methodology that combines design science activities with ontology engineering principles to address the above-mentioned issues. The ODSRE constructs a systematic mechanism leveraging the Ontop virtual paradigm to establish a state-of-the-art federated virtual knowledge graph framework (FVKG) embedded virtualized knowledge graph approach to mitigate the aforementioned challenges effectively. The proposed FVKG helps construct a virtualized data federation leveraging the Ontop semantic query engine that effectively resolves data bottlenecks. Using a virtualized technique, the FVKG helps to reduce data migration, ensures low latency and dynamic freshness, and facilitates real-time access while upholding integrity and coherence throughout the federation system. As a result, we suggest a customized framework for constructing ontological monolithic semantic artifacts, especially in FIS. The proposed FVKG incorporates ontology-based data access (OBDA) to build a monolithic virtualized repository that integrates various ontological-driven artifacts and ensures semantic alignments using schema mapping techniques. © 2025 by the authors.},
keywords = {Data integration, Data interoperability, Federated information systems, Federated ontology, Graph framework, Interoperability, Knowledge graphs, Knowledge management, Medical computing, Ontology, Ontology's, Ontop, Query processing, Semantic interoperability, Semantic Web, Semantics, Virtual knowledge, virtual reality, Virtualization, Virtualized knowledge graph},
pubstate = {published},
tppubtype = {article}
}
Fareedi, A. A.; Gagnon, S.; Ghazawneh, A.; Valverde, R.
Semantic Fusion of Health Data: Implementing a Federated Virtualized Knowledge Graph Framework Leveraging Ontop System Journal Article
In: Future Internet, vol. 17, no. 6, 2025, ISSN: 19995903 (ISSN).
Abstract | Links | BibTeX | Tags: Data integration, Data interoperability, Federated information systems, Federated ontology, Graph framework, Interoperability, Knowledge graphs, Knowledge management, Medical computing, Ontology, Ontology's, Ontop, Query processing, Semantic interoperability, Semantic Web, Semantics, Virtual knowledge, virtual reality, Virtualization, Virtualized knowledge graph
@article{fareediSemanticFusionHealth2025b,
title = {Semantic Fusion of Health Data: Implementing a Federated Virtualized Knowledge Graph Framework Leveraging Ontop System},
author = {A. A. Fareedi and S. Gagnon and A. Ghazawneh and R. Valverde},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105009278332&doi=10.3390%2Ffi17060245&partnerID=40&md5=8f53ce5a912bf16f4ac8bb24fb7338bf},
doi = {10.3390/fi17060245},
issn = {19995903 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Future Internet},
volume = {17},
number = {6},
abstract = {Data integration (DI) and semantic interoperability (SI) are critical in healthcare, enabling seamless, patient-centric data sharing across systems to meet the demand for instant, unambiguous access to health information. Federated information systems (FIS) highlight auspicious issues for seamless DI and SI stemming from diverse data sources or models. We present a hybrid ontology-based design science research engineering (ODSRE) methodology that combines design science activities with ontology engineering principles to address the above-mentioned issues. The ODSRE constructs a systematic mechanism leveraging the Ontop virtual paradigm to establish a state-of-the-art federated virtual knowledge graph framework (FVKG) embedded virtualized knowledge graph approach to mitigate the aforementioned challenges effectively. The proposed FVKG helps construct a virtualized data federation leveraging the Ontop semantic query engine that effectively resolves data bottlenecks. Using a virtualized technique, the FVKG helps to reduce data migration, ensures low latency and dynamic freshness, and facilitates real-time access while upholding integrity and coherence throughout the federation system. As a result, we suggest a customized framework for constructing ontological monolithic semantic artifacts, especially in FIS. The proposed FVKG incorporates ontology-based data access (OBDA) to build a monolithic virtualized repository that integrates various ontological-driven artifacts and ensures semantic alignments using schema mapping techniques. © 2025 by the authors.},
keywords = {Data integration, Data interoperability, Federated information systems, Federated ontology, Graph framework, Interoperability, Knowledge graphs, Knowledge management, Medical computing, Ontology, Ontology's, Ontop, Query processing, Semantic interoperability, Semantic Web, Semantics, Virtual knowledge, virtual reality, Virtualization, Virtualized knowledge graph},
pubstate = {published},
tppubtype = {article}
}
Fareedi, A. A.; Gagnon, S.; Ghazawneh, A.; Valverde, R.
Semantic Fusion of Health Data: Implementing a Federated Virtualized Knowledge Graph Framework Leveraging Ontop System Journal Article
In: Future Internet, vol. 17, no. 6, 2025, ISSN: 19995903 (ISSN).
Abstract | Links | BibTeX | Tags: Data integration, Data interoperability, Federated information systems, Federated ontology, Graph framework, Interoperability, Knowledge graphs, Knowledge management, Medical computing, Ontology, Ontology's, Ontop, Query processing, Semantic interoperability, Semantic Web, Semantics, Virtual knowledge, virtual reality, Virtualization, Virtualized knowledge graph
@article{fareediSemanticFusionHealth2025,
title = {Semantic Fusion of Health Data: Implementing a Federated Virtualized Knowledge Graph Framework Leveraging Ontop System},
author = {A. A. Fareedi and S. Gagnon and A. Ghazawneh and R. Valverde},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105009278332&doi=10.3390%2ffi17060245&partnerID=40&md5=72bd14d033887f72e7e0c8a6a1451415},
doi = {10.3390/fi17060245},
issn = {19995903 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Future Internet},
volume = {17},
number = {6},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
abstract = {Data integration (DI) and semantic interoperability (SI) are critical in healthcare, enabling seamless, patient-centric data sharing across systems to meet the demand for instant, unambiguous access to health information. Federated information systems (FIS) highlight auspicious issues for seamless DI and SI stemming from diverse data sources or models. We present a hybrid ontology-based design science research engineering (ODSRE) methodology that combines design science activities with ontology engineering principles to address the above-mentioned issues. The ODSRE constructs a systematic mechanism leveraging the Ontop virtual paradigm to establish a state-of-the-art federated virtual knowledge graph framework (FVKG) embedded virtualized knowledge graph approach to mitigate the aforementioned challenges effectively. The proposed FVKG helps construct a virtualized data federation leveraging the Ontop semantic query engine that effectively resolves data bottlenecks. Using a virtualized technique, the FVKG helps to reduce data migration, ensures low latency and dynamic freshness, and facilitates real-time access while upholding integrity and coherence throughout the federation system. As a result, we suggest a customized framework for constructing ontological monolithic semantic artifacts, especially in FIS. The proposed FVKG incorporates ontology-based data access (OBDA) to build a monolithic virtualized repository that integrates various ontological-driven artifacts and ensures semantic alignments using schema mapping techniques. © 2025 by the authors.},
keywords = {Data integration, Data interoperability, Federated information systems, Federated ontology, Graph framework, Interoperability, Knowledge graphs, Knowledge management, Medical computing, Ontology, Ontology's, Ontop, Query processing, Semantic interoperability, Semantic Web, Semantics, Virtual knowledge, virtual reality, Virtualization, Virtualized knowledge graph},
pubstate = {published},
tppubtype = {article}
}



