

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 Article de journal
Dans: Future Internet, vol. 17, no 6, 2025, ISSN: 19995903 (ISSN), (Publisher: Multidisciplinary Digital Publishing Institute (MDPI)).
Résumé | Liens | BibTeX | Étiquettes: 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},
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}
}
Nabelsi, V.; Gagnon, S.
Detecting constraints in supply chain reengineering projects: Case study of data and process integration in a hospital pharmacy Article d'actes
Dans: A., Zaremba M. Sasiadek J. Dolgui (Ed.): IFAC-PapersOnLine, p. 106–111, 2015, ISBN: 24058963 (ISSN), (Issue: 3 Journal Abbreviation: IFAC-PapersOnLine).
Résumé | Liens | BibTeX | Étiquettes: Administrative data processing, Artificial intelligence, Business Process, Business process management, Business process management (BPM), Business process re-engineering, Case-studies, Data integration, Data mining, Data models, Data structures, Data warehouses, Decision support system, Decision support system (dss), Decision support systems, Enterprise resource management, Extract transform and load, Extract Transform and Load (ETL), Hospitals, Information management, Integration, Process management, Project case, Re-engineering projects, Reengineering, Supply chain management, Supply Chain Management (SCM), Supply chain managements (SCM), System architectures, Verification method, Verification of information system
@inproceedings{nabelsi_detecting_2015,
title = {Detecting constraints in supply chain reengineering projects: Case study of data and process integration in a hospital pharmacy},
author = {V. Nabelsi and S. Gagnon},
editor = {Zaremba M. Sasiadek J. Dolgui A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953887968&doi=10.1016%2fj.ifacol.2015.06.066&partnerID=40&md5=ce9be2cbe2fdcfc4872793c13f4228a2},
doi = {10.1016/j.ifacol.2015.06.066},
isbn = {24058963 (ISSN)},
year = {2015},
date = {2015-01-01},
booktitle = {IFAC-PapersOnLine},
volume = {28},
pages = {106–111},
abstract = {This paper discusses how messy data may be a hidden failure factor that Business Process Reengineering (BPR) projects typically cannot detect during the planning phase. Our case study deals with Supply Chain Management (SCM) within two major urban hospitals, involving $2 million in minimum stocks for drug inventory. Our project addresses the feasibility of the hospital's data warehousing integration, especially at the stage of Extract, Transform, and Load (ETL). We conclude with a proposed system architecture audit and verification method that may serve to guide reengineering project planning and execution. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},
note = {Issue: 3
Journal Abbreviation: IFAC-PapersOnLine},
keywords = {Administrative data processing, Artificial intelligence, Business Process, Business process management, Business process management (BPM), Business process re-engineering, Case-studies, Data integration, Data mining, Data models, Data structures, Data warehouses, Decision support system, Decision support system (dss), Decision support systems, Enterprise resource management, Extract transform and load, Extract Transform and Load (ETL), Hospitals, Information management, Integration, Process management, Project case, Re-engineering projects, Reengineering, Supply chain management, Supply Chain Management (SCM), Supply chain managements (SCM), System architectures, Verification method, Verification of information system},
pubstate = {published},
tppubtype = {inproceedings}
}