@article{fareedi_digital_2025,

title = {Digital Health Transformation: Leveraging a Knowledge Graph Reasoning Framework and Conversational Agents for Enhanced Knowledge Management},

author = {A. A. Fareedi and M. Ismail and S. Gagnon and A. Ghazanweh and Z. Arooj},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85218906224&doi=10.3390%2fsystems13020072&partnerID=40&md5=53b218763023a1bec3d69899d4dd7a86},

doi = {10.3390/systems13020072},

issn = {20798954 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {Systems},

volume = {13},

number = {2},

publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},

abstract = {The research focuses on the limitations of traditional systems in optimizing information flow in the healthcare domain. It focuses on integrating knowledge graphs (KGs) and utilizing AI-powered applications, specifically conversational agents (CAs), particularly during peak operational hours in emergency departments (EDs). Leveraging the Cross Industry Standard Process for Data Mining (CRISP-DM) framework, the authors tailored a customized methodology, CRISP-knowledge graph (CRISP-KG), designed to harness KGs for constructing an intelligent knowledge base (KB) for CAs. This KG augmentation empowers CAs with advanced reasoning, knowledge management, and context awareness abilities. We utilized a hybrid method integrating a participatory design collaborative methodology (CM) and Methontology to construct a domain-centric robust formal ontological model depicting and mapping information flow during peak hours in EDs. The ultimate objective is to empower CAs with intelligent KBs, enabling seamless interaction with end users and enhancing the quality of care within EDs. The authors leveraged semantic web rule language (SWRL) to enhance inferencing capabilities within the KG framework further, facilitating efficient information management for assisting healthcare practitioners and patients. This innovative assistive solution helps efficiently manage information flow and information provision during peak hours. It also leads to better care outcomes and streamlined workflows within EDs. © 2025 by the authors.},

note = {Publisher: Multidisciplinary Digital Publishing Institute (MDPI)},

keywords = {conversational agent, CRISP-KG, Knowledge graphs, ontologies, SWRL},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{azzi_ontology-driven_2023,

title = {Ontology-Driven Parliamentary Analytics: Analysing Political Debates on COVID-19 Impact in Canada},

author = {S. Azzi and S. Gagnon},

editor = {Asemi A. Francesconi E. Ko A.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172088757&doi=10.1007%2f978-3-031-39841-4_7&partnerID=40&md5=5dff3b672c36c66070042a35eed048e0},

doi = {10.1007/978-3-031-39841-4_7},

issn = {03029743},

year  = {2023},

date = {2023-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {14149 LNCS},

pages = {89–102},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {Parliamentary debates are usually published in Parliament’s websites to allows citizens to be informed on the latest national debates, proposals and decisions. To enhance citizen experience and engagement, functionalities such as debates annotation and question answering are necessary. Annotating text requires semantic content and ontologies are known for their ability to describe a common vocabulary for a domain and can be a solid base for annotation and question answering. We report on an ongoing study to enhance parliamentary analytics using an ontology and knowledge graph to sharpen annotations and facilitate their query by end-users. As a salient case, a sample of debates are collected on the COVID-19 impact in Canada, as its complexity shows the relevance of using advanced knowledge representation techniques. We focused on the development of a new “Impact of COVID-19 in Canada Ontology” (ICCO) that provides contextualized semantic information on impact in numerous policy areas, as this ontology is entirely built from Canadian parliamentary debates. It has been evaluated and validated by experts. Our conclusion underscores the importance of integrating ontology-driven parliamentary analytics within the broader context of digital transformation in legislative institutions, and the need for new platforms supporting free and open Digital Humanities. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.},

note = {ISBN: 9783031398407},

keywords = {COVID-19, End-users, Knowledge graph, Knowledge graphs, Ontology, Ontology graphs, Ontology's, Parliamentary debate, Political debates, Question Answering, Semantic content, Semantic ontology, Semantics, Solid basis},

pubstate = {published},

tppubtype = {article}

}