## 3 Methodology  
### Ontology-Based Design Science Research Engineering (ODSRE) Methodology  
This section emphasizes the importance of integrating diverse data and knowledge and its evaluation within the _Design Science_ (DS) [57] discipline, particularly highlighting the value of combining _Design Science Research Methodology_ (DSRM) [24] and the _Ontology Engineering_ (OE) [58] paradigms [9]. The DS methodology helps to address practical real-time cases of legacy data source integration and resolve semantic interoperability challenges for frequent access in standardized form for developing domain-centric service, especially in the healthcare industry [4]. The primary goal of merging DSR and OE is to assess new digital artifacts inspired by theoretical knowledge design [59]. We customized DSR and OE _hybrid methodology_ (ODSRE) artifacts to construct an FVKG framework using the _\"Ontop\"_ platform, focusing on the design and creation of _Enterprise Knowledge Graphs_ (EKGs) specific to the healthcare industry. This approach supports four key themes: (i) understanding the contextual knowledge, (ii) use of legacy systems such as _Electronic Health Records_ (EHRs), (iii) information sharing (_explicit knowledge_), (iv) knowledge dissemination either in tacit or implicit knowledge and access through data acquisition techniques such as modeling workshops, following steps [60] with domain experts and a focal group. Figure 1 demonstrates an ontology engineering cycle that encompasses DSR activities. First, the _Knowledge Acquisition_ (KA) phase begins by focusing on two key parameters: detailed understanding of the domain knowledge and contextual knowledge. The KA process is initiated through collaborative modeling workshop sessions with domain experts guided by specific activities [60]. Second, in the problem investigation phase, we examine in-depth information related to data integration, access and semantic interoperability challenges. We also identify relevant theories, methods, and existing solutions to mitigate the aforementioned data-driven challenges using semantic technologies and their representation in standardized form for data exchange. Figure 1: Hybrid methodology ontology-based design science research engineering (ODSRE). (**a**) The ontology engineering life cycle embedded with design science research methodology paradigms; (**b**) the number of activities that help to develop a customized ontology mapped to the requirements of domain contextual knowledge. Third, in the objective definition phase, we concentrated on gathering specific requirements and defining key tasks to develop reasoning mechanisms to address particular challenges, particularly within the healthcare domain. Fourth, the design phase focused on creating digital artifacts and outlining how the integration is to be achieved and managed in the standardized form to resolve data interoperability issues using semantic techniques such as ontologies, knowledge graphs, and virtual platforms such as Ontop. Fifth, the development phase is dedicated to the creation of digital artifacts. Sixth, in the evaluation phase, these digital artifacts are assessed based on predefined criteria [59] grounded in design science research method activities [61]. Similarly, _Ontology Engineering_ (OE) is defined as \"a set of activities that link with the ontology development process, its life cycle, and the methodologies, tools and languages for building ontologies\" [4; 62]. In Figure 1, the OE activities are carried out using ontology development methodologies such as Methontology [63] and Tove [64; 65]. Activities 1 and 2: Problem Investigation and Motivation for Heterogeneous Data Collection--Construct Artifact  
The healthcare context of Cardiovascular Diseases (CVDs) plays a crucial role in this research. It aims to develop customized domain-centric ontology-driven digital artifacts (e.g., cardiovascular disease ontology) and prototypes demonstrating advanced methods for tackling data integration, access, and interoperability challenges in healthcare settings.