# A Knowledge Graph Framework for Dementia Research Data
## 3 Materials and Methods  
### Termological Foundation  
In the construction of the knowledge graph, the initial and pivotal decision revolves around selecting an appropriate graph schema to provide a solid conceptual base that effectively captures data entities drawn from the array of biological subdomains pertinent to dementia research. This choice presents a dichotomy: one option involves creating a flexible, ad hoc schema tailored to the identified needs, while the alternative entails adopting a more structured strategy that employs standard terminologies and ontologies. Our methodology aligns with the latter approach, and a fundamental design principle in the construction of our KG is the utilization of domain reference ontologies to ensure the following:1. The concept definitions are concise, accurate, and relevant;
2. There exists an active community keeping the ontology updated;
3. They are widely recognized, cross-referenced, and follow consistent design patterns. The criteria set forth are congruent with the guiding principles of the OBO foundry. OBO endorses an extensive range of domain-specific ontologies that are distinguished by well-demarcated scopes, the reutilization of concepts across ontologies, and alignment with a unified upper-level model, specifically the Basic Formal Ontology (BFO) [50], and relations are defined in the Relations Ontology (RO). Given these attributes, we gave preferential consideration to OBO ontologies during our selection process. As the KG must cater to a variety of domains, adopting this approach enables us to concentrate mainly on integration and only define new terms when detecting a gap. Some notable examples of the employed OBO ontologies include the Gene Ontology [51, 52], Chemical Entities of Biological Interest (CHEBI) [53], and Protein Ontology (PR) [54] for the genetic and molecular domain. For the phenotype and disease domain, we utilize the Monarch Disease Ontology (MONDO) [55], Human Phenotype Ontology (HP) [56, 57], and Phenotype And Trait Ontology (PATO) [58]. In the area of anatomy, we incorporate the Uber-Anatomy Ontology (UBERON) [59, 60] and the Foundational Model of Anatomy (FMA) [61]. For neuropsychological tests and their relations, we include the Neuropsychological Testing Ontology (NPT) [62] and the Neurocognitive Integrated Ontology (NIO) [63]. For modeling experimental settings, the Ontology for Biomedical Investigations (OBI) [64, 65] plays a central role. These ontologies provide a significant level of detail, and reusing or referencing concepts between them expands the knowledge network, facilitating the exploitation of multi-domain and multi-level relations. For example, this interconnectedness simplifies navigation from HP phenotypes referenced in a disease definition in MONDO to specific genes in GO, proteins in PR, and molecular entities in CHEBI. Furthermore, we also include relevant Monarch data and annotation ingestions; specifically, gene and gene-phenotype annotations, filtered protein-protein interactions from the STRING database [66], and pathway knowledge from the Reactome pathway knowledgebase [67]. The complete list of knowledge sources and annotations is listed in Table 1. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Source** & **Source Identifier** & **Reference** \\ \hline Basic Formal Ontology & BFO & [50] \\ Biolink model & biolink & [36] \\ Chemical Entities of Biological & CHEBI & [53] \\ Interest & Cell Ontology & CL & [68] \\ Evidence and Conclusion & ECO & [69] \\ Ontology & Environmental Factor & EFO & [70] \\ Ontology & Gene Ontology & GO & [52] \\ Gene Ontology Annotations & GOA & - \\ Human Phenotype Ontology & HP & [57] \\ Human Phenotype Ontology & HPOA & - \\ Annotations & Information Artifact Ontology & IAO & - \\ \hline \hline \end{tabular}
\end{table} 
Table 1: List of DemKG knowledge sources. While the standardization offered by domain ontologies is undoubtedly a strength, it can also impose limitations due to the inherent trade-off with flexibility.