A Modular Strategy to Build a Large-Scale Functional Status Knowledge Graph

Functional Status Information (FSI), which contains data on activity performance, social role involvement, and environmental and individual variables that influence well-being and quality of life, depicts physical and mental wellness at the level of the complete person. To effectively care for people with chronic diseases, multi-morbidity, and disabilities as well as to fulfill the demands of an aging global population, it is imperative to collect and analyze this data. Personal knowledge graphs (PKGs) are a useful method for displaying all data pertaining to a person’s FSI in a thorough and organized manner, as well as for reasoning over them to create custom coaching solutions assisting people in everyday life for leading a healthy lifestyle. We outline the development approach of the FuS-KG, a PKG to make possible the construction of AI-enabled systems aiming to raise people’s awareness of their own functional state. In particular, we emphasize the modular structure of FuS-KG designed for enhancing the scalability, management, understandability, and reuse of such a PKG.