  Healthcare providers face significant challenges with monitoring and managing
patient data outside of clinics, particularly with insufficient resources and
limited feedback on their patients' conditions. Effective management of these
symptoms and exploration of larger bodies of data are vital for maintaining
long-term quality of life and preventing late interventions. In this paper, we
propose a framework for constructing personal health knowledge graphs from
heterogeneous data sources. Our approach integrates clinical databases,
relevant ontologies and standard healthcare guidelines to support alert
generation, clinician interpretation and querying of patient data. Through a
use case of monitoring Chronic Obstructive Pulmonary Disease (COPD) patients,
we demonstrate that inference and reasoning on personal health knowledge graphs
built with our framework can aid in patient monitoring and enhance the efficacy
and accuracy of patient data queries.
