  This paper presents a data-centric and security-focused data fabric designed
for digital health applications. With the increasing interest in digital health
research, there has been a surge in the volume of Internet of Things (IoT) data
derived from smartphones, wearables, and ambient sensors. Managing this vast
amount of data, encompassing diverse data types and varying time scales, is
crucial. Moreover, compliance with regulatory and contractual obligations is
essential. The proposed data fabric comprises an architecture and a toolkit
that facilitate the integration of heterogeneous data sources, across different
environments, to provide a unified view of the data in dashboards. Furthermore,
the data fabric supports the development of reusable and configurable data
integration components, which can be shared as open-source or inner-source
software. These components are used to generate data pipelines that can be
deployed and scheduled to run either in the cloud or on-premises. Additionally,
we present the implementation of our data fabric in a home-based telemonitoring
research project involving older adults, conducted in collaboration with the
University of California, San Diego (UCSD). The study showcases the streamlined
integration of data collected from various IoT sensors and mobile applications
to create a unified view of older adults' health for further analysis and
research.
