Meaningful Integration of Data from Heterogeneous Health Services and Home Environment Based on Ontology

Abstract

The development of electronic health records, wearable devices, health applications and Internet of Things (IoT)-empowered smart homes is promoting various applications. It also makes health self-management much more feasible, which can partially mitigate one of the challenges that the current healthcare system is facing. Effective and convenient self-management of health requires the collaborative use of health data and home environment data from different services, devices, and even open data on the Web. Although health data interoperability standards including HL7 Fast Healthcare Interoperability Resources (FHIR) and IoT ontology including Semantic Sensor Network (SSN) have been developed and promoted, it is impossible for all the different categories of services to adopt the same standard in the near future. This study presents a method that applies Semantic Web technologies to integrate the health data and home environment data from heterogeneously built services and devices. We propose a Web Ontology Language (OWL)-based integration ontology that models health data from HL7 FHIR standard implemented services, normal Web services and Web of Things (WoT) services and Linked Data together with home environment data from formal ontology-described WoT services. It works on the resource integration layer of the layered integration architecture. An example use case with a prototype implementation shows that the proposed method successfully integrates the health data and home environment data into a resource graph. The integrated data are annotated with semantics and ontological links, which make them machine-understandable and cross-system reusable.

A Review of Internet of Things Technologies for Ambient Assisted Living Environments

“…There are a lot of initiatives and vendors, producing and fostering their own IoT solutions and devices/things using use different interoperability standards. However, these standards are not aligned and usually are not interoperable with each other [106,107]. This leads to the very fragmented IoT market, where users are forced to choose and use specific equipment from one producer with very limited ability directly combine different IoT platforms into one solution.…”

Connecting and linking neurocognitive, digital phenotyping, physiologic, psychophysical, neuroimaging, genomic, & sensor data with survey data

“…Other recent healthcare big data manuscripts focus on the medical internet of things [ 15 ] and summarize the technologies involved and on the internet of things network for healthcare [ 16 ] theoretical constructs such as topologies, architectural and physical elements standards, platform, services, and applications at a broader population-based level, recognizing the numerous challenges in the medical internet of things/internet of things network for healthcare. Other manuscripts address interoperability standards and ontologies concerning the web of things [ 17 ]. These articles summarize the current state of big data healthcare at a broad level across technologies, standards or lack of them and the inherent challenges in ingestion and harmonization given the diversity of divergent systems and platforms involved.…”

Semantic assessment of smart healthcare ontology

“…Linked Health Resource (LHR) (Peng and Goswami, 2019) ontology is modeled using RDFs and OWL standard to present the health-care information. LHR ontology has reused SSN-SOSA to link with IoT devices.…”