Design and Development of a Linked Open Data-Based Web Portal for Sharing IoT Health and Fitness Datasets

Abstract

The huge amounts of self-tracked health data collected by Internet of Things (IoT) fitness devices offer important opportunities to the research community. If properly exploited, IoT health and fitness datasets can help to gain valuable insights into the human health in order to provide better healthcare.However, IoT health data come from a variety of different heterogeneous sources and in proprietary formats, which means that they require an integration process, normally manually done by domain experts, in order to be analysed. This task is not only significantly time consuming but in many cases, error prone.In this study, we designed and developed a web platform for collecting and publishing IoT health and fitness datasets according to Linked Data principles. We leveraged the IFO ontology and the Semantic Web technologies to make the IoT health and fitness datasets freely available to the community in a shared, semantically meaningful, easily discoverable, and reusable manner.The system introduced in this article shows that Semantic Web technologies can be a viable and comprehensive solution for describing, integrating and sharing heterogeneous IoT datasets, thus overcoming the issues of data silos that nowadays dominate the IoT landscape.