用于全球传染病控制与预防的物联网语义网（SWoT）

Semantic Web of Things (SWoT) for Global Infectious Disease Control and Prevention.

作者信息

Shaban-Nejad Arash, Brenas Jon Haël, Al Manir Mohammad Sadnan, Zinszer Kate, Baker Christopher J O

机构信息

University of Tennessee Health Science Center-Oak Ridge National Laboratory (UTHSC-ORNL) Center for Biomedical Informatics, Department of Pediatrics, College of Medicine, Memphis TN, USA.

Big Data Institute - Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, U.K.

出版信息

Stud Health Technol Inform. 2020 Jun 26;272:425-428. doi: 10.3233/SHTI200586.

DOI:10.3233/SHTI200586

PMID:32604693

Abstract

This paper reports on the early-stage development of an analytics framework to support the semantic integration of dynamic surveillance data across multiple scales to inform decision making for malaria eradication. We propose using the Semantic Web of Things (SWoT), a combination of Internet of Things (IoT) and semantic web technologies, to support the evolution and integration of dynamic malaria data sources and improve interoperability between different datasets generated through relevant IoT assets (e.g. computers, sensors, persons, and other smart objects and devices).

摘要

本文报告了一个分析框架的早期开发情况，该框架旨在支持跨多个尺度的动态监测数据的语义整合，以为疟疾根除决策提供信息。我们建议使用物联网语义网（SWoT），即物联网（IoT）和语义网技术的结合，来支持动态疟疾数据源的演进和整合，并提高通过相关物联网资产（如计算机、传感器、人员以及其他智能对象和设备）生成的不同数据集之间的互操作性。