A Data as a Service Metamodel for Managing Information of Healthcare and Internet of Things Applications
Abstract:
Internet of Things (IoT) applications nowadays generate a large amount of data, which are continually requiring adequate treatment and services on the Cloud to be available to stakeholders. Healthcare applications manage critical data from different sources as patient charts, Electronic Health Record (EHR), and devices which need security levels, data formatting, and quality of data due to their importance and sensitivity. Data as a Service (DaaS) is a data management framework provided though services on Cloud to bring data storage, integration, processing, analysis services, security, availability, elasticity, and quality characteristics to the data concerning the stakeholders. In this context, this paper proposes a data management solution deployed as DaaS for the healthcare domain presented through a metamodel focused on the federation pattern of data based on an Extract-Transform-Load (ETL) model for data classification; and considering a brief analysis of the non-functional characteristics proper of the DaaS domain as the security, confidentiality, priority, and availability. The metamodel is validated through an instantiation process using the MOntreal Cognitive Assessment (MOCA) test as the entry. Finally, it is presented a discussion from four stakeholder perspectives (e.g., data engineer, IoT solution developer, data quality analyst, health professional) about the solution.
Año de publicación:
2020
Keywords:
- Ambient assisted living
- internet of things
- Metamodel
- Healthcare
- model-driven engineering
- Data as a service
Fuente:


Tipo de documento:
Conference Object
Estado:
Acceso restringido
Áreas de conocimiento:
- Análisis de datos
- Ciencias de la computación
Áreas temáticas:
- Ciencias de la computación
- Medicina y salud
- Funcionamiento de bibliotecas y archivos