TY - GEN
T1 - A Data as a Service Metamodel for Managing Information of Healthcare and Internet of Things Applications
AU - Cedillo, Priscila
AU - Valdez, Wilson
AU - Cárdenas-Delgado, Paúl
AU - Prado-Cabrera, Daniela
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Ambient assisted living
KW - Data as a service
KW - Healthcare
KW - Internet of things
KW - Metamodel
KW - Model-Driven engineering
UR - https://wjarr.com/content/students-perceptions-performance-professors-clinic-dental-school-university-cuenca-academic
U2 - 10.1007/978-3-030-62833-8_21
DO - 10.1007/978-3-030-62833-8_21
M3 - Contribución a la conferencia
AN - SCOPUS:85097291611
SN - 9783030628321
T3 - Communications in Computer and Information Science
SP - 272
EP - 286
BT - Information and Communication Technologies - 8th Conference, TICEC 2020, Proceedings
A2 - Rodriguez Morales, Germania
A2 - Fonseca C., Efraín R.
A2 - Salgado, Juan Pablo
A2 - Pérez-Gosende, Pablo
A2 - Orellana Cordero, Marcos
A2 - Berrezueta, Santiago
PB - Springer Science and Business Media Deutschland GmbH
T2 - 8th Conference on Information and Communication Technologies of Ecuador, TICEC 2020
Y2 - 25 November 2020 through 27 November 2020
ER -