Trustworthy data processing for health analytics tasks

Big Data Analytics are indispensable components of architectures dealing with processing and visualizing results of diverse healthcare-related information sources. In this work, we propose a versatile cloud design where the Health Analytic Tools (HATs) are decoupled from the Datastore and the User-Interface parts, still preserving the element of system trust. This design offers advantages over the process of modifying and constructing new health policy models by means of supporting many-to-many relations between HATs and Health Key Performance Indicators. Additionally, it offers independence regarding HAT providers, analytics frameworks, cloud providers and deployment environments allowing the scaling of the proposed architecture.