ACCELERATING ELEARNING FOR CLOUD SERVICES AND BIG DATA PLATFORMS IN HEALTHCARE

Abstract

Using Cloud services and Big Data platforms is considered a technological innovation in healthcare, furthermore improving performance of clinical data analytics and enabling the development of eHealth applications. In healthcare, Big Data can rapidly be used for obtaining new knowledge through online diagnostic and prediction tools, such as prevention of diseases, as well as easier access and reduced cost of healthcare services. Also, Cloud Computing enables the fast deployment of software applications as web services - Software as a Service (SaaS), which are hosted in a secure datacenter with elastic resources enabling scalability in case of workload change and failover redundancy in case of disasters. However, the problem of learning to work with such new technologies involves a delay in the adoption, many due to misunderstanding of aspects regarding data privacy and ownership issues, risks of misuse of personal data, and new scientific risks. The purpose of this paper is to analyze and compare technological innovations in eLearning for Cloud and Big Data technologies in the healthcare domain, moreover proposing an acceleration framework for the training of scientists and eHealth users in the use of open source tools. Furthermore, validated learning methods are proposed for eLearning where best practices for security and data management problems are addressed, given the heterogeneous nature of the communication and computing environment. The paper fills a gap in the eLearning literature by providing an overview of Cloud and Big Data best practices and open source tools that can be integrated for accelerated adoption in the healthcare domain.