R-Wingu, the ‘Big Data’ Analytic Framework: a Solution to Intelligent Correlation of Research Output in a Private Cloud Prototype for Seamless Research Ontologies

Abstract

‘Internet of Things’ is choking the world with Zettabyte scale data rate of which traditional computing can neither store nor process. Outputs of various kinds of Research endeavors are held in different media over the years and cannot be made to “talk to each other” to exploit each other for beneficial relative information. The prime objective is to find a platform that can easily accommodate Cloud technology which can elastically handle the big data concept. In this study a private cloud is built using Ubuntu and Eucalyptus open source software on two quad processor machines with 8GB Ram. Using Apache Flume and Hadoop analytics, Big Data obtained from Research outputs is mounted on the R-Wingu framework with capacity to data mine unstructured, unrelated data and relate the components intelligently and may be leased as Database as a Service(DaaS). Once disparate data streams are accessible in real time, in one place and a consistent fashion, data suddenly becomes much more powerful and decisions become that much more impactful. Surveys are conducted across research communities with an aim of isolating research Gaps through various statistical tools. Sample results are discussed alongside previous studies’ outputs. Research Gaps filled are compared by poll results conducted with exiting outcomes. Establishments are urged to embrace Big Data approach for competitive advantage.