Geospatial challenges in Big Data using Cloud Computing

Abstract

Big Data is one the emerging concept which gives new opportunities for research, development, innovation and business. It's characterized by four Vs: volume, velocity, veracity and variety and should bring significant value through the processing of massive data. The transformation of massive Data's 4 Vs into the 5th (value) may be a grand challenge for processing capacity. Cloud Computing has emerged as a replacement paradigm to supply computing as a utility service for addressing different processing needs with a) on demand services, b) pooled resources, c) elasticity, d) broad band access and e) measured services. The utility of delivering computing capability fosters a possible solution for the transformation of massive Data's 4 Vs into the 5th (value). This paper investigates how Cloud Computing can be utilized to deal with Big Data challenges to enable such transformation. We introduce and review geospatial scientific examples, including climate studies, geospatial knowledge mining, and dust storm modeling. The tactic is presented during a tabular framework as a guidance to leverage Cloud Computing for Big Data solutions. It was exhibited with some examples that the framework method supports the life cycle of massive processing, including management, access, mining analytics, simulation and forecasting. This tabular framework also can be referred as a guidance to develop potential solutions for other big geospatial data challenges and initiatives, like smart cities.