Taming the Evolution of Big Data and its Technologies in BigGIS - A Conceptual Architectural Framework for Spatio-Temporal Analytics at Scale

In the era of spatio-temporal big data, geographic information systems have to deal with a myriad of big data induced challenges such as scalability, flexibility or fault-tolerance. Furthermore, the rapid evolution of the underlying, occasionally competing big data ecosystems inevitably needs to be taken into account from the early system design phase. In order to generate valuable knowledge from spatio-temporal big data, a holistic approach manifested in an appropriate architectural design is necessary, which is a non-trivial task with regards to the tremendous design space. Therefore, we present the conceptual architectural framework of BigGIS, a predictive and prescriptive spatio-temporal analytics platform, that integrates big data analytics, semantic web technologies and visual analytics methodologies in our continuous refinement model.