Smart Web Services for Big Spatio-Temporal Data in Geographical Information Systems

The informative value of analytic processes by geographical information systems depends on the accuracy, consistency and completeness of the gathered data fed into the system. By feeding Big Data into it, such requirements are hard to maintain, as the provenance, veracity, velocity, structural and semantic heterogeneities of the gathered spatiotemporal data have to be addressed. Exploitation and integration of Big Data in such ways is an ongoing challenge. We present fundamentals of a well-defined and collaborative information integration approach based on semantic web technology, established ontologies and linked APIs that specifically emphasizes a spatio-temporal relation and enable a new generation of geographical information systems. We employ the concept of smart web services for dynamically composed workflows in order to cope with the characteristics of Big Data value streams and generate more elaborated data.