Sensor Web event detection and geoprocessing over Big data

In the Big Data era, scientific and social data can complement each other for enhanced data analysis and scientific discovery. In the geospatial domain, Sensor Web technologies can provide real-time or near real-time geospatial data to support timely decision-making. Scientific workflows have been identified as a key approach to support Big Data analytics for scientists. In the human-as-sensor aspect, the social content, as a special kind of sensor data, could be mined and fused in a Sensor Event Service (SES), allowing social data to be used inside a Spatial Data Infrastructure (SDI). This paper investigates an infrastructural approach on how social and scientific data could work together in an interoperable service environment. Sensor Web and geoprocessing services technologies are leveraged together for timely decision support from social and sensor data. A use case on haze-related data mining and analysis illustrates the applicability of the approach.