Linked Data Geo-Statistical Analysis of Air Pollution in Urban Areas

Linked Data technology as a result of growth of Semantic Web in the last decade, enable applications to exploit data from many different resources. Linked Data made it possible to search data semantically over the web, whereas common search engines use text matching approaches to find desired data and documents. So that, querying spatial and temporal features of various data becomes easier using Linked Data. Air pollution in large cities is one of the most important public health issues. This research takes advantage of Linked Data solution to enable the multisource data fusion and analytics. We use DBpedia to enrich air pollution information and specify areas having harmful levels of particulate pollution for vulnerable locations such as universities using AQI interpolation map and nearest universities to air monitoring stations with perilous level. The results of experiment show that using the intrinsic potential of Linked Data technology we can interlink information from various resources efficiently.