Soft Spatial Querying on JSON Data Sets

JSON (JavaScript Object Notation) has become popular for exchanging data sets over the Internet. Many data sets are “geo-tagged”, since they represent spatial entities. As an effect, spatial analysts have to perform spatial queries on JSON data sets. While working with large data sets, crisp (on/off) spatial relations could be marginally effective; instead, soft relations and “soft spatial querying” could be the right tools, because they reveal the extent of a given spatial relation. In this paper, we present the recent evolution of J-CO-QL+, the query language of the J-CO Framework (under development at University of Bergamo, Italy) towards soft spatial querying on geo-tagged JSON data sets.