The large number of geo referenced data sets provided by Open Data portals, social media
networks and created by volunteers within citizen science projects (Volunteered Geographical
Information) is pushing analysts to define and develop novel frameworks for analysing these
multisource heterogeneous data sets in order to derive new data sets that generate social value.
For analysts, such an activity is becoming a common practice for studying, predicting and
planning social dynamics. The convergence of various technologies related with data
representation formats, database management and GIS (Geographical Information Systems)
can enable analysts to perform such complex integration and transformation processes. JSON
has become the de-facto standard for representing (possibly geo-referenced) data sets to share;
NoSQL databases (and MongoDB in particular) are able to natively deal with collections of
JSON objects; the GIS community has defined the GeoJSON standard, a JSON format for
representing georeferenced information layers, and has extended GIS software to support it.
However, all these technologies have been separately developed, consequently, there is actually
a gap that shall be filled to easily manipulate GeoJSON objects by performing spatial
operations. In this paper, we pursue the objective of defining both a unifying view of several
NoSQL databases and a query language that is independent of specific database platforms to
easily integrate and transform collections of GeoJSON objects. In the paper, we motivate the
need for such a framework, named J-CO, able to execute novel high-level queries, written in the
J-CO-QL language, for JSON objects and will show its possible use for generating open data
sets by integrating various collections of geo-referenced JSON objects stored in different
databases.