出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：The large number of geo referenced data sets provided by Open Data portals, social medianetworks and created by volunteers within citizen science projects (Volunteered GeographicalInformation) is pushing analysts to define and develop novel frameworks for analysing thesemultisource 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 andplanning social dynamics. The convergence of various technologies related with datarepresentation formats, database management and GIS (Geographical Information Systems)can enable analysts to perform such complex integration and transformation processes. JSONhas 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 ofJSON objects; the GIS community has defined the GeoJSON standard, a JSON format forrepresenting georeferenced information layers, and has extended GIS software to support it.However, all these technologies have been separately developed, consequently, there is actuallya gap that shall be filled to easily manipulate GeoJSON objects by performing spatialoperations. In this paper, we pursue the objective of defining both a unifying view of severalNoSQL databases and a query language that is independent of specific database platforms toeasily integrate and transform collections of GeoJSON objects. In the paper, we motivate theneed for such a framework, named J-CO, able to execute novel high-level queries, written in theJ-CO-QL language, for JSON objects and will show its possible use for generating open datasets by integrating various collections of geo-referenced JSON objects stored in differentdatabases.
关键词：Collections of JSON objects; Geo-tagged data sets; Query Language for geographical analysis;Powerful spatial operators
