A cross-analysis framework formulti-source volunteered, crowdsourced, and authoritative geographic information: The case study of volunteered personal traces analysis against transport network data  

作　　者：Gloria Bordogna Steven Capelli Daniele E.Ciriello Giuseppe Psaila 

机构地区：[1]CNR IREA,Milano,Italy [2]DISCo,Universitádegli studi di Milano Bicocca,Sesto San Giovanni,Italy [3]DIGIP,University of Bergamo,Dalmine,Italy

出　　处：《Geo-Spatial Information Science》2018年第3期257-271,共15页地球空间信息科学学报（英文）

摘　　要：The paper discusses the need of a high-level query language to allow analysts,geographers and,in general,non-programmers to easily cross-analyze multi-source VGI created by means of apps,crowd-sourced data from social networks and authoritative geo-referenced data,usually represented as JSON data sets(nowadays,the de facto standard for data exported by social networks).Since an easy to use high-level language for querying and manipulating collections of possibly geo-tagged JSON objects is still unavailable,we propose a truly declarative language,named J-CO-QL,that is based on a well-defined execution model.A plug-in for a GIS permits to visualize geo-tagged data sets stored in a NoSQL database such as MongoDB;furthermore,the same plug-in can be used to write and execute J-CO-QL queries on those databases.The paper introduces the language by exemplifying its operators within a real study case,the aim of which is to understand the mobility of people in the neighborhood of Bergamo city.Cross-analysis of data about transportation networks and VGI from travelers is performed,by means of J-CO-QL language,capable to manipulate and transform,combine and join possibly geo-tagged JSON objects,in order to produce new possibly geo-tagged JSON objects satisfying users’needs.

关 键 词：Cross-analysis framework comparing VGI crowd-sourced and authoritative geographical data JSON data-sets declarative query language heterogeneous data-sets 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]