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.
(2022). Soft Spatial Querying on JSON Data Sets . Retrieved from https://hdl.handle.net/10446/235316
Soft Spatial Querying on JSON Data Sets
Fosci, Paolo;Psaila, Giuseppe
2022-01-01
Abstract
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.| File | Dimensione del file | Formato | |
|---|---|---|---|
|
ADBIS_Fosci_Psaila opt.pdf
Solo gestori di archivio
Versione:
publisher's version - versione editoriale
Licenza:
Licenza default Aisberg
Dimensione del file
284.42 kB
Formato
Adobe PDF
|
284.42 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo
