RT Journal Article
T1 SODA: A framework for spatial observation data analysis
A1 Villarroya Fernández, Sebastián
A1 Ríos Viqueira, José Ramón
A1 Regueiro, Manuel A.
A1 Taboada González, José Ángel
A1 Cotos Yáñez, José Manuel
K1 Spatial data
K1 Observation data
K1 Sensor data
K1 Data analysis
K1 Data warehouse
AB Very large amounts of geospatial data are daily generated by many observation processes in different application domains. The amount of produced data is increasing due to the advances in the use of modern automatic sensing devices and also in the facilities available to promote crowdsourcing data collection initiatives. Spatial observation data includes both data of conventional entities and also samplings over multi-dimensional spaces. Existing observation data management solutions lack declarative specification of spatio-temporal analytics. On the other hand, current data management technologies miss observation data semantics and fail to integrate the management of entities and samplings in a single data modeling solution. The present paper presents the design of a framework that enables spatio-temporal declarative analysis over large warehouses of observation data. It integrates the management of entities and samplings within a simple data model based on the well known mathematical concept of function. Observation data semantics are incorporated into the model with appropriate metadata structures.
PB Springer Nature
YR 2014
FD 2014
LK https://hdl.handle.net/10347/45291
UL https://hdl.handle.net/10347/45291
LA eng
NO Villarroya, S., Viqueira, J.R.R., Regueiro, M.A. et al. SODA: A framework for spatial observation data analysis. Distrib Parallel Databases 34, 65–99 (2014). https://doi.org/10.1007/s10619-014-7165-7
NO This work has been partially supported by the Spanish Ministry of Science and Innovation (TIN2010-21246-C02-02).
DS Minerva
RD 24 abr 2026