Diferenças

Aqui você vê as diferenças entre duas revisões dessa página.

--- group_modelling:general [2009/03/19 15:56] – inpeifgi
+++ group_modelling:general [2009/03/19 17:08] – inpeifgi
@@ Linha 16: / Linha 16: @@
-===== Presentations to the plenun =====
-===== Extended Abstracts =====
-=== Paper 01) Survey of web service specifications for spatio-temporal data ===
+===== Extended Abstracts =====
-\\
-//Authors//: Lubia Vinhas and Karine Ferreira
-\\
-\\
-//Abstract//: Spatio-temporal data is used to represent dynamic spatial phenomena.
-Some examples are physical processes like temperature and volcano eruption, moving objects
-like animal tracking and iceberg movement as well as evolving objects like oil spill evolution
-on the ocean. This spatio-temporal data is generated by different technologies, such as fixed
-and mobile geosensors, GPS and Earth observation satellites or radio-frequency identification
-(RFID) and can be distributed in different data sources. In order to analyse this kind of data
- specific operations are necessary, for instance, extraction of trajectories, calculation of
-the variation of distance between two moving objects over time and extraction of time series of
-a specific location or area.
-\\
-In this context, service oriented architecture is a good option to create interoperable
-frameworks in order to handle distributed spatio-temporal data sources. Therefore, this work
-aims to evaluate if and how existing web service specifications, such as Sensor Observation
-Service (SOS), Web Feature Service (WFS), Web Coverage Service (WCS), Web Processing Service (WPS),
-Open Location Service (OpenLS) and Sensor Planning Service (SPS),  deal with spatio-temporal
-information. The main goal is to assess them by considering the following aspects:
-supported spatio-temporal data and operations, usability and compliance of existing
-implementations.
+  - [[abstract_lubia_karine|Survey of web service specifications for spatio-temporal data]]
+  - [[abstract_lubia_edzer|Spatio-temporal analysis of remote sensing imagery time series]]