Luis E. Rodríguez, Alain Tamayo, Arturo Beltrán, Joaquín Huerta                                            Universidad Jau...
   Virtual Globes    ◦ More realistic vision of the      earth (satellite and aircraft      imagery).    ◦ Show geographi...
   Geo-sensors    ◦ Vast network of sensors.    ◦ Valuable and up-to date      data.    ◦ Big volumes of data.   SWE (Se...
   Big volumes of sensor data    freely accessible.   Data structured following    standards.   High temporal availabil...
   Classification of sensor data for finding appropriate    visualization methods for each class.   Implementation of pr...
     At a high level the observations can be      classified in:I.    Observations for which the result of a single      ...
   One sensor:    ◦ One Observation:       Textual representation, or some        categorization of the value.       Sh...
   Data that varies in its    spatial position:    ◦ Contour lines, dot      distribution –like maps,      analytic surfa...
Requirements:   Generic tool enabling the interaction with SOS    compliant servers.   To ease the access and retrieval ...
   Java desktop    application.   Uses Eclipse    Rich Client    Platform (RCP).   WWJ SDK.   SEXTANTE 0.6   Communic...
User interface   Composed by Views    for accessing specific    functionality:    ◦ Globe View    ◦ Servers View    ◦ Dat...
   OGC, SOS Filters    (temporal, spatial,    property-based).   Data composition,    and creation of new    datasets. ...
   Features:    ◦ Open source geo-spatial      analysis library.    ◦ More than 200 algorithms.    ◦ GUI components for  ...
   Is provided a    wizard for:    ◦ Selecting the      visualization type.    ◦ Selecting the data      to be visualized...
   Time series charts,    scatter plots    charts.   Customizable    through a wizard.                          15
   Animation showing    observations.    ◦ Animation controls    ◦ Selection of the      observations.   Includes import...
SEXTANTE Results: ◦   Charts. ◦   HTML content ◦   Vectors. ◦   Tabular data.Some examples:• Histogram• Statistics• Buffer...
   Offerings in a    server.    ◦ Information of      interest, sensors.                           18
   Visibility control,    elimination of    elements.   Observations    data inspection.                          19
   The prototype application allows consuming,    combining and analyzing sensor data from    different sources.   The v...
Questions?             21
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Presentation agile

  1. 1. Luis E. Rodríguez, Alain Tamayo, Arturo Beltrán, Joaquín Huerta Universidad Jaume I15th AGILE International Conference in Geographic Information Science
  2. 2.  Virtual Globes ◦ More realistic vision of the earth (satellite and aircraft imagery). ◦ Show geographic features, elevations, seafloor, buildings, roads. ◦ Allow the representation of different types of content: geometries (points, polygons, shapes), images, live content (video, sounds, HTML), KML. ◦ APIs for Java, JavaScript, etc. 2
  3. 3.  Geo-sensors ◦ Vast network of sensors. ◦ Valuable and up-to date data. ◦ Big volumes of data. SWE (Sensor Web Enablement) ◦ Set of standards:  Interoperability, tasking, formal description of observations and sensor systems.  SOS services, interface for accessing and storing observations. 3
  4. 4.  Big volumes of sensor data freely accessible. Data structured following standards. High temporal availability of data. Geo-located data gathered in places of scientific interest. Valuable for analyzing, exploring and visualizing. 4
  5. 5.  Classification of sensor data for finding appropriate visualization methods for each class. Implementation of prototype to visualize SOS- published sensor data on a Virtual Globe. Integration of the SEXTANTE library to add spatial data analysis capabilities to the prototype. 5
  6. 6.  At a high level the observations can be classified in:I. Observations for which the result of a single observation do not vary with either spatial position or time.II. Observations for which the result of a single observation contains multiple values that vary with spatial position, time, or both. 6
  7. 7.  One sensor: ◦ One Observation:  Textual representation, or some categorization of the value.  Shapes with visual properties linked to the value of the observation. ◦ Multiple Observations:  Time series charts, difference charts, animations. Multiple Sensors: ◦ One Observation:  In the same way as with one sensor, similar representations for similar properties. ◦ Multiple Observations:  Time series charts, scatter plot charts, animations. 7
  8. 8.  Data that varies in its spatial position: ◦ Contour lines, dot distribution –like maps, analytic surfaces. Data that varies with time: ◦ Animations, time series charts. Data that varies in space and time: ◦ Dynamic analytic surfaces, animations. 8
  9. 9. Requirements: Generic tool enabling the interaction with SOS compliant servers. To ease the access and retrieval of sensor data. Include data handling capabilities. Different visualization methods. Integration with SEXTANTE. Use the NASA World Wind for Java virtual globe. 9
  10. 10.  Java desktop application. Uses Eclipse Rich Client Platform (RCP). WWJ SDK. SEXTANTE 0.6 Communication library 10
  11. 11. User interface Composed by Views for accessing specific functionality: ◦ Globe View ◦ Servers View ◦ Datasets View ◦ Data handling view. ◦ Rendered Objects View. 11
  12. 12.  OGC, SOS Filters (temporal, spatial, property-based). Data composition, and creation of new datasets. Data presentation, selection for visualization. 12
  13. 13.  Features: ◦ Open source geo-spatial analysis library. ◦ More than 200 algorithms. ◦ GUI components for configuring the algorithms. ◦ Extensible trough implementation of geo- algorithms. Integration using adapters. ◦ Raster Data. ◦ Vector Data. ◦ Table Data. Algorithm Outputs: ◦ Raster, Vector, Charts, Text /HTML, Tabular data. 13
  14. 14.  Is provided a wizard for: ◦ Selecting the visualization type. ◦ Selecting the data to be visualized ◦ Customizing the visualization elements 14
  15. 15.  Time series charts, scatter plots charts. Customizable through a wizard. 15
  16. 16.  Animation showing observations. ◦ Animation controls ◦ Selection of the observations. Includes important values: ◦ maximum, minimum, mean. ◦ Sampling time. 16
  17. 17. SEXTANTE Results: ◦ Charts. ◦ HTML content ◦ Vectors. ◦ Tabular data.Some examples:• Histogram• Statistics• Buffers generatedwith tree observations(radius depends on theobservation) 17
  18. 18.  Offerings in a server. ◦ Information of interest, sensors. 18
  19. 19.  Visibility control, elimination of elements. Observations data inspection. 19
  20. 20.  The prototype application allows consuming, combining and analyzing sensor data from different sources. The visualization types help the data exploration, comparability and discovery of relations. The integration with SEXTANTE enhances the possibilities of performing analysis using sensor data. Future work: ◦ Inclusion of other visualization types. ◦ Improve the interaction with the visualized content. ◦ Work in ways of sharing the visualizations. ◦ Improve the use of metadata. 20
  21. 21. Questions? 21
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