Near Real Time Ocean Observations Online - PowerPoint PPT Presentation

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Near Real Time Ocean Observations Online

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Near Real Time Ocean Observations Online – PowerPoint PPT presentation

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Title: Near Real Time Ocean Observations Online


1
Near Real TimeOcean Observations Online
  • the Escape of SEACOOS(Southeastern Atlantic
    Coastal Ocean Observing System) Data Management
    and Visualization Secrets

2
The (tiny) big picture
3
(No Transcript)
4
The nuts bolts
  • Data is aggregated and stored
  • Data is normalized
  • Data is visualized
  • Data is disseminated

5
Data aggregation storage
  • Format flavors
  • netCDF coverage may vary format may not
    vary
  • PNG coverage may not vary color scale may not
    vary
  • Technology
  • Perl

6
Data aggregation storage
  • Relational database
  • One table per in-situ variable type
  • E.g. a wind_table, sst_table
  • Contains the real data
  • One table per raster variable
  • E.g. a sst_raster_table
  • Contains pointers to PNG files boundaries
  • One table per model variable per hour
  • E.g. a 12_00_00_current_forecast_table

PostgreSQL PostGIS

7
Normalization
  • Reporting time varies
  • In-situ data
  • E.g. daily, hourly, half-hourly, every 10 minutes
  • Remotely-sensed data
  • E.g. twice daily
  • Reporting area varies
  • Remotely-senseddata passes

PostgreSQL PostGIS

8
Visualization
  • Main engines
  • PHP, PHP-MapScript
  • Perl
  • MapServer, of course
  • Icing on the cake
  • Dynamic shapefile creation for colorbars
  • AnIS and GIFSicle for animations
  • ImageMagick for image manipulation and raster
    queries
  • Mouseovers
  • Time-series graphs usingGDGraph

9
Icing on the cake dynamic shapefiles
10
Icing on the cake animations
  • AnIS and GIFsicle
  • Produce severalimages and glue them together

11
Icing on the cake raster queries
  • Let MapServer take care of projection issues
  • How to get an SST, for example, from a raster PNG
  • Dump the current extent view of just the raster
    to PNG
  • Get (x,y) clicked pixel RGB of the dumped image
    with PerlImageMagick
  • Lookup pixel RGB in database to find out SST
  • Return SST in the normal query data train

12
Icing on the cake mouseovers
  • Use MapServer 4.x searchmap
  • Produce two images for an HTML page
  • One is static with the querymap
  • The other is an input image
  • Use javascript to swap the two images based on
    user activity
  • The querymap is produced by making a simple
    LWPsimple request for a querymap, and then it
    is merged with the HTML page

13
Icing on the cake time series graphs
  • Pass a query result set to GDGraph for a
    time-series graph

14
Dissemination
  • Maps and charts, of course
  • OPeNDAP (DODS) data access
  • OGC-friendly WMS, WFS
  • SEACOOS pushed a lot of data to the IOOS
    interoperability project
  • Down the pipeline
  • Ad-hoc CSV and/or netCDF data extraction

15
Magic 8 ball
  • Everyone wants speed
  • Near real time implies constantly updated
    databases
  • Recently introduced round-robin-ing of database
    requests
  • As machine A is populated with new data, send all
    DB requests to machine B
  • When machine A is done populating, have it resume
    DB handling, and go update machine B
  • Want to round-robin MapServer requests, too, as
    well as pull application server to its own box

16
A friend in the business
  • Development site http//nautilus.baruch.sc.edu/r
    s
  • Production site (new interface to be released
    soon)http//seacoos.org
  • Very active listserv dealing with mainly
    remote-sensing issues remotesensing_at_caro-coops.o
    rg
  • mailto majordomo_at_caro-coops.org
  • message text subscribe remotesensing
  • Who am I?
  • Charlton Purvis, University of South Carolina,
    SEACOOS
  • cpurvis_at_sc.edu
  • Happy to help and share.
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