Godiva2 Overview
Upcoming SlideShare
Loading in...5
×
 

Like this? Share it with your network

Share

Godiva2 Overview

on

  • 2,790 views

Overview of the Godiva2 environmental data online visualization system.

Overview of the Godiva2 environmental data online visualization system.

Statistics

Views

Total Views
2,790
Views on SlideShare
2,721
Embed Views
69

Actions

Likes
2
Downloads
22
Comments
0

7 Embeds 69

http://letthedataflow.ca 51
http://www.letthedataflow.ca 10
http://www.slideshare.net 3
http://www.slideee.com 2
http://www.letthedataflow.com 1
http://translate.googleusercontent.com 1
http://www.docshut.com 1
More...

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • Need lots of different types of data
  • WS can bring in data and provide analysis functions, extending capabilities of VGsOGC has >240 members including major industry players, research groups etc

Godiva2 Overview Presentation Transcript

  • 1. Interactive visualization of four-dimensional environmental data using an enhanced Web Map Service Jon Blower, Reading e-Science Centre, Environmental Systems Science Centre, University of Reading [email_address] http://www. reading.ac.uk/godiva2
  • 2. Issues we will cover
    • Why does environmental science need geospatial web services?
    • Online visualization of scientific data using a Web Map Service
      • What is meant by an “enhanced” WMS?
    • Difficulties applying geospatial web services to scientific data
    • Ideas for future research
  • 3. We need to see into the future All require interdisciplinary science! Flood prediction Search and rescue Climate prediction
  • 4. How can we make useful predictions?
    • Need computer models that:
      • encapsulate our scientific knowledge
      • are validated by observations
    • Output from these models needs to be disseminated:
      • within the scientific community
      • to government policy makers
      • to emergency response situations
      • ... often in (near) real time
    • Need to compare models with other geospatial data sources
      • e.g. land use maps, locations of assets
      • Requires interoperability
  • 5. The importance of visualization
    • Detecting features in models (e.g. storms)
    • Diagnosing problems in models
    • Preview data before downloading
    • Make sense of large datasets
    • Puts data into wider context
    • Communicate complex concepts
  • 6. Existing scientific visualization software
    • Problem-solving environments
      • Matlab, IDL
    • 3-D desktop visualization
      • MayaVi
    • 3-D remote visualization
      • Silicon Graphics
    • Web-based
      • Live Access Server
    • Geographic Information Systems (GIS)
    • All require expert knowledge
    • Limited interoperability between systems
  • 7. Barriers to effective visualization
    • Computer model outputs are large ...
      • Four-dimensional rasters (x,y,z,t)
      • High-resolution
      • Many variables
      • Ensembles
      • Tera/petabyte scale
    • ... complex ...
      • Many file formats and conventions
      • Many numerical grids (right)
    • ... and distributed
      • Too much data to hold in one place
  • 8. Summary so far
    • Predictions need models that are validated by data
    • Numerical model data pose several practical challenges
    • Visualization of env. sci. data is v. important but complex
    • Need to visualize data from lots of different sources
  • 9. Open Geospatial Web Services (plus many more!) Web Coverage Service Gridded data (rasters) Web Map Service Map imagery (PNG, JPG, GIF) Web Feature Service Simple features Complex features
  • 10. Web Map Service: a closer look
    • GetCapabilities -> metadata
    • GetMap -> map image, based on client-selected parameters, inc:
      • Image width/height
      • Image coordinate reference system
      • Style
    • GetFeatureInfo -> information about a particular map pixel
      • Format not standardized
    • Supports multidimensional data
    • Mandated by EC INSPIRE directive as means for visualizing geospatial data
  • 11. Lightweight visualization methods
    • Most heavyweight logic is transferred to server
      • Pros and cons!
    • Imagery transmitted over Web in standard formats
    • WMS interfaces (often)
    • Simple data formats, Javascript APIs
    • Simpler approach, easier to use
    • But functionality often limited
    NASA World Wind OpenLayers Google Earth Microsoft Virtual Earth
  • 12. Limitations of WMS for science
    • Map-oriented
      • Scientists want to slice data in lots of ways
    • Need extra metadata for scientific data
      • Format not standardized
    • Clients and servers often don’t support z and t
      • (but it’s in the specification)
    • Server implementations often slow for high-res raster data
      • Can’t use interactively
  • 13. A new system: Godiva2
    • Interactively explore 4D geospatial raster datasets on the web
    • ~40 datasets
      • Research data, operational forecasts, satellite products
    • Images generated dynamically for maximum flexibility
    • OGC Website of the Month, January 2008
    http://www.reading.ac.uk/godiva2
  • 14. Selection of depth Select from all the depth levels of the model
  • 15. Selection of time (range) Select from all the timesteps in the model Selection of a time range leads to an animation
  • 16. Finding the data value at a point Click on the data layer, data value and precise position is shown Lon: -64.08 Lat: 36.21 Value: 19.27
  • 17. Timeseries plots If a time range is selected, can create a timeseries plot at a point
  • 18. Vector plots
  • 19. Selection of colour palette
  • 20. Contrast-stretching
    • Manual or automatic
  • 21. Polar projections
  • 22. Choice of background images
  • 23. Export to Google Earth
    • Allows visualization of multiple data sources
    • Hurricane Katrina, August 2005
    • Storm track positions (analysed from ECMWF vorticity data) by Lizzie Froude, ESSC
    • Sea surface temperature data from UK Met Office FOAM model
    • Combination shows cooling of surface waters on right-hand side of cyclonic storm track
    • High winds cause upwelling of cool, deep water
  • 24. Architecture of Godiva2 system Java Web Application (Spring, JSP) Data abstraction layer NetCDF files Other files GetCapabilities GetMap GetFeatureInfo Custom metadata Godiva2 website JSON PNG, GIF Generic WMS client XML Remote data OPeNDAP PNG, GIF
  • 25. Visualizing distributed data: the MERSEA project OPeNDAP DATA North Atlantic data centre OPeNDAP DATA OPeNDAP DATA WMS @ Reading Dynamic Quick View website (= rebranded Godiva2) Uses existing OPeNDAP-based architecture Single point of failure http://www.resc.rdg.ac.uk/mersea Baltic data centre Arctic data centre Background imagery (from NASA etc)
  • 26. Removing the bottleneck: Federated visualization OPeNDAP DATA WMS OPeNDAP DATA WMS OPeNDAP DATA WMS Each data centre must install the WMS Less network traffic More robust Third-party WMS Background imagery (from NASA etc)
  • 27. What is the best use for this? Have an idea Discuss/explore Do the work Formally publish Godiva2 Matlab, IDL etc Disseminate Godiva2
  • 28. Who’s using Godiva2?
    • 100,000 GetMap requests served in 3 months
      • From 5 continents
    • Customized versions of Godiva2 site set up for MERSEA and ECOOP projects
      • Major EU framework projects – INSPIRE compliance important!
      • Will be used in MyOcean
    • UK National Centre for Ocean Forecasting
    • Server software installed by:
      • Plymouth Marine Labs
      • AIMS, Australia
      • NOAA, US
    • Code contributions from:
      • MeteoGalicia, Spain
      • TPAC, Tasmania
      • AIMS, Australia
  • 29. Enhancements to WMS
    • Piecemeal metadata-serving
      • avoids large Capabilities document
    • Extra metadata for science data
      • e.g. units of measurement
    • New parameters in GetMap for styling:
      • Choose colour palette
      • Set contrast range
      • Linear or logarithmic scaling
      • Far simpler than Styled Layer Descriptor
    • Generation of timeseries plots via GetFeatureInfo
    • … but fully backward-compatible with WMS1.1.1 and 1.3.0
  • 30. Interoperability 3rd-party clients can’t use the custom WMS extensions NASA World Wind Cadcorp SIS Google Earth
  • 31. Godiva2 summary
    • Godiva2 site is useful for exploring and previewing data
      • Users need to download data for more sophisticated analysis
      • Available as open-source software (http://ncwms.sf.net)
    • Have focussed on marine data but applicability is much wider
    • Use of WMS standard enables wide adoption and helps to build a community
    • Successful example of delivering an application via the web
  • 32. Elephants I have ignored: The three “S”s
    • Security
    • Semantics
    • Scalability
  • 33. Conclusions…
  • 34. Why is it hard to reconcile scientific data and open GIS standards? Data volumes often too large for XML XML is primary exchange mechanism Weird and wonderful coordinate systems (spatial and temporal) Well-known, stable coordinate systems Fully four-dimensional data Map-oriented, i.e. 2.5D ( although things are changing, slowly ) Geographic location is an attribute of data Everything is an attribute of a geographic location Science GIS
  • 35. Future work
    • Support non-raster data
      • E.g. In-situ observations
    • Support non-map slices
      • x-t (Hovmuller)
      • x-z, y-z (depth sections)
    • Visualize multiple datasets at once
    • Add capability for simple data processing
    • Integrate with existing community software
      • THREDDS, GeoServer, ERDDAP
  • 36. More research needed…
    • Scalability of servers
      • Key disadvantage of service-oriented software!
    • “ Science profile” for Web Map Service?
      • Earth Observation profile already exists
    • How best to link with Processing Services?
      • E.g. for data intercomparisons
      • Service chaining
    • Appropriate security methods?
    • Redesign of OGC services?
      • Reveal information (esp. metadata) piecemeal
    • Implementation of standards!
  • 37. Some final thoughts
    • Geospatial Web Services are all about interoperability
    • Interoperability is almost always lossy
    • Law of diminishing returns applies
    • In science we usually can’t lose any information
    • Hence what is the practical limit for application of GWS technology in science?