sharing and visualizing earth science data with web services and virtual globes
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Sharing and visualizing earth science data with Web Services and Virtual Globes. Jon Blower (with help from lots of others!) Reading e-Science Centre Environmental Systems Science Centre University of Reading United Kingdom. The Problem. discover analyse visualize. - PowerPoint PPT PresentationTRANSCRIPT
Sharing and visualizing earth science data with Web Services
and Virtual Globes
Jon Blower (with help from lots of others!)Reading e-Science Centre
Environmental Systems Science Centre
University of Reading
United Kingdom
The Problem
discoveranalysevisualize
lots of software packages!
WHAT GOES HERE?
lots of file formats!access control
Solution 1: Web interfaces to datasets
Separate websites for
each data provider
What’s wrong with Solution 1?• Discovery relies on web search and “just knowing
it’s there”• Hard to intercompare data from different sites• Slow route to visualization:
– Download data file(s)– Import into your tool of choice– Produce image
• Can’t download subsets or aggregations of files• Different login for each provider• In summary: not very flexible!• All this is because websites are designed for
humans, not machines
Solution 2: Web Services
Web Services Web Services Web Services
Different user interfaces for different user communities
More about Solution 2• Each data provider provides “hooks” into the data
store– Discovery: results = find_data(“salinity”)– Download: data = get_data(“temperature”, “North Atlantic”, “June 2006”, “NetCDF”)
– Visualize: picture = get_map(“currents”, “global”, “2007-05-05”, “PNG”)
• These “hooks” are Web Services• Third-party systems can use Web Services as plug-
ins• Different user interfaces can be built on top of the
same system• Much more flexible than Solution 1
A closer look at Web Services
• Designed for machine-to-machine interaction• They are “subroutines” that run on remote machines• Data and messages are exchanged in platform-
independent formats• Serve data to another system
– with one notable exception (see later)
• Can be made to be secure
• You can do anything with Web Services!• BUT to be useful, communities must agree on
standards for compatibility
So the question becomes…
WHAT EXACTLY GOES HERE?
Different user interfaces for different user communities
Some standard Web Services for earth science data
• OPeNDAP (Open-source Project for a Network Data Access Protocol):– formerly known as DODS– allows clients to download data subsets– aggregates files into a single, logical whole– clients can treat remote data sets just like local ones– well supported by software tools and libraries– but requires clients to have advance knowledge of the
data structure• Open Geospatial Consortium (OGC):
– Whole suite of Web Services for different situations– Provides a logical and semantic view of the data– Tooling support less than OPeNDAP but growing quickly
OGC Web Services
Web Service Purpose
Web Map Service (WMS) Serves map images (e.g. satellite images)
Web Feature Service (WFS) Serves geographical features (e.g. buoy locations, radiosonde profiles)
Web Coverage Service (WCS) Serves multidimensional raster data (e.g. numerical model output, 3-D seismic data)
Web Processing Service (WPS) Processes data
Sensor Web Enablement (SWE) – coming soon
Whole suite of standards for monitoring and managing sensor systems
Geography Markup Language (GML) underpins OGC Web Services
OGC implementations
• GeoServer
• MapServer (U of Minnesota)
• Deegree
• ncWMS (for NetCDF data)
• Lots of commercial stuff…
Standards give interoperability!
NASA World Wind
Cadcorp SIS
Google Earth
Geo-website
Web Services in Action:UK NERC Data Grid (NDG)
• Provides access to atmospheric and oceanographic datasets produced by NERC projects
• Each data provider installs a suite of Web Services– nothing is centralized!
• Clients can use the NDG web interface or build their own interfaces
• NDG allows:– discovery of data– online visualization of data– exploration of metadata– download of data
http://ndg.nerc.ac.uk
Discovering and browsing data
Web Map Service (WMS) in Action:online data visualization
• “Godiva2” website gives very fast previews of 4-D data on an interactive website
• Reads data from NetCDF files and OPeNDAP servers
• Serves images through an "enhanced" WMS
• Draggable, zoomable map
• Allows the fast creation of animations
http://lovejoy.nerc-essc.ac.uk:8080/ncWMS/godiva2.html
Selection of depth
Select from all the depth levels of the model
Selection of time (range)
Select from all the timesteps in the model
Selection of a time range leads to an animation
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
Timeseries plots
If a time range is selected, can create a timeseries plot at a point
Godiva2 architecture
NetCDFDatasources
Non-standardfile format
NetCDF
Web interfaceVirtual GlobeGIS client
WMS
OPeNDAP
Web Services: conclusions• Web sites can be excellent, but are "dead ends" for data
– You can't build on top of a website• Exposing data and metadata via Web Services allows:
– Building of new interfaces on top of your data– Data from different locations to be brought together
• OGC standards are part of the story– They handle the "geospatial" component of data– Need separate web services for other things like vocab, property
databases• Web Services should be standards-compliant or simple (or
both!)• WS and standards are no good without tools
• Many providers now see more traffic through Web Services than their primary web site!
How can we bridge the gap?
PaperPDF or
Web site(text + images)
Web Service
For humans For machines
Dead end for data Open end for data
KML
Virtual Globes• Easy to use 3-D applications for
visualizing environmental data– All scales from global to sub-metre
• Around 30 currently in existence!– Google Earth– NASA World Wind– ArcGIS Explorer– ...
• Can combine data from numerous sources
• Enable discovery of data• Use open standards
– Simple data formats– Standard Web Services
• Often free or low-cost• Generally can't do data analysis
– Not replacements for fully-functional GIS systems!
NSIDC Snow water equivalentin NASA World Wind
Keyhole Markup Language (KML)• Balances simplicity with richness of
representation– Simpler than GML– Richer than GeoRSS
• The format of Google Earth, but understood by many other systems:
– Google Maps– NASA World Wind– ArcGIS Explorer– Other GIS software
• Encodes simple geographic features:– Points, lines, polygons (e.g. in-situ
observations)– Image overlays (e.g. satellite images,
model output)• Can annotate features with more
information– E.g. links to website
• Can easily be created from existing data (Excel, databases…)
• Now on the standards track through OGC
Quick comparison of 3 Virtual Globes
• Google Earth– Aimed at "the man in the street"– Easy to use– Poor support for OGC services– Big community
• NASA World Wind– Aimed at scientists– Portal to NASA satellite imagery– Next version will be exciting (pluggable, customizable)
• ArcGIS Explorer– Aimed at GIS community (esp. existing Arc users)– Can display subsurface and submarine data– Can write plug-ins in .NET– Very young
Virtual Globe strengths and weaknesses
• Strengths– Easy to use– Easy to visualize data from different sources– Provide "lightweight GIS" format: KML– Low cost– Some support for discovery through VG interface
• Weaknesses– Poor direct support for OGC services (WMS support
patchy, WCS/WFS support almost non-existent)– Many historical GIS formats (shapefiles) not usually
supported– Hard to visualize subsurface/submarine data
Google Earth and Web Services
• Poor native support for OGC web services• BUT can link with a website that generates
KML dynamically– Perhaps with data sourced from OGC services
• Some OGC implementations have KML as a direct output format
• Creative use of KML can lead to sophisticated systems!
• (We are preparing a community website for people to share tips on VGs and geo-web)
Communication of scientific phenomena
• Hurricane Katrina, August 2005
• Picture left shows sea surface temperature (UK Met Office) and storm position/intensity (TRACK analysis of ECMWF data)
• Winds cause upwelling of cooler subsurface water on right-hand side of the cyclonic storm track
• (much more obvious in live system!)
Highlighting of risks• Eruption of
Cleveland volcano modelled by PUFF (Alaska VO)
• 4-D simulation of ash cloud– Represented in
KML– Can be animated
in Google Earth• Could overlay with
real-time aeroplane tracks for basic risk assessment
Monitoring an observing system
• BODC use Google Earth as spatial metadata browsing tool for in-situ measurements
• Can easily check for errors– E.g. Ocean data located on
land– Misplaced component of
linear ship track
• Displays “light” metadata, with link to more sophisticated information
• Developed in under a week!
Direction of missions with real-time data
• British Antarctic Survey (BAS) used Google Earth to direct 2 scientific cruises in 2006
• Multiple data streams (ship location, sea temp and salinity, air temp and pressure) streamed to Google Earth in near real time
• Combined with info about wider environment
• Enabled real-time decision-making (e.g. tracking of predators, left)King penguin track
overlain with concurrent chlorophyll and satellite
imagery
Diagnosis of models and observations
• Picture left shows comparison of NEMO model and observations for Nov 2004
• Red dots show bad model-obs fits, green dots are good fits
• Google Earth allows very efficient browsing of these large datasets
• Could read obs and model data from different sources and bring together in Google Earth or another client
Search and Rescue
• ESSC and BMT Cordah
• Use Google Earth as common platform for visualizing:– Oceanographic
numerical model output data
– SAR predictions
• Drives improvements to both models.
Conclusions• Web Services avoid data "dead ends"
– HTML and static images (websites) are "dead ends"– Web Services and GML are "open ends"– KML, SVG are somewhere in between
• Serving data "the right way" allows new science to be done!– Interoperability permits intercomparison– Fast route to visualization (WMS, KML)
• (The best technical solution is not always the most popular with users!)
• Virtual Globes provide an easy way to drive collaborative work:– Quick intercomparison of data– Data discovery– ... but can never be the whole story
Some recommended web searches• "REST vs SOAP" : different approaches to Web Services
• "OpenLayers" : open-source alternative to Google Maps
• "KML tutorial" : (esp. NetworkLinks…)
• "NASA World Wind" : open-source alternative to Google Earth
• "ArcGIS Explorer" : ESRI virtual globe (free)
• "GeoRSS" : Simple georeferencing (KML-lite)
Limitations of Virtual Globes• Large variability among VG
applications. Generally:• Only basic support for OGC
Web Services• Lack of support for
subsurface and submarine data– Picture on right shows a
workaround• No data analysis functions
– But can link with Web Services and websites to do this
• Most do not support GIS file formats (shapefiles, GeoTIFFs)– Need to do a conversion
3-D Gulf Stream shown above ground in Google Earth