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