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Dynamic Quick View, interoperability and the future Jon Blower, Keith Haines, Chunlei Liu, Alastair Gemmell Environmental Systems Science Centre University.

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Presentation on theme: "Dynamic Quick View, interoperability and the future Jon Blower, Keith Haines, Chunlei Liu, Alastair Gemmell Environmental Systems Science Centre University."— Presentation transcript:

1 Dynamic Quick View, interoperability and the future Jon Blower, Keith Haines, Chunlei Liu, Alastair Gemmell Environmental Systems Science Centre University of Reading United Kingdom

2 Introduction We have developed an interactive website and map server for data visualization –work originated in UK e-Science programme and National Centre for Ocean Forecasting Takes advantage of freely-available Web GIS tools We have integrated our prototype with the MERSEA system (via OPeNDAP) –not yet an approved MERSEA service We hope to demonstrate the exciting potential of this system and benefits of adherence to open standards –Will be very important in INSPIRE Potential use is much wider than marine science

3 Dynamic Quick View (DQV) Service Gives very fast previews of 4-D data on an interactive website Reads data from OPeNDAP servers at the MERSEA TEPs Draggable, zoomable map Allows the fast creation of animations Based on a standards-compliant Web Map Service

4 Selection of depth Select from all the depth levels of the model

5 Selection of time (range) Select from all the timesteps in the model Selection of a time range leads to an animation

6 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

7 Timeseries plots If a time range is selected, can create a timeseries plot at a point

8 Export to Google Earth DQV website contains link to load currently-visible data into Google Earth –Our WMS outputs in KMZ format Can then view data alongside other KML datasets –e.g. DAMOCLES Can view animations of data No problem with map projections!

9 Visualize alongside third-party data Hurricane Katrina, August 2005 Showing sea surface temperature (UK Met Office) and storm position/intensity (ECMWF) Winds cause upwelling of cooler subsurface water on right-hand side of the cyclonic storm track

10 Selection of non-MERSEA datasets also available OSTIA (GHRSST-PP): SST and sea ice high res (1/20°) NSIDC Snow-water equiv. (non-NetCDF) ECMWF System 3 Reanalysis Everything on the website can be exported to Google Earth

11 The Web Map Service DQV website is built on a custom-made WMS –backwards-compatible with OGC spec, version 1.3.0 Optimized for fast, dynamic generation of map images Enhancements to allow changing of colour scale, generation of timeseries plots, etc Reads data from CF-NetCDF files or OPeNDAP servers –reading directly from NetCDF is more efficient OPeNDAP NetCDF WMS

12 Important features of our WMS implementation Fast generation of images Handling of four-dimensional data Handling of data on unusual grids, e.g. NEMO Dynamic change of colour scale extent Generation of animations Export to Google Earth

13 Current DQV architecture: centralized OPeNDAP NetCDF TEP 1 OPeNDAP NetCDF TEP 3 OPeNDAP NetCDF TEP 2 WMS DQV website Requires minimal setup Single point of failure Relies on fast, reliable OPeNDAP servers Background imagery (from NASA etc)

14 Possible future DQV architecture: federated OPeNDAP NetCDF TEP 1 DQV website Requires each TEP to install WMS No single point of failure More efficient WMSOPeNDAP NetCDF TEP 2 WMSOPeNDAP NetCDF TEP 3 WMS Third-party WMS Background imagery (from NASA etc)

15 MERSEA data in third-party clients NASA World Wind Cadcorp SIS Google Earth

16 In-situ data 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 do the same for MERSEA systems, e.g. CORIOLIS Could read obs and model data from different sources and bring together in Google Earth or another client

17 DQV future enhancements Display of wind/current fields as vectors Caching of image tiles for performance increase Support for more map projections –E.g. polar stereographic Display of observations on website Integration with GeoServer, THREDDS –Requires community assistance …Lots more!

18 Conclusions We have demonstrated a dynamic website for exploring MERSEA data quickly and interactively Based on an OGC Web Map Service –but with important enhancements –other WMS implementations will not support all the features in DQV Gives interoperability with third-party services –view MERSEA data alongside third-party data –will be important in INSPIRE Exciting possibilities for the future!

19 Contact details jdb@mail.nerc-essc.ac.uk To find website: Google for "Godiva2"


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