StefanoWMO-INSPIRE-Meeting 23-25 Jan 2007

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					                           JRC - ISPRA, 24 January 2007

        INSPIRE Architecture:
Interoperability with the Geosciences
       Information Community
                      Stefano Nativi1 and Gil Ross2
                Members of INSPIRE Metadata Drafting Team

  1 Italian   National Earth & Environment Research Community (INTERO)
                                 2 MetOffice UK
• Interoperability between the Geosciences
  (Earth Sciences) info Community and the
  Geo-Information Community
  – Data model Harmonization issues              Functional
  – Protocols adaptation issues                  Issues
  – Non-functional issues
    •   Quality of Service (e.g. Real-time access)
    •   Fault tolerance for critical missions
    •   Data policy and volume
    •   Trustworthiness
    •   ….
Data Model Harmonization
  Earth Science (Geosciences) Info
• Disciplinary Communities
   –   Geology
   –   Oceanography, limnology, hydrology
   –   Glaciology
   –   Atmospheric Sciences
        • Meteorology, Climatology, Aeronomy, …
• Interdisciplinary Communities
   –   Atmospheric chemistry
   –   Paleoceanography and Paleoclimatology
   –   Biogeochemistry
   –   Mineralogy
   –   ….
• Basic Disciplines
   – physics, geography, mathematics, chemistry and biology

                                              [from Wikipedia the Free Encyclopedia]
   Earth Science (Geosciences) Info
 • Disciplinary and Interdisciplinary models

interdisciplinary   Mineralogy     ….. Paleoceanography         Atmospheric
         models                                                  Chemistry

   ES discipline    Geology      Oceanography     Atmospheric     Glaciology
        models                                      Sciences

           Basic      Chemistry     Physics     Biology   Geography
         models                           Mathematics

                                              Earth Sciences Info Realm
   Geographic Information Realm
 • Stack of model layers
 • A couple of general models (see ISO 19100)
     – Boundary model
     – Coverage model

                      Boundary model      Coverage model
information models

   Basic discipline     Topology       Geography
           models                  Mathematics

                                   GI Realm
            ES and GI Info realms
• Historical and technological differences:

                              ES                                 GI
                              Realm                              Realm

Focus on geo-      Low (low resolution,             High (spatial queries support,
location           intrinsic inaccuracy, implicit   high resolution, explicit
                   location)                        location)
Focus on           High (Temporal series            Low (low variance; epoch
temporal           support, high variance           based approach)
evolution          (seconds to centuries),
                   running clock and epoch
                   based approaches)
Metadata content   Acquisition process              Management & spatial
                   (Measurement geometry            extension (maintainability,
                   and equipment, count             usage constraints, spatial
                   description, etc.)               envelope, evaluation, etc.)
             ES and GI Info realms
• Historical and technological differences:

                         ES                                      GI
                         Realm                                   Realm

Data        Hierarchical tree (multiparameter         Dataset Series
aggregation complex datasets)                         Dataset
levels      Simple trees (time series)                Features
            Grid cell aggregations (clusters,
            regions, topological sets)
            Fiber bundles (multichannel satellite
Data types    Multi-dimensional arrays (at least 3-   Topological features (usually
              D + time)                               2-D geometry) referred to a
                      WMO case
• Observation and Forecast domain
  – Real time data involve observations from surface stations,
    ships, buoys, upper air balloons and in-flight aviation
    transmissions. There are also remote soundings from
    surface sites, radar and satellite soundings which are
    much greater in volume.
  – The raw data from forecasts are “fields” of individual
    parameters from Numerical Weather Prediction models
  – Each NWP model run has values on 4 D grids, which are
    usually projected and sliced onto horizontal grids for
     • The forecast fields are used to create summary forecast products
       to aid decision making which are also disseminated on the GTS.
  – Both the observational data and the forecast fields
    normally require processing for human consumption.
                       WMO case
• Observation and Forecast domain
  – WMO data or NWP (Numerical Weather Prediction)
    models do not have the resolution of geographic data
     • The highest resolution of NWP models in operation is about 4km;
     • The global models use typically a 50km grid resolution.
     • The trend is to higher resolutions, with limitations.
         – Models in the 1 km range, for example may need to resolve
           individual cloud processes.
  – A large part of WMO exchanged data is in the form of
    real-time data
  – WMO data are (almost) all spatio-temporal, and while
    (almost) every dataset has a spatial extent, the data is
    organized instead by date and time.
     • Data all have a time-stamped identifier, while there is (almost) no
       spatial information in the identifier.
                WMO case
• Boundary and coverage models
  – No well-developed features (boundary) and
    coverage models for weather data
  – Projects are developing such models
    • Parts of WMO’s Weather Information System (WIS)
      project – a portal-like system to replace the GTS –
      are working on such models for the specification of
      all WMO real-time and climate summary data.
    • OGC experts on observation and measurements
      are involved in these projects
                  WMO case
• Metadata model
  – In practical terms there are effectively no
    WMO discovery metadata holdings for a
    general user
     • Metadata for public discovery are not generally
       available, in ISO discovery or any similar form.
  – WMO services do not have service metadata
    in the intended form
Service-Oriented Architecture
                Distributed Systems Vs Architectural
                                                         Architectural Styles
Distributed Systems

                                   Object-oriented Resource-               Service-
                                               Object A                    oriented
                                      attribute:Type = initialValue
                                      operation(arg list):return

                                                                              
SOA: Service Oriented Architecture
• Suitable for extensible and heterogeneous distributed
• Interoperability is granted by declaring in a self-
  contained, self-explanatory and neutral way
     1.   Application Interfaces
          Service specification (protocol based; e.g. WSDL)
     2.   Payload data models (data encoding)
          Important part of the service description; semi-structured
          models (e.g. XML schema)
      SOA: payload data models
• GI realm
   – OGC GML (Geography Markup Language)
   – Product related
       • Google KML (Keyhole Markup Language) -- GoogleEarth
       • ESRI ArcXml (Arc eXtensible Markup Language) -- ArcIMS

• Earth Science info realm
   – Plethora of new MLs
       • Holistic approach (at different model levels)
             – ESML, ncML, HDF XML encoding, GeoSciML, SensorML, etc.
       • Reductionist approach
             –   Structural Geology ML (SGeoML)
             –   Exploration and Mining ML (XMML)
             –   MarineXML
             –   Hydrological XML Consortium (HydroXC)
             –   Climate Data ML (CDML)
             –   Climate Science Modelling Language (CSML)
             –   Digital Weather ML (DWML)
             –   ….
   – Binary Data Encoding format
       • GRIB, NetCDF, HDF, BUFR, …
SOA: Interface protocols adapters
• GI realm
  – OWS (i.e. WMS, WFS, WCS, CS-W, WPS, ….)
  – Product related
     • Google Map and Google Earth service interfaces
     • ArcIMS service interfaces
• Earth Science info realm
  – Holistic approach (at different levels)
         – OPeNDAP, THREDDS catalog service, …
  – Reductionist approach
         – CDI, EOLI, …
                         WMO case
• Distribution systems
   – More Push than Pull-based
   – Several service buses
       • Global Telecommunications System (GTS)
           – highly resilient – and therefore costly - worldwide distribution system
       • The Weather Information System (WIS) project is a portal like
         system to supplement then replace the GTS
       • GEONETCast: a global network of satellite dissemination systems
         (involving inter alia, NOAA, WMO and EUMETSAT)
       • TV and Radio.

• Architectural Style
   – None of the existing WMO services operate through Web
   – For services with the volume required for WMO operational
     services or WMO archives, Internet is unlikely to bear the load
     (bandwidth costs and constraints)
                WMO case
• Data encoding
  – None of the WMO codes (alphanumeric and
    table-driven) have yet been converted to an
    agreed XML form,
    • This process is under consideration by the World
      Weather Watch Programme expert teams.
  – Information on observing stations and sensors
    are not formatted in XML
  – Table driven code forms include BUFR and
    CREX , and GRIB data forms.
                     WMO case
• Registry and Catalog services
  – There are lots of catalogues, but not in the form of a
    registry service.
     • This is under development in the WIS project
  – Almost all WMO registers are on-line documents or
    searchable databases.
  – The WMO catalogue for GTS data is available as a
    searchable database, and as published documents
    for the catalogue of bulletins, transmission schedule
    and information for shipping.
     • The catalogue of bulletins does not list bulletins by time, but it
       does list the bulletin and the originator – the disseminating
       station in WMO terms.
              WMO case
• Registry and Catalog services
  – WMO Public Weather Services are browser
    based on NMHS websites and not of a
    standard form.
    • WMO metadata is document based, for WMO
                        WMO case
• View Services
   – WMO members do not offer view services as defined by
       • WMO view services (Public Weather Services) are referenced
         through related links, through NMHSs web services and through
         WMO PWS weather forecast offices.
       • The EC web site for all EC functions, (courts etc) gets 4 million hits
         per day for the whole of Europe!
   – It is difficult to mix the map paradigm for INSPIRE (to pan, zoom,
     navigate etc.) with the natural meteorological paradigm of time
     sequence and animation.
       • While it is technically possible to mix horizontal panning with time
         sequencing, it would be difficult for anyone to understand such a
   – The view service with time sequencing is a service which is
     missing from the INPIRE Architecture Overview.
                WMO case
• Gazetteers Services
  – There are gazetteers of WMO registered
    observing stations, radiosonde stations,
    synoptic and climatological networks, and lists
    of observing ships.
  – This is not a gazetteer service in OGC terms.
                       WMO case
• Download Services
  – Example of available delivery services by request over Internet
      • Web Werdis Web Weather Request and Distribution System of
        DWD Deutscher WetterDienst
      • DPDS Data Production and Delivery System of the UK Met Office
      • Météo France secure download service.
  – A download service is not the usual or preferred mechanism by
    which the NMHSs distribute their data.
  – NMHSs do not rely on users actively requesting data.
  – Nearly all the data services are delivered by a regular
    dissemination of data to registered users.
      • There are always time-critical requirements, particularly for safety of
      • For security, reliability and robustness, these are usually
        disseminated over fixed links or dial-up rather than by Internet.
                WMO Case
• Clearinghouse services
  – WMO’s Weather Information System (WIS)
    project is a portal-like system to subsume the
  – It is highly unlikely that any purely geographic
    portal would have or would want to have the
    capability to handle meteorological data in the
    way the manner being designed for WIS.
• G. Ross, “World Meteorological Organisation data and services
  relevant to the INSPIRE Architecture Overview”, version 0.8, 15
  January 2007.
• S. Nativi, “Interoperability between Earth Sciences and GIS models:
  an holistic approach”, seminar at NCAR and UCAR-UOP, Boulder
  (CO) USA, 27 July 2006. available at

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