International Standards for Data Interoperability: Earth Sciences and GIS models interoperability

1. Atmospheric Data Access for the Geospatial User Community (ADAGUC) 3-4 October 2006 - KNMI (De Bilt, Netherlands) International Standards for Data Interoperability:Earth Sciences and GIS models interoperability Stefano Nativi Italian National Research Council (Institute of Methodologies for Environmental Analysis) and University of Florence nativi@imaa.cnr.it

2. Rationale • Growing demand of Society to discover and access Geospatial Information (GI), in a seamless and RT way: • Applications and initiatives • Decision Support Systems (DSS) • Science Digital Library (NSDL) • Global Monitoring for Environment and Security (GMES) • Spatial Data Infrastructures (INSPIRE) • GEO System of Systems (GEOSS) • Technological drivers • Increasing resolution and availability of remotely sensed data • Growing number of operational satellites and sensor networks • Ubiquitous connectivity throughout the Society • Growing computing and storage capabilities

3. Geospatial Information/Data LM ES • Stem from two main realms • Land Management Community • mainly using GIS • Earth Sciences Community (or Geosciences Community) • Historical and technologicaldifferences: • Acquisition sensors and process • Space and time resolutions • Amount of data • Metadata scopes • Applications and users

4. LM ES Geospatial Data Acquisition and Encoding • Society platforms and systems are GIS-based • A GI standardization framework has been defined for geospatial data interoperability To add ES resources to this picture • Three main processes SOCIETY INFRASTRUCTURES, PLATFORMS and SYSTEMS Using Standard Models and Interfaces for GI Interoperability Knowledge Extraction and Harmonization

5. GI ISO 19100 series OGC OWS OGC GML CEN profiles INSPIRE IR …. ICT Semi-structured models Science Markup Languages WS-I Grid services MDA SOA OOAD …. GI Standardization Framework • Interoperability Experiments • OGC GALEON IE • OGC GEOSS Service Network (GSN) • GMES testbeds • NSDL testbeds • INSPIRE testbeds • OGII • …. SOCIETY

6. Provide Information Society with an effective, NRT and easy-to-use fruition of multidimensional Earth Science datasets (e.g. 4/5-D) Main Objective SOCIETY INFRASTRUCTURES, PLATFORMS and SYSTEMS Explicit Semantic level / Interoperability level Standard Models and Interfaces Geospatial datasets Acquisition and Encoding Knowledge Extraction and Harmonization

7. Land Management Info Realm Earth SciencesInfo Realm Info Communities Interoperability • Imply to conceive and implement Info realms interoperability • Data & metadata models • Related services SOCIETY INFRASTRUCTURES, PLATFORMS and SYSTEMS GISRealm

8. Earth Science (Geoscience) Info Communities • 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]

9. Interoperability Model How to pursue Interoperability? • Holistic approach • A common interoperability model • Reductionist approach: • An interoperability model for each discipline Mineralogy Paleoceanography AtmosphericChemistry ….. Glaciology Geology Oceanography AtmosphericSciences GIS Realm Chemistry Physics Biology Geography Mathematics Earth Sciences Info Realm

10. Domain Models: an holistic view

11. Over-simplified Worldviews • To the Geographic Information community, the world is: • A collection of features (e.g., roads, lakes, plots of land) with geographic footprints on the Earth (surface). • The features are discrete objects described by a set of characteristics such as a shape/geometry • To the Earth Science community, the world is: • A set of event observations described by parameters (e.g., pressure, temperature, wind speed) which vary as continuous functions in 3-dimensional space and time. • The behavior of the parameters in space and time is governed by a set of equations. [from Ben Domenico]

12. A visual example: Traditional GIS view [from Ben Domenico]

13. A visual example: Atmospheric Science view [from Ben Domenico]

14. Historical and technological differences: ES and GI Info realms ES Realm GIS Realm

15. Historical and technological differences: ES and GI Info realms ES Realm GIS Realm

16. Netcdf-3 Data Model [from J. Caron]

17. OPeNDAPDataModel(DAP-2) [from J. Caron]

18. HDF5 Data Model [from J. Caron]

19. GIS Abstract Data Models General feature model (in both OpenGIS and ISO TC 211 specs) Feature Feature Topology Feature Attribute Location Attr. Non-Spatial Attr. Spatial Attr. Temporal Attr. GM (Geometry Model) Object

20. GIS Abstract Data Models • Simplified schema of ISO 19107 geometry basic types GM (Geometry Model) Object GM_Point GM_MultiPoint GM_CompositePoint GM_Surface GM_Solid GM_Curve

21. Domain Models Harmonization abstract solution

22. Coverage • compilation of values of a single property across the domain of interest • data prepared for analysis/pattern detection Observ.s Vs. Features: Value-added Chaining • (Event) Observation • estimate of value of a property for a single specimen/station/location • data-capture, with metadata concerning procedure, operator, etc • Feature • object having geometry & values of several different properties • classified object • snapshot for transport geological map elements • object created by human activity • artefact of investigation borehole, mine, specimen [from S.Cox Information Standards for EON]

23. The Coverage concept • Coverage definition A feature that acts as a function to return one or more feature attribute values for any direct position within its spatiotemporal domain [ISO 19123] • An extremely important concept to implement model interoperabilty • A coverage is a special case of (or a subtype of) feature [The OpenGIS™ Abstract Specification Topic 6: The Coverage Type and its Subtypes].

24. Model ES data as Coverage • To explicitly mediate from a ES hyperspatial observation data model to a GIS coverage data model • To express ES obs. semantics using GIS the Coverage elements

25. Scalar measured quantities explicit/semi-implicit/implicit Geometry <dimension>, <variable> <variable> 01101100111 11010101010 010101… 01101100111 11010101010 010101… ES Dataset content N-Dimension Coordinate Systems <dimension>, <coordinateSystem> <coordinateAxis> <netcdf type> multidimensional Observation dataset (e.g. 4/5D hypercube)

26. explicit/implicit Geometry <gridDomain>, <rectifiedGrid Domain>, <multipointDomain> Spatial Reference System (SRS) <GeographicCRS> GIS coverage content 2D Spatial Coordinate System + elev + time <_CoordinateSystem>, <coordinateSystem Axis> Range set <_Coverage> <rangeSet> 2D+elev+time dataset

27. N-Dimension Coordinate Systems 2D SCS + elev + time 2 Dimension Coordinate System 2 Dimension Coordinate System 2 Dimension Coordinate System 2 Dimension Coordinate System Implicit/explicit Geometry Implicit/explicit Geometry Implicit/explicit Geometry Implicit/explicit Geometry Implicit/explicit Geometry Spatial Reference System (SRS) Spatial Reference System (SRS) Spatial Reference System (SRS) Spatial Reference System (SRS) Spatial Reference System (SRS) explicit/semi-implicit/implicit Geometry 2D+elev+time dataset Range set Range set Range set Range set Range set s S Scalar measured quantities S S S 01101100111 11010101010 010101… 01101100111 11010101010 010101… The Mediation Process 2D + elev + time Coverages ES hyperspace dataset (3/4/5D) a Coverage

28. Introduced GIS Coverage conceptsin brief • A dataset origins several different coverages • Each coverage is characterized by a domain, a range-set and is referenced by a CS/CRS • Each coverage is optionally described by a geographic extent • Each domain is characterized by a geometry • Supported domains: evenly spaced grid domain, non evenly spaced grid domain and multipoint domain • Each range-set lists or points set of values associated to each domain location • Supported range-set types: scalar range-set and parametric range-set

29. An Implemented Solution

30. The Implementation • ES data model • netCDF • Extra metadata: CF conventions • GIS Coverage model • ISO 19123: DiscreteGridPointCoverage • Harmonization implementation-style • Declarative style • Mediation Markup Language • Rule-based procedure

31. CF-netCDF Model • NetCDF data model was extended adding a set of conventions • One of the most popular convention is the Climate and Forecasting metadata convention (CF) • Introduce more specific semantic elements (i.e. metadata) required by different communities to fully describe their datasets netCDF Model

32. DiscreteGridPointCoverage

33. 1…n 0…1 0…1 Mapping Rules

34. Domain and Functional Definitions Observation Data/Observation b: d c d, c  B= {b} Dataset Spatial Domain Coverage

35. Domain and Functional Definitions Observation to Coverage Operator Dataset to Coverage Operator Coverage Portrayal Operator

36. GML ncML Encoding level Data model harmonization: Implementation style Earth Sciences Information Community GIS Information Community Abstract Mapping rules Abstract model level Hyperspatial Observation Coverage/Feature Content Mapping rules Content model level netCDF + CF ISO 19123 Coverage Model Declarative Approach

37. ncML-GML • Mediation Markup Language • An extension of ncML (netCDF Markup Language) based on GML (Geography Markup Language) grammar

38. Java Web Start Available Language specification and Tools • The ncML-GML markup language implements the presented reconciliation model • It is a Mediation Markup Language between ncML (netCDF Markup Language) and GML • An extension of ncML core schema, based on GML grammar • NcML-GML version 0.7.3 • based on GML 3.1.1 • N2G version 0.8 • Java API for ncML-GML ver. 0.7.3 • WCS-G • WCS 1.0 which supports ncML-GML/netCDF documents • Subsetting (domain and range-set) • netCDF • ncML-GML 0.7.3 • WCS light client • Test client for WCS-G • GI-go thick client

39. Experimentation • OGC GALEON IE • Geo-interface for Air, Land, Earth, Oceans NetCDF • OGC GEOSS Service Network • Lucan SDI • Pilot Application: Hydrogeological disturbances survey

40. Spatial Data Infrastructure (Geospatial Data Infrastructure) • SDI mission • mechanism to facilitate the sharing and exchange of geospatial data. • SDI is a scheme necessary for the effective collection, management, access, delivery and utilization of geospatial data; • it is important for: objective decision making and sound land based policy, support economic development and encourage socially and environmentally sustainable development • Main functionalities • Resource Discovery • Resource Evaluation • Data Portrayal (Preview) • Data Mapping (Overlaying & Visualization) • Data Transfer

41. Access Infrastructures Technological Standards Security Infrastructure Data Policy Geospatial Resources SDI Architecture SOCIETY • Two kinds of Geospatial resources • ES • Land Managements(mainly GIS-based) ESS Realm Land Management Realm

42. CS-W Data tier Data Discovery tier Data Access tier Access and Download Services Catalog services based on ISO 19115 profiles Thematic Portals GML WFS Protocol s Adaptation Protocol s Adaptation Protocol s Adaptation View services netCDF ADDE HDF IDD/LDM GRIB WCS WCS WC MS Data Models Mediation Data Models Mediation Data Models Mediation G . . . 2 THREDDS Data Server View services OPeNDAP WMS WMS Others... Data Presentation tier HTTP SDI Architectural Framework Land Manag. GeoTIFF DWG SHP Server-based GIS . . . Others... ES

43. WCS WC MS G 2 Main Technologies • GIS technologies • OGC WFS, WCS, WMS, GML, ISO 19115 profile (e.g. INSPIRE) • ES technologies • CF-netCDF, ncML, TDS/OPenDAP, etc. • Interoperability technologies • ncML-GML, GI-cat, WCS-G, WC2MS

44. WCS G NcML-GML: model harmonization Data Models Mediation ncML-GML Encoding Model netCDF Data Model CF Metadata ncML EncodingModel WCS 1.x Content Model GML 3.x EncodingModel ISO 19123 Coverage Model WFS Content Model GIS Information Community Earth Sciences Information Community GIS - Coverages ES Observation Dataset

45. NASA ESG GI-Cat • Caching, asynchronous, brokering server with security support, which can federate six (seven) types of information resources • Catalog of Catalogs or Catalog Gateway solution • Service-oriented technology CS-W Message-oriented asynchronous interaction

46. GI-go • To present all the different federated servers as a unique catalog server (e.g. a CS-W server) • A GUI to implement user interaction GI-profile

47. WC MS 2 WCS G WC2MS • A solution to introduce semantics: • To reduce domain dimensionality • To reduce co-domain dimensionality • The above semantics is captured and encoded in CPS request parameters Extra Semantics WMS Map Coverage Coverage Portrayal Service

48. Main Conclusions • ES and GIS data model interoperability is more and more important for Society’s applications • Standards should be conceived and used for holistic interoperability solution rather than reductionist ones • The GIS coverage concept seems to be a good solution to bridge GIS and ES data models • Complex ES datasets (hyperspatial data) could be projected generating a set of “simpler” but more specific coverages • A solution for mapping complex hyperspatial netCDF-CF1 datasets on a set of GIS coverages has been developed: the ncML-GML • It was experimented in the framework of the OGC GALEON IE through OGC WCS; OGC GSN and the Lucan SDI • Data interoperabiltiy solutions, along with catalog interoperability ones, are crucial to develop effective SDI