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SAN DIEGO SUPERCOMPUTER CENTER International Water Information Systems: Evolving the CUAHSI HIS to a Standards-based Infrastructure David Valentine Ilya.

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Presentation on theme: "SAN DIEGO SUPERCOMPUTER CENTER International Water Information Systems: Evolving the CUAHSI HIS to a Standards-based Infrastructure David Valentine Ilya."— Presentation transcript:

1 SAN DIEGO SUPERCOMPUTER CENTER International Water Information Systems: Evolving the CUAHSI HIS to a Standards-based Infrastructure David Valentine Ilya Zaslavsky David Arctur

2 SAN DIEGO SUPERCOMPUTER CENTER Overview Background: Acronyms Translator Water Information Services Concept Study Viewpoints Enterprise Viewpoint Information Viewpoint –WaterML Computation Viewpoint –Mapping to OGC Engineering Viewpoint –Catalog –Discovery Services Monitoring and Reporting

3 SAN DIEGO SUPERCOMPUTER CENTER Delivering Water Information is more than time series Services/Data Sources 10’s to 1000’s Sites 1 to 1 million Phenomena 1 to 10,000 Series 10’s to millions Site, Phenomena, Data Type, statistics, Time Range, Count quality control level (1+) source (1+), method (1+) Domain Lists Organizations, Methods, QC, Units Results/Data Values date, value, censored, quality control level, source, method, qualifier (1+), sample code Analytical Chemistry Details WQX HIS is not one service. HIS based on OGC standards will be a set of services

4 SAN DIEGO SUPERCOMPUTER CENTER Open Geospatial Consortium Acronyms WMS Web Map Server. Returns an image WFS Web Feature Server. Returns Geography Markup Language. Demonstrated by UT to provide series and sites CSW Catalog Services for the Web Geodata, Geo services For Example: ESRI Geoportal SOS Sensor Observation Service Create, manage sensors. Discover and retrieve results WPS Web Processing Service

5 SAN DIEGO SUPERCOMPUTER CENTER CUAHSI to Open GIS translator CUAHSIOGC Observations and Measures SiteFeature VariableObserved Phenomena Series~Observation DataValueResult MethodProcedure TimeSeries Values listTimeSeriesCoverage WaterML:Timeseries Controlled VocabularyCoded Domain

6 SAN DIEGO SUPERCOMPUTER CENTER Water Information Services Concept Development Study Report Open Geospatial Consortium Engineering Document Outlining the CUAHSI Experience, and the migration to OGC Standards

7 SAN DIEGO SUPERCOMPUTER CENTER Geospatial Service Architecture Viewpoints

8 SAN DIEGO SUPERCOMPUTER CENTER Drivers for the Concept Development Study New requirements stemming from operational experience with existing system, as expressed by government and other users: Transition to OGC model – for better interoperability, including international: what is the suggested path, what are new service interfaces, and what may be missing from this reference model? Federation of catalogs – since many data providers stand up catalogs, also better scalability: what is the suggested combination of catalog technologies and interfaces? Recognition that we don’t need to search over all services: what are the better search patterns (e.g. 3-step data access: identify services, then extract time series metadata, and then request data content for the time series)? Recognition that we can (and need to) rely on common implementations of mature, modular standard specifications: what is an appropriate operational governance model for distribution of roles and responsibilities within such a modular system?

9 SAN DIEGO SUPERCOMPUTER CENTER ENTERPRISE VIEWPOINT Purpose, scope, policies: What for? Why? Who? When? © 2011 Open Geospatial Consortium, Inc.

10 SAN DIEGO SUPERCOMPUTER CENTER The Enterprise Agenda Addressing key bottlenecks of hydrologic data sharing and integration for the next decade: As massive volumes of hydrologic data become available it is important to develop sophisticated data integration strategies and architectures enabling re-purposing and re-using observations Distributed hydrologic data should be easily discoverable Data are structurally and semantically heterogeneous, follow different spatial and temporal sampling patterns, and undergo different types of processing before they become available Addressing problems that could not be addressed before (e.g. regional and continental scale modeling, global climate change effects, large-scale disaster response) requires clarification in the roles and responsibilities of all system stakeholders, including government and academic monitoring and research activities Making hydrologic data publishing easy with standards-compliant mainstream software Integrating government and academic sources of hydrologic observations Integrating data across research domains and languages © 2011 Open Geospatial Consortium, Inc.

11 SAN DIEGO SUPERCOMPUTER CENTER Answering key Enterprise-level questions - 1 Suggested migration path: Mapping CUAHSI HIS architecture to OGC reference model –Mapping of information models (for features, time series, catalogs) to OGC encoding specifications described in the Information Viewpoint –Mapping of data access, metadata, catalog and processing services to OGC service interface specifications described in the Computational Viewpoint –Mapping of specific technologies used in CUAHSI HIS to technologies implementing OGC- RM is described in the Engineering Viewpoint Elements missing from the OGC reference model: Managing semantic descriptions and controlled vocabularies –How is the uniform semantic framework established and curated –Where is semantic compliance established and validated –Which semantic compliance responsibilities are assumed by each role in the system Modeling of time series catalogs, and their interaction with service registries –It appears that for catalogs of services and datasets OGC offers mature CSW-ISO specifications, while suggesting custom CSW/ebRIM development – see Information Viewpoint Access control at the level of time series © 2011 Open Geospatial Consortium, Inc.

12 SAN DIEGO SUPERCOMPUTER CENTER Answering key Enterprise-level questions - 2 Catalogue federation: Multitude of CSW profiles and implementations make it difficult to federate catalogs; Federation use cases need to be defined, demonstrating advantages of catalog federation for hydrologic observation service catalogs and for catalogs that index resources other than hydrologic data services Search patterns: How OGC query interfaces express distributed discovery of hydrologic data, using semantic, spatial and temporal filters for services and time series What are pros and cons of different architecture patterns enabling data discovery and retrieval Operational governance model: What are the key roles in the operational system, and how do they change with the transition to the standards-based model: –With respect to governing: encodings and service signatures; community vocabularies and ontologies; mappings between semantic concepts and domain of values; catalog curation; validation and system monitoring Defining best practices for publishing hydrologic data and catalogs, enabling applications /implementations clearinghouse © 2011 Open Geospatial Consortium, Inc.

13 SAN DIEGO SUPERCOMPUTER CENTER INFORMATION VIEWPOINT Information sources and models: What is it about? © 2011 Open Geospatial Consortium, Inc.

14 SAN DIEGO SUPERCOMPUTER CENTER Information Models and Encodings For hydrologic observations: WaterML 1.x/ODM (in the original CUAHSI HIS) – transitioning to  WaterML 2.0 (upcoming OGC standard) WQX (EPA): eventually may serve as a model for an O&M profile for analytical chemistry/water quality sampling Other extensions: a lightweight profile of WaterML2; encoding of rating curves; forecasting (and uncertainty) For hydrologic catalogs: Time series catalog encoding as defined by CUAHSI HIS (GML simple features) ebRIM v. 3.0 (XML) ISO (services), ISO Other relevant: Instruments: SensorML; access rules: GeoXACML; error/accuracy: UncertML © 2011 Open Geospatial Consortium, Inc.

15 SAN DIEGO SUPERCOMPUTER CENTER Water Markup Language 1.0 An XML schema used by CUAHSI web services to communicate time series information in a standard format. Uses Observational Data Model semantics Result of the CUAHSI Hydrologic Information System project. It is a standardized way to convey water information over web services.

16 SAN DIEGO SUPERCOMPUTER CENTER Water Markup Language 2.0 An international effort to communicate the semantics of water information under the Hydrology Working Group of the Open Geospatial Consortium Create an open, re-usable and useful, standard for the exchange of hydrological data sets A UML model attempting to capture the semantics of hydrologic information A XML schema, which uses GML to represent the information.

17 WaterML 2.0 Information is linked

18 Request WaterML 2 Request Feature (WFS) Request Procedure

19 SAN DIEGO SUPERCOMPUTER CENTER COMPUTATION VIEWPOINT Types of services and protocols: How does each bit work? © 2011 Open Geospatial Consortium, Inc.

20 SAN DIEGO SUPERCOMPUTER CENTER Services and Protocols For hydrologic observations: WaterOneFlow (in the initial CUAHSI HIS) - transitioning to  Sensor Observation Service (SOS1/ SOS2, with Data Availability Extension) For hydrologic features: Web Feature Service (WFS) For hydrologic time series and individual observations at points: Web Feature Service (WFS) CSW-ebRIM, CSW-OWL For hydrologic service registry: CSW-ebRIM, CSW-OWL, CSW-ISO For querying: Filter Encoding Standard (FES) For access control: Shibboleth, Distributed Access Control System (DACS) Other to consider: Sensor Instance Registry (SIR), Sensor Observable Registry (SOR) © 2011 Open Geospatial Consortium, Inc.

21 SAN DIEGO SUPERCOMPUTER CENTER Mapping WaterOneFlow to OGC WaterOneFlow (All WaterML 1.x) WFS (DataCart) CSWSOS Location/SiteGetSites (0..n) GetFeature (0..n) (returns GML /WaterObservat ionPoint) GetFeature (returns Simple GML) GetRecords (returns Service Metadata Records) (HDWG Best Practice: use WFS) GetFeatureOfInterest (optional ) DescribeSensor(m) VariableGetVariables GetCapabilities (as keywords) SeriesGetSiteInfoGetFeature (returns Simple GML) GetRecords (returns Custom Record) GetCapabilities /offering Get Data Availability (optional extension) DataValues/ Observations/ Results GetValues(records contain Pointer) GetObservation (returns WaterML 2) (records contain pointer to Feature)

22 SAN DIEGO SUPERCOMPUTER CENTER ENGINEERING VIEWPOINT Solution types, distribution infrastructure: How do the components work together? © 2011 Open Geospatial Consortium, Inc.

23 Possible Architecture A large observation data repository case: a CSW for the data repository is registered in the federated catalog system Main Catalog Distributed Catalog CSW-GetRecords Persisted Datasource CSW-GetRecords PUBLISH –(Register) CSW-GetRecords WFS Filters SOS Filters WCS Filters CSW-Harvest GetCapabalties WFS WCS SOS WMS FTP/HTTP Metadata Coverage Map Access Data Clients

24 SAN DIEGO SUPERCOMPUTER CENTER

25 Architecture Variation 25 A smaller observation network case: individual water data services are registered in the central federated catalog, possibly a local CSW node is registered there as well

26 SAN DIEGO SUPERCOMPUTER CENTER OGC CUAHSI HIS Water Web Services Water Web Service Water Web Data Service Water Web Catalog Service Water Web Ontology Service Water Quality Exchange Service Map Services Processing Services REST SOS (Sensor) WFS (Features) WMS (Maps) REST WPS REST/SOA P Catalog WFS (Features) WMS (Maps) REST SOS (Sensor) WFS (Features) WMS (Maps) REST WPS

27 SAN DIEGO SUPERCOMPUTER CENTER CATALOGING AND DISCOVERY

28 SAN DIEGO SUPERCOMPUTER CENTER Catalog technologies (1) Step 1: Study of distributed search vs harvesting metadata into a central catalog © 2011 Open Geospatial Consortium, Inc. Goal: make joining the system easy by relying on COTS catalogs Solution in CUAHSI HIS: use a combination of distributed search and harvesting, to optimize performance while maintaining autonomous catalog nodes. For example, large agency repositories would expose catalog services and vocabulary services to enable catalog federation and distributed search; for smaller academic services harvesting (along with versioning, provenance management and centralized curation and monitoring) is a better strategy

29 SAN DIEGO SUPERCOMPUTER CENTER Catalog technologies (2) © 2011 Open Geospatial Consortium, Inc. Gi-CAT HydroPortal SDSC HIS Central WFS HydroPortal UTA CSW service HydroPortal UTA ESRI WFS HydroPortal CUAHSI Multiple HydroPortal CSW servers Harvested THREDDS (Gi-CAT) MotherlodeNAMModels Solution in CUAHSI HIS: hierarchical organization of federated catalogs to support indexing both time series and grid data services, taking advantage of different capabilities of CSW implementations. CUAHSI Central Office maintains both Gi-CAT and ESRI HydroPortal CSW nodes, to federate catalogs from multiple organizations. The SDSC HydroPortal federates time series service catalogs and indexes academic WFS time series metadata services

30 SAN DIEGO SUPERCOMPUTER CENTER Discovery Patterns Step 1: define different discovery use cases within the scope of time series analysis, and assemble supporting technologies (catalogs, filter encoding, query services and user interfaces) Step 2: define new discovery patterns given the hierarchy of catalogs Step 3: implement new discovery patterns in software Solution in CUAHSI HIS: filtering by location (Where), time (When), attribute (What), provider (Who) 3-step data discovery and access pattern: Initial semantics-based and location-based discovery over integrated catalog at the CUAHSI Central Office, which aggregates service registries and semantic search from registered CSW catalogs (faceted search on the UI; ontology-based search) More detailed time series discovery over the appropriate WFS services only (either directly at sources, or as harvested and curated at the central time series catalog at SDSC) Data access and retrieval once time series are found Where What When Who (services) Goal: make data discovery efficient over distributed catalogs © 2011 Open Geospatial Consortium, Inc.

31 SAN DIEGO SUPERCOMPUTER CENTER

32 Services Monitoring and Reporting A distributed system with distributed responsibility requires monitoring of the services Monitors Monitoring Service – R-U-On.com Machine Monitors Web Site Monitors Custom Monitors HIS Central Services WaterOneFlow Services –Reliability will be calculated Reporting Logged requests are analyzed via a Microsoft SQL Server Reporting Server Beginning to test Google Analytics

33 SAN DIEGO SUPERCOMPUTER CENTER R-U-On

34 SAN DIEGO SUPERCOMPUTER CENTER

35 Reporting Service

36 SAN DIEGO SUPERCOMPUTER CENTER Google Analytics

37 SAN DIEGO SUPERCOMPUTER CENTER

38 Summary Water Information Services Concept Development Study Report provides an outline for moving the HIS infrastructure to OGC Standards HIS based on OGC standards will be a set of services Discovery via CSW and WFS Data Retrieval via SOS Mapping via WMS/WFS WaterML 2 is a profile of OGC Observations and Measures Services Monitoring and Reliability will be a component of future systems

39 SAN DIEGO SUPERCOMPUTER CENTER Delivering Water Information is more than time series Services/Data Sources 10’s to 1000’s Sites 1 to 1 million Phenomena 1 to 10,000 Series 10’s to millions Site, Phenomena, Data Type, statistics, Time Range, Count quality control level (1+) source (1+), method (1+) Domain Lists Organizations, Methods, QC, Units Results/Data Values date, value, censored, quality control level, source, method, qualifier (1+), sample code Analytical Chemistry Details WQX HIS is not one service. HIS based on OGC standards will be a set of services

40 SAN DIEGO SUPERCOMPUTER CENTER Hydrology Domain Working Group Formed in December 2008 CUAHSI, CSIRO (Australia), and WMO are the co- chairs WaterML under development First working group meeting held March participants 7 countries ~ 12 organizations: WMO, USGS, CSRIO, CUAHSI, Kisters and many others Interoperability experiments

41 SAN DIEGO SUPERCOMPUTER CENTER Information Scope Observation styleDescription In-situ, fixed observation style Generally temporally dense, spatially sparse, small number of observed phenomena. Examples: river level or stage, river discharge, storage level, rainfall etc. Ex-situ, complex processing observations Temporally sparse, spatially sparse, many observed phenomena. Examples: nutrients (nitrate, phosphorus etc.), pesticides (atrazine, glyphosate etc.), biologicals, pH, turbidity etc. Complex data productsThese consist of processed or synthesized observational data, mainly created to provide estimation of not directly measurable phenomena or predictions of future values. Examples: outputs from models or algorithms, water storage estimates, calculation of complex physics- chemistry, biological indices (French : IBGN, German/Austrian : Saprobic Indice,...).

42 SAN DIEGO SUPERCOMPUTER CENTER Harmonzing Hydrologic Data Semantics Harmonize Time series structures (results); General metadata for the procedure used in measurement; Minimal metadata data for spatial features (descriptions of stations) and guidance on linking to external descriptions; Techniques for linking to definitions of observed phenomenon First step to defining a common information model Paper to be released in April

43 SAN DIEGO SUPERCOMPUTER CENTER Adopting a common model Generating an XML schema from the core WaterML UML model that suits a deployment platform Defining or importing other specific schema requirements Linking a schema to vocabulary definitions Generating documentation Customising a validation framework Adapting tools © 2009 Open Geospatial Consortium, Inc. 43

44 SAN DIEGO SUPERCOMPUTER CENTER Tradeoffs Soft-typing vs. hard-typing Data Exchange vs Archival Standalone vs. Reference to information © 2009 Open Geospatial Consortium, Inc. 44

45 SAN DIEGO SUPERCOMPUTER CENTER Features Defining a large set of hydrologic features is out of scope Define a set of in-situ monitoring points: Monitoring station descriptions Requirements for metadata: Existing standards GRDC profile Domain users

46 SAN DIEGO SUPERCOMPUTER CENTER Time Series Encoding A conceptual time series model, with: A GML-style coverage encoding A SWE Common encoding Others (as determined by Interoperability Experiments)

47 SAN DIEGO SUPERCOMPUTER CENTER Procedure Descriptions Define a basic process structure with metadata Provide linkage mechanisms for full descriptions

48 Example river flow observation in UML 48 A doppler flow meter was used to make a flow measurement of the Macquarie river at the Macquarie at Trefusis station. The result of this observation was a time series. The Macquarie River is in the South Esk Basin GML note: Nearly Everything is a Feature Type

49 SAN DIEGO SUPERCOMPUTER CENTER WaterML 2 © 2009 Open Geospatial Consortium, Inc. 49

50 SAN DIEGO SUPERCOMPUTER CENTER Interim Summary We have a group working on an international standard for communicating water information This is going to be a long process HIS provided an entire stack: We need to talk about data discovery, and delivery, aka services Testing WaterML and Services Interoperability Experiments

51 SAN DIEGO SUPERCOMPUTER CENTER Original Water Web Service Get Sites Get Site Info (Series) Get Variables Get Values

52 SAN DIEGO SUPERCOMPUTER CENTER Services (1/2) Sites Map them WFS WMS – too many to send over wfs Together. WMS with paged WFS Phenomena Describe What variables are available Discover What sites in area have this phenomena Series Discover them CSW What sites in area have this phenomena –With this time period –Spacing –Squlity, method Show me the best quality Map them WFS+WMS Give me all

53 SAN DIEGO SUPERCOMPUTER CENTER Services (2/2) Domain Organizations, Methods, QC, Units, Ontologies Data SOS WaterML 2 Analytical Chemistry Details Fixed URL reference? WQX

54 SAN DIEGO SUPERCOMPUTER CENTER Water Web Data Services Client Water Web Catalog Service Data Services Mapping Services Service Interactions Search Results Image of Search Results Water Quality Exchange Services Reference to Analytical Metadata Analytical Chemistry Details

55 SAN DIEGO SUPERCOMPUTER CENTER Interoperability Experiments Groundwater (Dec 2009 to Dec 2010) Surface Water (June 2010 to ?) Water Quality (TBD) Modeling (TBD)

56 SAN DIEGO SUPERCOMPUTER CENTER Groundwater Interoperability Experiment Plotting of Water Well levels across the US/Canada Border Uses: GroundwaterML as the description for the Well “features” Sensors Web Enablement Common for results Lessons so far Sensor Observation Service 1 million wells features breaks works with some hacks Features What do you link the data with. –A well, –a well depth, –screen at a depth in a well Demo linklink

57 SAN DIEGO SUPERCOMPUTER CENTER Surface Water Interoperability Experiment Test the transmission of surface water Three use cases Cross Border Visualize information across border Forecasting Find streamflow forecast data and download Global Runoff (WMO Global Runoff Data Center) Provide automated runoff volume data for large rivers

58 SAN DIEGO SUPERCOMPUTER CENTER Participation Do you have a use case that you think should be covered by a Water Information Standard? In order to become a participant in this IE, an organization must be willing make a resource commitment and a substantial contribution in one or more of the following areas: An OGC web service component (SOS, WFS, WMS) for surface water data; a web client that makes use of service components, OR testing of the Services/Clients, OR compilation of documentation into one or more of the Interoperability Experiment deliverables (note that all participants must also provide sub-reports for inclusion in the final reports)

59 SAN DIEGO SUPERCOMPUTER CENTER Summary Transitioning to a vetted open standard will be a long process WaterML 2 and how water information is delivered will be tested through a series of interoperability experiments A hydrologic information system will be a set of services, not all of which can be defined using presently defined open gis standards We will need to some roll our own We can use these standards to deliver data, now

60 SAN DIEGO SUPERCOMPUTER CENTER Hydrology Domain Working Group Google: Hydrology Domain Working Group Website: gyDWG/WebHomehttp://external.opengeospatial.org/twiki_public/bin/view/Hydrolo gyDWG/WebHome Interoperability Experiments Hydro.dwg mailing list https://lists.opengeospatial.org/mailman/listinfo/hydro.dwg WaterML 2.0 Development Presently limited to participants and observers –Contact us to become an observer April 2010: Finalized Harmonization Report June 2010: Overview, Use Cases and Examples

61 SAN DIEGO SUPERCOMPUTER CENTER Possible Method Naming Convention List Describe Get

62 SAN DIEGO SUPERCOMPUTER CENTER HIS Water Web Services

63 SAN DIEGO SUPERCOMPUTER CENTER Water Web Data Services Client Water Web Catalog Service Data Services Get Water Quality Exchange Services Utilizing WQX Reference to Analytical Metadata Analytical Chem Details

64 SAN DIEGO SUPERCOMPUTER CENTER Local Data Server

65 SAN DIEGO SUPERCOMPUTER CENTER Water Quality Exchange Service

66 SAN DIEGO SUPERCOMPUTER CENTER Water Web Catalog Services

67 SAN DIEGO SUPERCOMPUTER CENTER Water Web Service Capability Describes Services Water Web Data Services Water Web Catalog Service Water Quality Exchange Service Water Web Ontology Service Map Services

68 SAN DIEGO SUPERCOMPUTER CENTER Water Web Data Service Harvest (List) Single object access (Describe) Basic query (Get) Objects Services Domains Series Sites Variables Data Values Pointer to Map Service (optional)

69 SAN DIEGO SUPERCOMPUTER CENTER Water Quality Exchange Standardized access to Water Quality Exchange Services Utilize WQX standard for the details of analytical chemistry observations Organizations Projects Activities –Methods »Results

70 SAN DIEGO SUPERCOMPUTER CENTER Water Web Catalog Services Search interface, not a harvest interface Utilize same queries to retrieve “objects” Return reference to map services for appropriate object queries (features and series) Objects Services Domains Series Features Variables Provide Map Services for services

71 SAN DIEGO SUPERCOMPUTER CENTER Catalog Query Parameters Paging: count, startindex Location: box, siteCode, polygon Variables: VariableCode Ontology: conceptCode Series: SeriesCode Time: BeginTIme, EndTime Updated: lastmodified DataService: DataService DataType: DataType Theme: Theme Code, Theme Name Search by name: SearchTerms

72 SAN DIEGO SUPERCOMPUTER CENTER Queries Variable For box, pass a bbox For a set of sites or series, pass multiple site or series codes Series For box, pass a bbox For a set of a concept, pass a concept code from the ontology Services For box, pass a bbox For a set of a concept, pass a concept code from the ontology

73 SAN DIEGO SUPERCOMPUTER CENTER Water Web Ontology Services Handle Multiple Ontologies List Terms for an ontology (domains) Provide hierarchies/relationships for an ontology (conceptTree). Provide method for user interfaces Provide method to assist with matching variable name to concept(s)

74 SAN DIEGO SUPERCOMPUTER CENTER Map Services Data Services should provide a Web Map Service to plot their location on a map. Well known features need to provide Web Map Service, and Web Feature Services. Examples of this would be HUC’s, and state and county boundaries.

75 SAN DIEGO SUPERCOMPUTER CENTER Authentication and Authorization Use standards OpenId for Authentication We don’t store passwords, in general Oauth for Authorization Servers needing restricted data provide authorization service Level is up to server. Auth service should only know about Object Identifiers Clients When access is rejected, clients need to know how to authenticate to an authorization service Pass authorization

76 SAN DIEGO SUPERCOMPUTER CENTER Message WaterML is the message The Language is GML It’s like English. We communicate in English, but there are technical dialects Difference in the present process: HIS started with the services, the defined a message We still need to talk about services. Add dan to the title

77 SAN DIEGO SUPERCOMPUTER CENTER Connecting a Catalog with Users and Servers Server User Catalog Data Services HydroServerHydroDesktop HIS Central Data Services WISKI ArcGIS Desktop HIS Central Data Services A general pattern …. is implemented in different ways ….

78 SAN DIEGO SUPERCOMPUTER CENTER Mapping the Catalogs Server User Catalog Server User Catalog Server User Catalog Server User Catalog Server User Catalog Data Services Water observation sites in a catalog are mapped ….. ….. a map in ArcGIS Online serves as an integrating mechanism for water observations over the earth Mapping Services


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