Transcript
Page 1: Lectures 6 and 7 Spatial Data Infrastructures

Lectures 6 and 7Spatial Data InfrastructuresPartnerships in Action

Longley et al. Chapter 20

Page 2: Lectures 6 and 7 Spatial Data Infrastructures

PartnershipsOften fraught with hazards – can take longer and create friction

BUTOften there is no real choice for they can bring:

New staff skillsAdditional technologyMarketing skillsBetter brand imageNew insights on user needsNew productsCost- and risk-sharing

Page 3: Lectures 6 and 7 Spatial Data Infrastructures

Local partnerships: an example

Channel Island National Marine Sanctuary

NOAA NMS

SB County Planning & Develop

Island Packers

Blue Planet

Commercial Fisherman of SB, Inc

Ventura College

UCSB

Channel Islands National Park

Calif Coastal Commission

Many, many others …

Page 4: Lectures 6 and 7 Spatial Data Infrastructures

Local to global partnerships: an exampleGIS Day is an annual grassroots event which began in November 1999, designed to promote geographic literacy in schools, communities, and organizations. GIS Day GIS users and vendors open their doors to schools, businesses, and the general public to showcase real-world applications of the technology.

News of the event is spread by use of the Internet and by advertising. Any organization can host such an event: 2,400+ organizations hosted GIS Day events in more than 91 different countries in 1999 (see map). About 2.4 million children and adults were enlightened on GIS technology on that day

Page 5: Lectures 6 and 7 Spatial Data Infrastructures

www.gisday.com

Page 6: Lectures 6 and 7 Spatial Data Infrastructures

National partnerships via NSDIsThe problem:

Data duplication commonplace – so waste occursAd hoc data sharing has many difficultiesData often tailored to one applicationBest data often collected in greatest detail at local level but not accessible to regional or national folkIndexes/metadata to available GI unknown until recentlyNo general protocols for any of this until NSDI…

Page 7: Lectures 6 and 7 Spatial Data Infrastructures

What is a National Spatial Data Infrastructure?

‘the technology, policies, standards, and human resources necessary to acquire, process, store, distribute, and improve utilization of geospatial data’

Source: Presidential Executive Order #12906 (1994): 'Co-ordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure' W Clinton.

BUT what does it mean in practice?

Page 8: Lectures 6 and 7 Spatial Data Infrastructures

Initial elements of the US NSDIDefined standards (mandated on federal agencies and encouraged for others) Minimizing inconsistencyClearinghouse – metadata descriptions of existing data. Advertising what is availableNational geospatial data framework - a common ‘template’ on which to assemble other data

Page 9: Lectures 6 and 7 Spatial Data Infrastructures

The NSDI is composed ofThe NSDI is composed of

MetadataMetadata

Geo dataGeo data

ClearinghouseClearinghouse

StandardsStandards

Partnerships

Page 10: Lectures 6 and 7 Spatial Data Infrastructures

The data provide a core...The data provide a core...

Geographic/Geospatial DataGeographic/Geospatial Data

Page 11: Lectures 6 and 7 Spatial Data Infrastructures

Categories of Geographic DataCategories of Geographic DataCommunity-developed data sets single purpose potential re-usecommon content specification “Framework” data

Page 12: Lectures 6 and 7 Spatial Data Infrastructures

SpecializedSpecializedFrameworkFramework

Categories of Geographic DataCategories of Geographic Data

Page 13: Lectures 6 and 7 Spatial Data Infrastructures

Digital orthoimagery

Elevation and bathymetry

BoundariesRailroadsGeodetic

FederalState

LocalPrivate

Utilities

Spatial Analysis Base for Other Data Finished Maps

RoadsCadastral

Hydrography

Framework DataFramework Data

Spatial Analysis Base for Other Data Finished Maps

Page 14: Lectures 6 and 7 Spatial Data Infrastructures

Web Sites of the WeekWeb Sites of the Week

Page 15: Lectures 6 and 7 Spatial Data Infrastructures

SpecializedSpecializedFrameworkFramework

MetadataMetadata

Describing your data...Describing your data...

Page 16: Lectures 6 and 7 Spatial Data Infrastructures

Metadata: “nutritional” label for Metadata: “nutritional” label for GIS data setsGIS data sets

Internally - saves 4 hrs research 10 times a year = (4x10x$50) = $2,000 (time it takes to look up or contact someone for information about a dataset)External Questions - refer 30 inquires/year (1hr/inquiry) = (30x1x $50)=$1,500 (time it takes to answer calls from people who want to use the data or find out more about it) Future reuse/enhancement -$5,000 to $25,000Liability (lawyers, courts) - $$$$

Page 17: Lectures 6 and 7 Spatial Data Infrastructures

The uses of metadataThe uses of metadata Provides documentation of existing

internal geospatial data resources within an organization (inventory)

Permits structured search and comparison of held spatial data by others (advertising)

Provides end-users with adequate information to take the data and use it in an appropriate context (liability)

Page 18: Lectures 6 and 7 Spatial Data Infrastructures

SpecializedSpecializedFrameworkFramework

MetadataMetadata

Making data discoverable...

Clearinghouse (catalog)Clearinghouse (catalog)

Page 19: Lectures 6 and 7 Spatial Data Infrastructures

Clearinghouse provides...Clearinghouse provides... Discovery of spatial data Distributed search worldwide Uniform interface for spatial data

searches Advertising for your data holdings

Page 20: Lectures 6 and 7 Spatial Data Infrastructures

Clearinghouse operates as...Clearinghouse operates as... Entry point to constellation of

servers Collection of distributed servers,

using a common protocol (e.g., Z39.50)

A virtual “Google” for geographic data

Page 21: Lectures 6 and 7 Spatial Data Infrastructures

WebWebClientClient

Gateway

ClearinghouseClearinghouse““Nodes” orNodes” or

ServersServers

This is all “Clearinghouse”This is all “Clearinghouse”

NOAANOAA

OregonOregonUSGSUSGSNMDNMD

NGSNGS

Page 22: Lectures 6 and 7 Spatial Data Infrastructures

SpecializedSpecializedFrameworkFramework

MetadataMetadata

Clearinghouse (catalog)Clearinghouse (catalog)

StandardsStandards

Consistent approaches...

Page 23: Lectures 6 and 7 Spatial Data Infrastructures

Who builds standards?Who builds standards? ISO - Intl Standards Organization FGDC Standards working group in

partnership with . . . FGDC Thematic subcommittees

Open Geospatial Consortium (OGC) Concerned organizations Producers and users of geospatial

data

Page 24: Lectures 6 and 7 Spatial Data Infrastructures

Types of standardsTypes of standards Data content

—Common classifications—Common collection criteria

Data managementMetadataSpatial Data Transfer Standard (SDTS)

Data transfer protocols (e.g., WMS)

Page 25: Lectures 6 and 7 Spatial Data Infrastructures

Clearinghouse/Catalog & StandardsClearinghouse/Catalog & StandardsImportant differences:

Data models, data structures (formats), query languages, (syntactic) meaning of terms in metadata, meaning of values in data (semantic)

E.g.: Metadata:

– Different metadata standards (ISO vs. FGDC)– Different terms: ‘Seabed’ vs. ‘Seafloor’

‘Coastline’ vs. ‘Shoreline’

Page 26: Lectures 6 and 7 Spatial Data Infrastructures

Open Geospatial Consortium (OGC)Open Geospatial Consortium (OGC)OGC Web Service:

OGC specificationInterface allowing requests for geographic “resources” across the Web using platform-independent callsMain OGC services:• Catalogue Service for the Web (CSW)• Web Map Service (WMS) • Web Feature Service (WFS)• Web Coverage Service (WCS)

Page 27: Lectures 6 and 7 Spatial Data Infrastructures

Catalog Services for the Web (CSW) ExampleCatalog Services for the Web (CSW) ExampleInternational Coastal Atlas Network (ICAN)Connect individual coastal atlases to an integrated global atlas

Global atlas

Local atlases

Page 28: Lectures 6 and 7 Spatial Data Infrastructures

Catalog Services for the Web (CSW) ExampleCatalog Services for the Web (CSW) ExampleICAN CSW based on open source GeoNetworkGeonetwork-opensource.org

Atlas X

ISO Metadata&

MIDA terminology

FGDC Metadata&

OCA terminology

X Standard&

X terminology

“Seabed” “Seafloor”

Page 29: Lectures 6 and 7 Spatial Data Infrastructures

Next step for ICAN is WMSNext step for ICAN is WMS

CSW

X

WMS WFS WFS WFS

CSW CSWWMS WMS

Linking of terms in metadata helps ultimate to link to data:

ICAN:Coastline

is similar to

OCA:Shoreline

Page 30: Lectures 6 and 7 Spatial Data Infrastructures

Web Mapping Service (WMS) ExampleWeb Mapping Service (WMS) ExampleDISMAR: Data Integration System for Marine Pollution and Water Quality. More current projects at http://interrisk.nersc.no/

Page 31: Lectures 6 and 7 Spatial Data Infrastructures

International Coastal Atlas Networkican.science.oregonstate.edu

Page 32: Lectures 6 and 7 Spatial Data Infrastructures

Partnerships

GEOdataGEOdataFrameworkFramework

MetadataMetadata

Clearinghouse (catalog)Clearinghouse (catalog)

StandardsStandards

Page 33: Lectures 6 and 7 Spatial Data Infrastructures

Lots of people involved…Federal government (many agencies)State governmentLocal governmentPrivate sector – contractors, value-adders, exploitersNot for profit organizationsCitizenryOthers…

No one is in charge…

Page 34: Lectures 6 and 7 Spatial Data Infrastructures

Data.gov

Page 35: Lectures 6 and 7 Spatial Data Infrastructures

Mapaction.org

Page 36: Lectures 6 and 7 Spatial Data Infrastructures

Government and the private sectorNational governments own and control national mapping agenciesAll such mapping produced to national specifications until recentlyNew private sector providers:

Produce imagery for anywhere in worldProduce road databases

How do we get these to work together?

Page 37: Lectures 6 and 7 Spatial Data Infrastructures

A Research AgendaFuture of the Spatial Information Infrastructure

Information policy• Intellectual property rights, privacy, liability

Digital government researchLocal generation and integration of data• Public participation GIS

Page 38: Lectures 6 and 7 Spatial Data Infrastructures

Short Term Research Prioritieswww.ucgis.org priorities-->research

Institutional aspects of SDIsGI PartneringGI Resource MgmtGradation, Indeterminate BoundariesGeospatial Semantic WebSpatializationPervasive Computing

Location Based ServicesSpatial ClusteringGeoslavery & SecurityGeospatial Data FusionGlobal Representation and ModelingData Mining and Knowledge DiscoveryDynamic Modeling

Page 39: Lectures 6 and 7 Spatial Data Infrastructures

Other Research Priorities(Long Term)

Geographic RepresentationScaleSpatial Data Acquisition & IntegrationSpatial CognitionSpatial Ontologies

Space and Space/Time Analysis & ModelingUncertaintyVisualizationGIS and SocietyGeographic Information Engineering

Page 40: Lectures 6 and 7 Spatial Data Infrastructures

A Global Spatial Data Infrastructure?

Difficult enough to get national players to work together…Is GSDI a process, a general framework or a product?Who are the stakeholders?Who needs it? (military doing what they need themselves?)

Page 41: Lectures 6 and 7 Spatial Data Infrastructures
Page 42: Lectures 6 and 7 Spatial Data Infrastructures

Life, partnerships and GISWhen do you work in partnership with other people or organisations?

What makes it worthwhile?The same applies to GIS partnerships:

Commitment to a cause, wish to improve matters?Personal ambition? Influence? Fame? Status?Money?

Page 43: Lectures 6 and 7 Spatial Data Infrastructures

Summary - 1Partnerships versus competition

LocalNational Spatial Data Infrastructure

• Geodata, Framework, Metadata, Clearinghouse, Standards, Partnerships

Global Spatial Data InfrastructuresPolitical power in partnershipsBringing it all together: the GIS game

Page 44: Lectures 6 and 7 Spatial Data Infrastructures

Summary - 2Partnerships potentially very powerful so look beyond the normal..Nothing is without cost…Choose GIS partners carefully, nurture relationships…


Recommended