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GeoSpatial Systems – Metaknowledge Mashup. Dan Rickman GeoSpatial SG. Agenda. What are GIS What is GeoSpatial Data Data management issues Neo-Geography Standards Current and future developments. What are GeoSpatial Systems?.

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agenda
Agenda
  • What are GIS
  • What is GeoSpatial Data
  • Data management issues
  • Neo-Geography
  • Standards
  • Current and future developments
slide3

What are GeoSpatial Systems?

  • Known as Geographic Information Systems, Spatial Information Systems
  • Enables capture, modelling, storage, retrieval, sharing, manipulation and analysis of geographically referenced data
  • Not CAD! Database is at the heart – as is “attribute” data
  • Model developing – perhaps GeoSpatial data better seen as “attribute” of alphanumeric business information
  • Presentation does not have to be map-based in all cases
  • Key element is spatial indexing – uses different techniques to alphanumeric indexing
what is geospatial information 1
What is Geospatial Information? - 1
  • Spatial data which relates to the surface of the Earth
  • Geodetic reference system as base e.g. WGS84 used for Global Positioning System (Earth as an ellipsoid), Latitude and Longitude (Earth as a sphere)
  • Ordnance Survey (GB) define National Grid – projection onto flat surface – NB: OS(NI) use Irish grid
  • Spatial relationships – defined around concept of neighbourhood – relates to two “laws” of geography:
      • Most things influence most other things in some way
      • Nearby things are usually more similar than things which are far apart
what is geospatial information 2
What is Geospatial Information? - 2
  • Unstructured – spaghetti data
  • Topology – information structured as networks, polygons
  • GeoSpatial information requires metadata – e.g. minimal information such as map projection used
  • GeoSpatial information may also temporal modelling – e.g. farm subsidies vary as utilisation and legislation change
  • Field-based model versus object-based model of space, e.g. rainfall versus buildings on which rain falls
  • GeoSpatial information requires ontology
    • What is the “real world”, how classified
  • Relates to semantics
where used examples
Where used? Examples
  • Central government – DEFRA, ODPM, Land Registry, ONS
  • Local government – planning, highways authorities
  • Utilities – physical and logical network
  • Insurance – flood plains
  • Health – epidemiology
  • Travel, multi-modal route planning
  • More widespread use – addresses, postcode based data against regional boundaries, infrastructure (“geographies” used to divide country, catchment area)
  • Fiat boundaries verus “bona fide” boundaries – what is “real world” how do we structure it?
structured geo database paradigm shift
Structured geo-databaseParadigm shift?

Relational

Database

(Attribute data)

Spatial

Data

(proprietary format)

Real

Time/Engineering

Systems

CRM

ERP

  • Spatially extended RDBMS
  • Complex data types for spatial data
  • Computational geometry
  • Spatial indexing
  • DDL and DML extensions
networks and topology
Networks and Topology
  • Routing
  • Connectivity
  • Explicit spatial relationships
  • Can be complex - one way,
  • - restricted turn
  • - average speed
terrain and 3d
Terrain and 3D
  • Line of sight
  • Radio Propagation
  • Flood
  • Water Pressure
temporal
Temporal

Time as a dimension

or measure

How things change

over time

geospatial data modelling
Geospatial data modelling
  • Field-based model versus object-based model
  • Geographic Information Systems are object-based in practice
  • Most common field based information, e.g. Digital Elevation Model (line of sight applications), attached to objects
  • Objects rely on field-based model, i.e. spatial co-ordinates
  • Initiatives such as Digital National Framework encourage organisations to structure data on references to objects, not re-capture and duplicate data
  • GeoSpatial equivalent of “referential integrity”
  • Nevertheless duplication, lack of (referential) integrity is common place and hard to eradicate
digital national framework
Digital National Framework
  • Capture information once and use many times
  • Benefits:
    • avoid cost of duplicate data capture
    • benefit through 3rd party data maintenance (i.e. avoid cost of maintaining one's own data)
    • benefit of improved data management especially where COU is used to identify area of change (which can then be used to focus and improve maintenance of non-spatial business object data, as appropriate)
  • Capture at the highest resolution possible
  • Benefit:
    • avoid re-capture later on
    • improve potential for data interoperability
  • Publish lower resolutions from this data - if required
    • avoids data recapture
  • Use existing proven standards
    • provides framework, avoids costs of "re-inventing the wheel" NB: sort of benefit one would expect from a strategy!
in search of the blpu
In search of the BLPU
  • Basic Land and Property Unit
  • “Holy grail” of industry – no Da Vinci code produced yet!
  • Example of Ordnance Survey Master Map (OSMM):
  • "St Mary's football stadium, Southampton" is one object
  • Typical detached house and its plot of land, likewise
  • Complex entities such as "Southampton railway station" are defined in terms multiple objects: one for the main building, several for the platforms, one more for pedestrian bridge over the tracks. (NB: See Wikipedia article on TOID)
  • Defining the candidate BLPU, their lifecycles and their attribute data and verifying that these are meaningful/practicable from the wide variety of business processes which apply to the BLPU and the aggregate entities which are created from them
  • Dependencies so that data sets are based on the BLPU wherever possible limited by business use, e.g. field use change quite different from a tenant/owner perspective
slide15

database

records

digital

records

geographic

information

paper

records

digital mapping

paper mapping

1990

1970

Evolution of geographic information

2010

1950

raster map data
Raster map data
  • Scanned ortho-rectified map or map-based data – metadata is co-ordinates, projection, extent
  • For example Google Maps/Google Earth, Microsoft Virtual Earth
  • Traditionally stored outside the database as external files, analogous to vector data storage, e.g. Oracle 10g GeoRaster
  • Data stored as BLOBs, metadata required regarding number of bytes per pixel, compression algorithms and so on
  • Benefits limited as “intelligence” in map requires interpretation
  • Still limited progress on map-based pattern recognition – there are semi-automated solutions from companies such as Laser-Scan
benefits of integration
Benefits of integration
  • Geo-spatial data mining
    • Spatial links
    • Shipman example
  • Visualisation
  • Provide new ways of linking data
    • Avoid capturing data e.g. DNF
    • Maintenance of data
  • Lower costs of integration and delivery at front-end
  • Back-end integration still an issue – data
  • Reduce endless data cleaning – as part of information management strategy
  • Reduce data maintenance costs
  • Improve data in business – does this matter?
geospatial drivers
Geospatial - Drivers
  • Awareness
  • Current use of data
  • Front end integration – Mashups
  • Back end – Database
  • Data providers
    • Ordnance Survey
    • Developing middle/large scale market
    • Open source data
    • Free our data
slide19
EDRM
  • Electronic document and records management
  • Increase usage in local/central government due to Freedom of Information act
  • Contain potentially significant geospatial data
  • Most common example is address
  • Requires capture of appropriate metadata or appropriate pattern recognition to identify addresses
  • Requires gazetteers to provide reference to spatial co-ordinates
  • NB: most familiar gazetteer – list of streets in AtoZ maps
costs
Costs
  • Hardware – no special hardware required
  • Network – bandwidth generally adequate
  • Software – Increasingly delivered through “thin” clients
  • SOA – promise of mashups (WMS/WFS, Google, Yahoo, Microsoft), GeoRSS
  • Development skills – limited specialist skills required
  • Data
    • Still expensive
    • Complex
    • Requires re-engineering/data management
    • “Boring” issue – drivers often hidden in BAU
standards
Standards
  • GeoSpatial widely used – in database technology, web-based systems and developing IS architecture.
  • Organisations already exist -BCS must be relevant
      • Open GeoSpatial Consortium - http://www.opengeospatial.org/
      • ISO TC211 (GI/Geomatics) - http://www.isotc211.org/
      • BSI Committee for GI (http://www.gistandards.org.uk/)
      • Association for Geographic Information (http://www.agi.org.uk)
  • A topic for parliamentarians (EU e.g. INSPIRE http://inspire.jrc.it/ & Westminster e.g. GI Panel http://www.gipanel.org.uk/gipanel/ Already an issue for business – significant investment
  • Needs to be a credible BCS specialist group
  • Provide voice for BCS in GeoSpatial issues
  • Public policy - Free our data?
gsg why
Benefits for BCS

Embracing part of cultural change within IS/IT/IM

Microsoft, Google and Oracle significant investment and developments

Prominence in “Web 2.0” sites, e.g. www.platial.com (“Collaborative atlas”)

Enabling technologies/architecture such as SOA

Seen as being relevant

BCS recovering lost ground

GIS SG previously existed

No vendor tie in – no conflict of interest

BCS recruitment mechanism for potential BCS members

GSG: WHY
gsg why1
GSG: WHY
  • How we address GeoSpatial issues?
    • Vendor, academic, end user/ business experience
    • Survey and consensus of Group Members
  • How do we convey this message ?
    • Meetings minimum once a quarter, but ideally every 6 weeks.
    • A positive effort to hold meetings in the nations & regions.
    • Contribution to discussions, events (representation).
    • Web site communication
    • Email bulletins
    • Press
summary
Summary
  • Geospatial now becoming mainstream
  • Significant developments in market, e.g. Pitney Bowes purchase of MapInfo, increasing demand for linking BI with GIS
  • Neo-Geography and wider awareness drive use of geospatial data
  • However data availability and quality are key issues, implications of this not always well understood
  • Metadata and catalogue standards exist not always integrated with wider standards and not always well implemented or implemented at all …