GeoSpatial Unstructured Data

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GeoSpatial Unstructured Data

• Dan Rickman
• GeoSpatial SG

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Agenda

• What is geospatial data
• What does structured geospatial data look like?
• General data modelling issues regarding
  geospatial data
• In search of the BLPU
• A brief history of OS maps how structured are
  they (then and now)
• Raster map data
• EDRM
• Geo-parsers/gazetteers/metadata
• Web-based systems
• Future directions?

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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

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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

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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
• 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

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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?

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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

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GIS
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ROMANSE - Hampshire CC
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(No Transcript)
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Roadwork Information
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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

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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

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Evolution of geographic information
1950
2010
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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

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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

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Geo-parsers/gazetteers/metadata

• Geo-parsers identify spatial tags (geo-tags) in
  data
• Context sensitivity and patterns of usage
  required
• E.g. Jordan (country) ! Jordan (Katie Price)
• Can see an example at
• http//edina.ac.uk/projects/geoxwalk/geoparser.htm
  l
• Relies on and populates gazetteer of associated
  names
• Emerging standards for geo-parsing, e.g. Open GIS
  Consortium looking at
• Gazetteer service
• Geo-coder service
• Web services (WMS/WFS)

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Web-based systemsGoogle Earth meets Flickr

• Web-based systems (metacarta, KML, mashup)

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Web-based systems

• World wide wild west of unstructured data
• Increasing use of systems to control, coordinate
  and make this accessible
• Geo-enabled semantic web raises issues of
  ontology
• www.metacarta.com provide web-based Geographic
  Text Search (GTS), has the ability to confine
  searches by geography and retrieve information
  that it detects using the keywords, and then
  displays this information geographically on a map
  interface (working now with Google Earth).

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They know where you live

• MetaCarta(R), Inc., a leading provider of
  geographic intelligence, announced today that it
  had won a one-year contract with the Department
  of Homeland Security which identifies and
  assesses current and future threats to the
  homeland, maps those threats against the nation's
  vulnerabilities, issues timely warnings and takes
  preventative and protective action The product
  automatically identifies geographic references
  using advanced natural language processing (NLP)
  from any type of unstructured content in a
  customer's archives such as email, web pages,
  newswires or cables. It assigns a latitude and
  longitude to these references so that users can
  analyze their text archives using geographic
  maps, keywords and time as filters. The results
  of a query are displayed on a map with icons
  representing the locations found in the natural
  language text of the documents and as a text
  results list. Both the icons and text summaries
  are hyperlinked to the documents they represent.
• (Source http//www.prnewswire.com/cgi-bin/stories
  .pl?ACCT109STORY/www/story/03-14-2005/000319390
  9EDATE)

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The future (and summary)

• Structured environment will contain more
  unstructured data
• Web will continue to provide unstructured
  distributed data
• Success of semantic-based approach yet to be
  determined, experience with geospatial data
  indicates there are significant complexities
  based around our representations of the real
  world
• One issue is clear increasingly less privacy,
  location is already accessible through mobile
  phones and linking this to other data can provide
  significant intelligence information
• Also clear data quality issues will persist
• They will still get it wrong!