Geog 463 GIS Workshop

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Geog 463GIS Workshop

• April 17 2006

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Outlines

• Data Acquisition
• Acquiring spatial data
• Metadata
• Spatial data quality
• Determining fitness-for-use of data
• Spatial Data Infrastructure (SDI)
• Concepts of SDI
• What constitute SDI
• How can SDI be characterized

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• Part I. Data Acquisition

Evaluating the applicability of data is one of
essential skills for GIS professionals
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Acquiring spatial data

• Use data download service
• USGS National Map Seamless Data Distribution
  System http//seamless.usgs.gov
• USGS EROS Data Center http//edcwww.cr.usgs.gov/
• Microsofts Terraserver http//terraserver.microso
  ft.com/
• TIGER/Line by Census Bureau or ESRI
• http//www.census.gov/geo/www/tiger/tiger2002/tgr2
  002.html
• http//www.esri.com/data/download/census2000_tiger
  line/index.html
• Subnational GIS clearing house (e.g. WAGDA)
• Use data catalogue service (or spatial portal)
• Geospatial one-stop http//www.geodata.gov
• ESRI geographynetwork.com http//www.geographynetw
  ork.com/

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Tips for spatial non-spatial data acquisition

• By geographic scale
• Data resolution is often related to the
  geographic scale of data providing agency being
  considered
• federal data sources have lower resolution with
  wider geographic coverage (e.g. LU/LC in EROS
  Data Center)
• parcel data can be found in the local level (e.g.
  City of Seattle)
• By related agency and organizations
• Best data about housing can be found in HUD
• Best data about transportation can be found in
  BTS
• Best data about education can be found in NCES
• Best data about justice can be found in BJS
• By theme
• Talk to resource persons in the area they
  probably have go through data search processes

Also read http//courses.washington.edu/geog360a/d
ataatlibs2003.ppt if youre not familiar with UW
library system
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Metadata

• Describes content and characteristics of data
• Helps determine fitness for use
• Is the data suitable for the application
• Is metadata always available
• No (much shared data is more likely to be
  published with metadata e.g. USGS public domain
  data)
• What if metadata is not available
• Look for data dictionary at least or contact
  persons in charge
• Metadata standard for public data in the U.S.
• FGDC metadata content standard (www.fgdc.gov)

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Reading FGDC metadata
Never miss reading abstract and purpose!
Example http//wa-node.gis.washington.edu/uwlib/
10mdem.html
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Creating metadata

• How do I create metadata
• Use metadata creation/editing tool
• ArcCatalog from ESRI
• tkme from
• http//geology.usgs.gov/tools/metadata/tools/doc/
  tkme.html
• How do I check if this metadata conforms to FGDG
  Content Standard
• Use metadata validation tool
• Install program mp from http//geology.usgs.gov/to
  ols/metadata/tools/doc/mp.html
• Use web service at http//geo-nsdi.er.usgs.gov/val
  idate.php

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Spatial data quality
 

• where
• Column components of geographic information
• Row components of data quality 
• Accuracy lack of discrepancy between measurement
  and values considered true (e.g. is this location
  near true value)
• Consistency whether given components conform to
  logical rules (e.g. any digitizing error)
• Completeness whether whats required is encoded
  in data (i.e. anything missing)

How is spatial data quality related to fitness
for use of data
FGDC metadata terms
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Determining fitness for use

• Does map scale or resolution of the data provide
  the level of details required by the application
  
• Using low-resolution satellite image for
  street-level survey is not acceptable
• Any generalization algorithms used
• Is data current enough to support needs
  identified from P1
• Using outdated data for replacing a old map is
  not acceptable
• Are specific characteristics of data useful for
  the application
• Topology for routing operation
• Multispectral image for land use detection
• Non-planar representation for 3D visualization
• Any processing steps linked to usefulness of data
  for specific applications
• Some processing steps brought about irreversible
  effects on data (e.g. unknown algorithm
  parameters)

Questions shown in this lecture note are not
intended to be exhaustive
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Determining fitness for use

• Is the stated level of accuracy sufficient given
  error tolerance
• Requirements for accuracy vary highly by the
  applications
• Required types of accuracy vary by need-to-know
  questions or research questions (e.g. measuring
  parcel size require relative accuracy while
  surveying require absolute accuracy)
• Is the state level of completeness of features or
  attribute adequate to need-to-know question
• Some entities and attributes are required rather
  than optional
• Logical consistency of data
• Doesnt data lack conformance to logical rules
  (e.g. is identifier generated properly Doesnt
  data has too many sliver)
• Does metadata indicate that the agency put any
  effort in quality control (e.g. lack of
  information in data quality section)

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• Part II. Spatial Data Infrastructure

Searching for the day we take less pain in data
acquisition
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• Imagine the future when information is extracted
  from data upon request (maybe future is now)
• In the future data is right there and different
  data are integrated in a seamless manner so that
  value-added products can be generated in a timely
  fashion
• What are barriers to getting there Are we
  getting there What are steps towards making the
  best use of spatial data

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Role of geographic information

• Statistics shows that 80 of government-related
  activities require locational information
• Business demand exist to analyze customers need
  on a locational basis
• There are overriding concerns for understanding
  the complexity of human and natural environment
  and its interaction
• Locational framework can act as a glue that puts
  together related themes
• Sustainability can be understood by examining
  relationships of all related themes not by
  examining one theme separate from other themes
• Sustainability has been widely acknowledged as a
  future agenda in varying organizational structure

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Spatial data as commodity

• Thus spatial data is being seen as assets
  promoting good governance economic development
  and improved environmental sustainability as we
  observe increasing attention to holistic
  approaches
• Also seen as push towards information society
• In addition many sustainability concerns cannot
  be addressed without cutting across multiple
  jurisdictions
• Access to applicable spatial data is essential to
  this endeavor
• Spatial data infrastructure that provides
  enabling environment for a spatially enabled
  society

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Spatial data integration
Thematic integration
Geographic integration
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SDI Reinventing the meaning of GIS

• The larger the scope of GIS project is the more
  base data is shared thus generating more benefit
• What about national or global effort to sharing
  spatial data (e.g. NSDI Global Map)
• Spatial data as an infrastructure
• Airplane doesnt fly but airline does
• Highway only doesnt take you there but all
  related technical and institutional arrangements
  do
• Spatial data only doesnt meet your need but
  multiple aspects related to creation
  maintenance extraction and dissemination of
  spatial data do

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What constitute SDI

• What is needed to facilitate data sharing Or
  what are barriers to facilitating data sharing as
  a counter example
• What if theres no metadata that describes data
• What if theres no people who know
  characteristics and constraints attached to
  spatial data
• What if theres no website for data
  dissemination
• What if theres no standards that promote
  interoperability (e.g. FGDC metadata content
  standard)
• What if theres no coordination between agency
• What if theres no willingness to share data
• SDI spatial data people technology
  standards policy

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How can SDI be characterized

• SDIs are shared
• as they seek to make available expensive
  geo-referenced spatial data digitally to a
  variety of users for diverse application needs
  (for example biodiversity utilities and
  health) based on an integrated approach.
• SDIs are open
• as no pre-defined boundaries limiting the user
  groups are made and typically various government
  departments citizens and private sector are
  expected to draw upon them.
• SDIs are inherently enabling
• as they are not pre-configured to a particular
  application and can potentially be used by
  different entities to design their own
  applications.

Groot and McLaughlin 2000