Midterm next Wednesday
Midterm• May start off with multiple choice
• Bulk will be short answer/short essay
• Lecture PPTs and your notes, readings in Longley et al., Zeiler
• Will not include – Labs or Arc Marine exercise
– Journal articles
Major concepts
• Representations• Object vs Field• Model, data model, analysis model• Data models
– UML terminology, basic procedure from• Reality --> conceptual --> logical --> physical
– Customized Arc GIS data models• For enterprise GIS
• Analysis Models– Binary, ranking, rating, weighted rating
Major concepts - cont.
Concepts of Data SharingLongley et al., Chapter 11
NSDI ---> data.gov
• Who needs to share data? – jurisdictions with common borders
– jurisdictions in a region
– private and public sectors
– local, state, and Federal agencies
– government and individuals
NSDI ---> data.gov• State, local, private production of
geospatial data – loss of Federal monopoly, patchwork
– variable accuracy, level of detail
– the WWW
– everyone can be a producer, publisher, distributor of geospatial data
• See GEO 465/565 lecture #6– dusk.geo.orst.edu/gis/lec06.html#nsdi
Barriers to Data Sharing(1) interoperability
– will ArcGIS read Intergraph data?
– find a common format that both can read • output into the common format • input the common format
– is the common format the same as one of the GIS formats?
• if yes, only one conversion is needed • if no, two conversions are needed
– issues of format, syntax within ONE GIS
• Digital Line Graphs (DLGs)–vector topographic maps
–1:24,000, 1:100,000 ,1:10,000
Govt Agency Data Formats
• Digital Raster Graphics (DRGs)– raster topographic maps at
1:24,000
• Digital Elevation Models (DEMs)– raster elevation data
– 90m, 30m, 10m
– Oregon 10m DEMs from buccaneer.geo.orst.edu/dem
• Digital Orthophoto Quads (DOQs or DOQQs)– aerial photographs
– camera orientation, terrain info.
– raster images at 1m resolution
– 6m positional accuracy at scale of 1:12000
• Imagery– satellites
– Landsat, SPOT, SPIN, etc.
Govt Agency Data Formats
National Data Sharing (cont.)
• new high resolution commercial imagery • 1 m resolution• www.spaceimaging.com
Barriers to Data Sharing(2) how to describe what you need
– how to assess whether some data set fits the need?
Describing Data
• Metadata• Again, see GEO 465/565 lecture #6
– dusk.geo.orst.edu/gis/lec06.html#nsdi
• ArcCatalog– graphic thumbnail
– Tables
– FGDC format metadata
– ESRI format metadata
– XML format metadata
Issues with metadata?
• potential complexity– can be larger than the data set!
• investment to create– can be larger than the data set!
• carrots and sticks – FGDC’s "don't duck metadata"
Barriers to Data Sharing
(3) retrieval - large spatial data sets(4) national security - e.g., impact of 9/11(5) search engines
– how to know where to look on the WWW?– SAPs know where to look (more on this soon)
• National clearinghouse, www.data.gov• Regional and campus clearinghouses• www.geo.oregonstate.edu/ucgis/datasoft.html• Google
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