Lecture to UCSB GIS class, February 19, 2009, by Alan Glennon. Overview of recent, interesting maps, introduction to spatial data, online mapping, considerations, and best practices.
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Spatial Information and the Internet
1. SPATIAL INFORMATION and the
Alan Glennon
INTERNET spatial.ucsb.edu
University of California, Santa Barbara
19 February 2009
Image Source: GeoEye.com 2009
2. Mission:
To facilitate the integration of spatial thinking into processes for
learning and discovery in the natural, social, and behavioral
sciences, to promote excellence in engineering and applied
sciences, and to enhance creativity in the arts and humanities.
University of California, Santa Barbara
Engagement:
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Hosting events (brownbags, workshops, lectures)
Developing spatial analytic tools
Offering a help desk
Assisting with research proposal development
Image Source: NAIP, 2005
6. Grassroots mapping of Gaza
(Gaza project spearheaded by Mikel Maron. left: December 2008 data; right: February 2009 data)
University of California, Santa Barbara
19 February 2009
Source: openstreetmap.org, 2009
9. SPATIAL INFORMATION and the
INTERNET
• Three significant maps of the last
twelve months
• Considering spatial data
• Web 2.0
• Comparing the language of
University of California, Santa Barbara
Topics cartography, GIS, and Internet
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geography
• Capabilities and concerns
• Policy and best practices
• Future
Image Source: GeoEye.com 2008
10. Geographic Data
Two practical perspectives:
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Data that include or can be harvested for spatial
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references
Combinations of spatially-referenced points, polylines,
polygons, and images with their associated attributes
and relationships
Image Source: Google.com 2008
11. Image Source: Google.com 2008
Geographic Data
University of California, Santa Barbara
19 February 2009
12. Geographic Data
Significance:
visually compelling
provide context and content; close things are
usually more related; spatial order; pattern and trend
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recognition
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popular; widespread use, particularly on the Internet
professional expectation: Google Maps as a baseline
13. “…it would behove spatial scientists to articulate to
the broader research community the potential of
recording and making accessible spatial data in the
appropriate formats — and the painlessness of the
process.”
University of California, Santa Barbara
19 February 2009
A place for everything:
More researchers must record the latitude and longitude of their data.
Editorial: Nature 453, 2 (1 May 2008)
14. Web 2.0 and Spatial Mashups
Web 2.0: The notion of the Internet as a
computing platform.
tags: sharing, collaboration, user generated content, community, dynamic, real-time
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quot;Web 2.0 is the business revolution in the computer
industry caused by the move to the Internet as platform,
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and an attempt to understand the rules for success on
that new platform.“
Tim O’Reilly, December 2006
15. What is a Mashup?
Mashup: a website or application that
combines data from more than one source.
Characteristics:
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combination, aggregation, visualization
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16. Enabling Technologies
• web search
• client-server architecture
• Internet applications and AJAX
wikis, online office apps, email, maps, media
hosting, social networks, asynchronous data
and response
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• structured, simple data types
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XML and RSS
• Application Programming Interfaces (API)
• willing users
17. Sample Software
Open Source
NASA World Wind (client and server)
OpenLayers (client)
MapServer (server)
Geoserver (server)
GDAL/OGR (server-based geo-database toolkit)
GRASS (full desktop GIS client)
Google Earth (client)
Google Maps (client)
Free
Microsoft Virtual Earth (client)
University of California, Santa Barbara
ArcGIS Explorer (client)
MapQuest (client)
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Google Earth Enterprise (server)
Proprietary
ArcGIS (full desktop GIS client)
ArcGIS Server (server)
deCarta (server)
AutoDesk AutoCad (client)
AutoDesk ProductStream (server)
Oracle Spatial (server)
18. Example Geographic File Types
• ESRI shapefile (.shp)
• KeyHole Markup Language (.kml)
• GeoRSS (.rss, .xml)
• AutoCad DXF (.dxf)
• Census TIGER
• ESRI Coverage
• ESRI Personal Geodatabase
• GeoTIFF
• Digital Raster Graphic (DRG)
• Digital Elevation Model (DEM)
University of California, Santa Barbara
• Spatial Data Transfer Standard (SDTS)
• Image formats like jpg, tiff, gif, and png (often served via a WMS operation)
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Considerations when choosing a file type for spatial data:
What software support it? What does your consumer want? Is it fast? What
type of data, complexity, and dynamics can it support? How easy is it to
autogenerate and update (from your database to the new file format)? How
well will it age?
19. The language, tools, and technology of cartographers, geographers and spatial
information engineers.
Map Making Process
Transformation
simplifying, generalizing, and abstracting the world
Interrogation
asking questions of spatial data and maps
Communication
creating spatial results that can be understood and have meaning
Geographic Information Systems
Collection
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Storage
Analysis
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Visualization
Geostack
capture
produce
communicate
aggregate
consume
20. University of California, Santa Barbara
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Note: Classroom use only. Cartographers, GIS Thinkers, Neogeographers
21. University of California, Santa Barbara
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The Geostack (Source: Andrew Turner, highearthorbit.com)
22. The nature of online spatial queries
• data overlays are common
• queries are often predesigned and directed
• user generated content, also known as volunteered
geographic information, is prevalent. These data are
often harnessed as “wisdom of crowds” / “collective
intelligence”. Could be considered a brute-force type
query.
• data are often discovered through search and browsing
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• simplicity and ease of use are emphasized
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Google’s Impact
250,000,000 Google Earth activations
1,000 human lifetimes spent using Maps/Earth
Source: John Hanke, October 2007
24. reliability (authority, persistence, legacy) of data
patchiness (inconsistent data quality, availability and resolution)
reliability of associated infrastructure
inaccessibility when not connected to internet
lack of metadata
privacy (both in space and time)
national security interests
inappropriate use of data (analytical issues, scale)
Concerns
classical mapping issues
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misunderstanding projections
poor design, confusing, misleading
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hard to use
slow, varying scales (often ignored) -- Google Maps
intellectual property
unlabeled censorship
25. University of California, Santa Barbara
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Source: http://crschmidt.net/mapping/wpserverdemo/, 2009
26. Practice
familiarity with “the geostack”
client/server interaction
Python
Java
University of California, Santa Barbara
Javascript
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GDAL/OGR
OSGeo Projects
27. Case Study: Keyhole Markup Language (KML)
Keyhole Markup Language (KML) is an open source XML-based
specification for expressing geographic data.
Developed as a Google Earth file format to represent
georeferenced points, polylines, polygons, and images
KML has become widely supported by many other software
applications and online mapping services.
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Core data within a KML document include longitude, latitude,
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elevation, and name descriptions
A sizable number of advanced specifications also exist, including
tags for cartographic customization, viewer position, time, and
iterative data refresh calls.
28. HelloWorld.kml
<?xml version=quot;1.0quot; encoding=quot;UTF-8quot;?>
<kml xmlns=quot;http://earth.google.com/kml/2.2quot;>
<Document>
<name>HelloWorld1.kml</name>
<Placemark>
<name>Transformers</name>
<description>There are some transformers here.</description>
<Point>
<coordinates>
-119.8512453552352,34.41944355498201,0
</coordinates>
</Point>
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</Placemark>
</Document>
</kml>
19 February 2009
Something to notice
If the first letter of a tag is upper
case, it can hold child elements. If
the first letter is lower case, it
denotes a simple element—one
that has no possible children.
29. HelloWorld.kml University of California, Santa Barbara
19 February 2009
30. Network Link
Via a Network Link, a server-side
script could call external
databases or other online
Dynamic KML
sources.
You could also create a webpage
interface that assembles and
returns a KML based on user
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preferences.
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For example: Source: NOAA
http://radar.weather.gov/ridge/kmzgenerator.php
http://www.srh.noaa.gov/gis/kml/
31. Time
In KML, features can be associated with time with
these tags:
<TimeStamp> associates a feature to an
Dynamic KML
instant in time
<TimeSpan> associates a feature to a
length of time. The tag
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requires a begin time
and/or end time.
19 February 2009
With respect to rendering, these tags typically
serve as a visibility filter against a timeline.
32. Temporal Tags Example
…
<Placemark>
<name>Transformers</name>
<description>There are some transformers here.</description>
<Point>
<coordinates>0,0,0<!simplified></coordinates>
Dynamic KML
</Point>
<TimeSpan>
<begin>1990</begin>
<end>2009</end>
</TimeSpan>
</Placemark>
University of California, Santa Barbara
<Placemark>
<name>homebase</name>
<description>Line from home base to transformers.</description>
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<LineString>
<tessellate>1</tessellate>
<coordinates>0,0,0 1,1,0<! simplified></coordinates>
</LineString>
<TimeStamp>
<when>2008-09-24T10:30:15-08:00</when>
</TimeStamp>
</Placemark>
…
33. Time
When Google
Earth reads a
temporal tag
within KML, a
time browser
appears.
Clicking on the
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clock icon
19 February 2009
brings up
additional time
navigation
options.
Source: Google Earth and Declan Butler; http://www.nature.com/news/author/Declan+Butler
34. Distribution and Sharing
(Note: some of these overlap and/or could be combined)
A) Delivery of raw or auto-assembled KML
KML file is shared via a website, email, or disk
User loads KML into the Google Earth application
B) Delivery of KML from Google Maps
KML is hosted
Google Maps renders KML
C) Delivery of KML with the Google Earth browser plug-in
Webpage created using Google Earth API
Hosted KML is rendered within Google Earth frame
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D) Delivery with desktop applications like ArcGIS Explorer,
Virtual Earth, NASA World Wind, etc.
19 February 2009
Generally similar to standalone KML (option A)
E) Mediator web service
Website service allows user collaboration, provides
hosting, and file index or discovery mechanism.
Examples: Google MyMaps, Flickr, Platial , Facebook,
Yahoo! FireEagle
35. Distribution and Sharing
(Note: some of these overlap and/or could be combined)
F) Server-based delivery
Application and data are hosted. Interface may be
public or, in some cases, secured. Examples: Google
Earth Enterprise, OpenLayers, ArcGIS Server
G) Enterprise relational database manager
Typically for intranet-type usage. Manages multiple user
collaboration, conflicts, and versioning
Oracle Spatial, ArcSDE
University of California, Santa Barbara
H) Search engine discovery of spatial data (an emerging case);
programmatic structured query using various sites’ APIs.
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Application launches as defined by user or OS (assisted
by properly configured MIME type). Examples: Google
Search, Yahoo! Pipes, Microsoft Popfly
36. Select Geographic Database Analysis Tasks
Relational-spatial attribute query
Proximity analysis (buffer and
distance calculation)
Query
Spatial joins (intersection and union
comparisons; inside/out)
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Network analysis (routing and
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optimization; left/right; topology)
Raster comparison (Map Algebra)
37. Geocoding
The process of assigning geographic coordinates to a
map feature, description, or address.
Input: Address or location description
Examples: Goleta, CA; 90210; New Zealand
World Trade Center, downtown Los Angeles
Query
Output: Geographic Coordinates
University of California, Santa Barbara
45.2342W, 15.2346N, 1000m asl, WGS84
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There are many complicating factors to geocoding.
For example: the grammar of the input, positional
accuracy / vagueness / scale, places with the same
name, foreign languages, deprecated names, new
names, misspellings, etc.
38. Geocoding
Despite the problems, geocoding is at the core of
many web-based mapping applications.
KML offers the <address> element as an alternative
to coordinates. Google Earth and Google Maps will
attempt to geocode the address and render the
Query
position. Usability will largely depend on the input
address and the intended application.
University of California, Santa Barbara
For example, the following KML uses the street
address of a UCSB electrical transformer station
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(shown in the middle left of the screen; geocoded
address is on the bottom right).
Note: In Google Earth and Maps, if a <Point> tag is provided in the
KML also, it will take precedence over an <address>.
39. <?xml version=quot;1.0quot; encoding=quot;UTF-8quot;?>
<kml xmlns=quot;http://earth.google.com/kml/2.2quot;>
<Document>
<name>addressexample.kml</name>
<Placemark>
<name>Transformers</name>
<description>Better than nothing.</description>
<address>552 University Road, Santa Barbara, CA
University of California, Santa Barbara
93106</address>
</Placemark>
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</Document>
</kml>
40. Geocoding Resources
Google Maps API
Yahoo! Maps and FireEagle API
MetaCarta Labs
Query
Geocoder.us
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Batchgeocode.com
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NGA Geographic Names Search
Mapping Hacks by Erle, Walsh, and Gibson
(available from O’Reilly). How to build your
own geocoder.
41. Routing and
Service Area
Routing implementations
remain largely proprietary,
though some open source
options are beginning to
emerge.
The Google Maps API offers
access to driving directions.
University of California, Santa Barbara
Proprietary web services are
plentiful.
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ArcGIS Server offers routing
functionality.
Image source: ArcGIS Network Analyst, esri.com
42. Google Earth Developers
Interact with other developers and explore their work.
Query: Analysis Resources (http://groups.google.com/group/kml-support)
ArcGIS Explorer
Proprietary virtual globe with analysis functionality, particularly
when coupled with other ESRI products. Note: UCSB has an
ArcGIS site license. (esri.com)
Yahoo! Pipes
Graphical multistep web query that includes spatial data.
(pipes.yahoo.com)
University of California, Santa Barbara
Microsoft Popfly
Graphical multistep web query that includes spatial data.
(popfly.com)
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OpenLayers
Javascript slippy map library with a gallery of numerous web
applications. (openlayers.org)
GIS.com
A “paleo” introduction to geographic information and analysis
43. Source: Yahoo! Pipes; Photos near Wineries, Author: Ido
Query: Example
University of California, Santa Barbara
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44. University of California, Santa Barbara
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http://www.esri.com/software/arcgis/explorer/graphics/showcase/longbeach-plume-lg.jpg
Source: ArcGIS Explorer, esri.com
45. Policy and Best Practices The Policy Landscape
No homogenous body of geographic data web standards
or regulations exist. So far, emerging precedents are
largely arising from privacy and intellectual property law.
Private enterprise is also gauging consumer reaction and
trying to maximize utility, create monetization potential,
and not alienate users.
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Accessibility
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Suggested Design Practices
Locational Privacy
46. -Wired.com, September 11, 2008
Policy and Best Practices
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19 February 2009
47. Accessibility
Policy and Best Practices Provide a text description of the map’s or data’s purpose.
Provide descriptions of any included, integrated multimedia.
Use clear, descriptive names and labels.
Consider appropriate colors and contrast for people with color
discernment difficulties or other visual impairment
Cite data sources; allowing users to investigate other mechanisms for
its visualization
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In technology selection, consider open 3D rendering formats. For
instance, OpenGL calls to a graphics card can be captured and
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manipulated. Haptic feedback devices can more readily interpret the
data.
Ensure links are simple, visible, and exposed (no hidden image links)
Be very cautious about rapid blinking and dynamic data refreshes.
Provide warnings as necessary to assist epileptic population.
48. Best Practices
Policy and Best Practices
Consider geographic and cartographic principles
Use GeoRSS to syndicate geographic data (refer to
KML). HTML:RSS::KML:GeoRSS
Maximize link confidence (hide awkward script
calls; links to external resources should be reliable;
make sure the external resource acts like you think
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it should).
Provide usage information and instructions for
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complex data
Provide data authorship credit (also affords author
responsibility).
49. Best Practices
Policy and Best Practices
Consider window viewing sizes (large images and
long descriptions can take over an entire
viewscreen).
Allow users control and navigation of layers.
Consider file size, number of points, complexity
(warn as necessary). For instance, in KML, use
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Regionator to manage large image overlays
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Minimize the distraction of legends or screen
overlays.
Cache geocodes
50. Geographic Privacy
Policy and Best Practices
Right to privacy varies greatly by jurisdiction. The
California Constitution, Article 1, Section 1,
describes privacy as an inalienable right.
Spatial and temporal data resolution is a key
component with respect to invasion of privacy.
For example, spatially aggregated U.S. Census
University of California, Santa Barbara
data are available soon after compilation.
Individual Census responses are prohibited from
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release for 72 years.
Aggregating multiple individuals’ personal
information is considered less invasive than
individually identifiable information.
51. Geographic Privacy
Policy and Best Practices
Internet users are comprised of all age groups, including
those that may have no understanding of personal privacy
or its consequences.
University of California, Santa Barbara
19 February 2009
Graphic source: David H. Williams/E911-LBS, October 25, 2006,
The associated article argues for privacy considerations to be an fundamental part of Location-Base Service design
http://www.directionsmag.com/article.php?article_id=2323&trv=1
52. Yahoo! Fire Eagle
Policy and Best Practices Developer Code of Conduct
Note: These points are paraphrased.
Always tell users what you want to do with
their location
Let users know when you are collecting their
location information
Give users control of their own data
University of California, Santa Barbara
Make sure users' data are secure
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Only allow users to manage their location, but
not others
Don't be creepy
Source: Fire Eagle Developer Code of Conduct,
http://fireeagle.yahoo.net/developer/documentation/code_of_conduct
53. International Safe Harbor Privacy Principles
Policy and Best Practices Notice - Individuals must be informed that their data is being
collected and about how it will be used.
Choice - Individuals must have the ability to opt out of the
collection and forward transfer of the data to third parties.
Onward Transfer - Transfers of data to third parties may only occur
to other organizations that follow adequate data protection
principles.
Security - Reasonable efforts must be made to prevent loss of
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collected information.
Data Integrity - Data must be relevant and reliable for the purpose
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it was collected for.
Access - Individuals must be able to access information held about
them, and correct or delete it if it is inaccurate.
Enforcement - There must be effective means of enforcing these
rules.
Source: United State International Trade Administration
54. “We no longer go to maps to find out
where we are. Instead, we tell maps
where we are and they form around us
on the fly.”
Jessica Clark- American University
University of California, Santa Barbara
(February 2008)
19 February 2009
55. Evolving Spatial Information
• software objects for dynamics
• language for object dynamics
• UML equivalent for fields
• handling real-time feeds
• handling spherical/global queries
• realistic actors (phenomena that react to stimuli:
interactions, time, physics)
• interior data models
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• spatiotemporal data handling
• asynchronous analysis
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• sensor networks
Source: Goodchild and Glennon (2007)
56. The near Future of Spatial Data
more. everywhere.
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19 February 2009
Image Source: NAIP, 2005
57. The near Future of Spatial Data
• Web 3.0: automated data discovery and
analysis
• ubiquity
• mixed reality
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• evolving business models
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• conversations with maps
• expanding scales
• interior spaces
Image Source: NAIP, 2005
58. The Future of Spatial Data
An evolving platform:
extending the geographic model to Eames’ and
Morrisons’ Powers of Ten
The Progression of Internet Maps Interaction:
1. view (see my house)
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2. add (tag locations important to me)
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3. query (get directions, see patterns)
4a. communicate (sharing and social interaction)
4b. mirror world (more realism/physics)
5. inhabit
Image Source: NAIP, 2005
59. The Future of Spatial Data
Semantic Spatial Web
(spatially literate, natural language Internet)
3D Internet
(spatially visualized and inhabitable Internet. Mixed
mirrored and virtual reality)
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Digital Earth
(spatiotemporal database of everything)
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Transhumanism
(closer connection of information to individual senses.
Think digital contact lenses and putting your own skin
on reality. Consequential multi-place existence)
Image Source: NAIP, 2005
60. University of California, Santa Barbara
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Sources: GeoEye.com 2008, Openstreetmap 2009, Wikimedia 2008
Image Source: GeoEye.com 2008
61. SPATIAL INFORMATION and the
INTERNET
• Internet geography is mass media. Be a communicator.
• Internet geography is accessible. Be useful.
• Internet geography is at its best when it is timely and also considers
geographic concepts. Be fast. Be smart.
University of California, Santa Barbara
• Internet geography creates higher public expectations for
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professional geographers. Be thoughtful. Be better.
• Internet geography is not bound to simple queries and mashups.
That is, it can be GIS. Push it forward. Be an engineer. Be a geographer.
Image Source: GeoEye.com 2008