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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.

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 Spatial Information and the Internet Presentation Transcript

  • SPATIAL INFORMATION and the Alan Glennon INTERNET spatial.ucsb.edu University of California, Santa Barbara 19 February 2009 Image Source: GeoEye.com 2009
  • 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: 19 February 2009 Hosting events (brownbags, workshops, lectures) Developing spatial analytic tools Offering a help desk Assisting with research proposal development Image Source: NAIP, 2005
  • Source: Wikimedia Commons, 2008 University of California, Santa Barbara 19 February 2009
  • Source: Allen Gathman, 2008 University of California, Santa Barbara 19 February 2009
  • Source: Strangemaps, 2008 University of California, Santa Barbara 19 February 2009
  • 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
  • Image Source: GeoEye.com 2008
  • Source: Photosynth.com, 2008 University of California, Santa Barbara 19 February 2009
  • 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 19 February 2009 geography • Capabilities and concerns • Policy and best practices • Future Image Source: GeoEye.com 2008
  • Geographic Data Two practical perspectives: University of California, Santa Barbara Data that include or can be harvested for spatial 19 February 2009 references Combinations of spatially-referenced points, polylines, polygons, and images with their associated attributes and relationships Image Source: Google.com 2008
  • Image Source: Google.com 2008 Geographic Data University of California, Santa Barbara 19 February 2009
  • Geographic Data Significance: visually compelling provide context and content; close things are usually more related; spatial order; pattern and trend University of California, Santa Barbara recognition 19 February 2009 popular; widespread use, particularly on the Internet professional expectation: Google Maps as a baseline
  • “…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)
  • 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 University of California, Santa Barbara quot;Web 2.0 is the business revolution in the computer industry caused by the move to the Internet as platform, 19 February 2009 and an attempt to understand the rules for success on that new platform.“ Tim O’Reilly, December 2006
  • What is a Mashup? Mashup: a website or application that combines data from more than one source. Characteristics: University of California, Santa Barbara combination, aggregation, visualization 19 February 2009
  • 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 University of California, Santa Barbara • structured, simple data types 19 February 2009 XML and RSS • Application Programming Interfaces (API) • willing users
  • 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) 19 February 2009 Google Earth Enterprise (server) Proprietary ArcGIS (full desktop GIS client) ArcGIS Server (server) deCarta (server) AutoDesk AutoCad (client) AutoDesk ProductStream (server) Oracle Spatial (server)
  • 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) 19 February 2009 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?
  • 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 University of California, Santa Barbara Storage Analysis 19 February 2009 Visualization Geostack capture produce communicate aggregate consume
  • University of California, Santa Barbara 19 February 2009 Note: Classroom use only. Cartographers, GIS Thinkers, Neogeographers
  • University of California, Santa Barbara 19 February 2009 The Geostack (Source: Andrew Turner, highearthorbit.com)
  • 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 University of California, Santa Barbara • simplicity and ease of use are emphasized 19 February 2009 Google’s Impact 250,000,000 Google Earth activations 1,000 human lifetimes spent using Maps/Earth Source: John Hanke, October 2007
  • Source: openstreetmap.org, 2009 University of California, Santa Barbara 19 February 2009
  • 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 University of California, Santa Barbara misunderstanding projections poor design, confusing, misleading 19 February 2009 hard to use slow, varying scales (often ignored) -- Google Maps intellectual property unlabeled censorship
  • University of California, Santa Barbara 19 February 2009 Source: http://crschmidt.net/mapping/wpserverdemo/, 2009
  • Practice familiarity with “the geostack” client/server interaction Python Java University of California, Santa Barbara Javascript 19 February 2009 GDAL/OGR OSGeo Projects
  • 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. University of California, Santa Barbara Core data within a KML document include longitude, latitude, 19 February 2009 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.
  • 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> University of California, Santa Barbara </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.
  • HelloWorld.kml University of California, Santa Barbara 19 February 2009
  • 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 University of California, Santa Barbara preferences. 19 February 2009 For example: Source: NOAA http://radar.weather.gov/ridge/kmzgenerator.php http://www.srh.noaa.gov/gis/kml/
  • 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 University of California, Santa Barbara 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.
  • 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> 19 February 2009 <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> …
  • Time When Google Earth reads a temporal tag within KML, a time browser appears. Clicking on the University of California, Santa Barbara 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
  • 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 University of California, Santa Barbara 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
  • 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. 19 February 2009 Application launches as defined by user or OS (assisted by properly configured MIME type). Examples: Google Search, Yahoo! Pipes, Microsoft Popfly
  • Select Geographic Database Analysis Tasks Relational-spatial attribute query Proximity analysis (buffer and distance calculation) Query Spatial joins (intersection and union comparisons; inside/out) University of California, Santa Barbara Network analysis (routing and 19 February 2009 optimization; left/right; topology) Raster comparison (Map Algebra)
  • 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 19 February 2009 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.
  • 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 19 February 2009 (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>.
  • <?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> 19 February 2009 </Document> </kml>
  • Geocoding Resources Google Maps API Yahoo! Maps and FireEagle API MetaCarta Labs Query Geocoder.us University of California, Santa Barbara Batchgeocode.com 19 February 2009 NGA Geographic Names Search Mapping Hacks by Erle, Walsh, and Gibson (available from O’Reilly). How to build your own geocoder.
  • 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. 19 February 2009 ArcGIS Server offers routing functionality. Image source: ArcGIS Network Analyst, esri.com
  • 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) 19 February 2009 OpenLayers Javascript slippy map library with a gallery of numerous web applications. (openlayers.org) GIS.com A “paleo” introduction to geographic information and analysis
  • Source: Yahoo! Pipes; Photos near Wineries, Author: Ido Query: Example University of California, Santa Barbara 19 February 2009
  • University of California, Santa Barbara 19 February 2009 http://www.esri.com/software/arcgis/explorer/graphics/showcase/longbeach-plume-lg.jpg Source: ArcGIS Explorer, esri.com
  • 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. University of California, Santa Barbara Accessibility 19 February 2009 Suggested Design Practices Locational Privacy
  • -Wired.com, September 11, 2008 Policy and Best Practices University of California, Santa Barbara 19 February 2009
  • 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 University of California, Santa Barbara In technology selection, consider open 3D rendering formats. For instance, OpenGL calls to a graphics card can be captured and 19 February 2009 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.
  • 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 University of California, Santa Barbara it should). Provide usage information and instructions for 19 February 2009 complex data Provide data authorship credit (also affords author responsibility).
  • 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 University of California, Santa Barbara Regionator to manage large image overlays 19 February 2009 Minimize the distraction of legends or screen overlays. Cache geocodes
  • 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 19 February 2009 release for 72 years. Aggregating multiple individuals’ personal information is considered less invasive than individually identifiable information.
  • 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
  • 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 19 February 2009 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
  • 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 University of California, Santa Barbara collected information. Data Integrity - Data must be relevant and reliable for the purpose 19 February 2009 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
  • “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
  • 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 University of California, Santa Barbara • spatiotemporal data handling • asynchronous analysis 19 February 2009 • sensor networks Source: Goodchild and Glennon (2007)
  • The near Future of Spatial Data more. everywhere. University of California, Santa Barbara 19 February 2009 Image Source: NAIP, 2005
  • The near Future of Spatial Data • Web 3.0: automated data discovery and analysis • ubiquity • mixed reality University of California, Santa Barbara • evolving business models 19 February 2009 • conversations with maps • expanding scales • interior spaces Image Source: NAIP, 2005
  • 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) University of California, Santa Barbara 2. add (tag locations important to me) 19 February 2009 3. query (get directions, see patterns) 4a. communicate (sharing and social interaction) 4b. mirror world (more realism/physics) 5. inhabit Image Source: NAIP, 2005
  • 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) University of California, Santa Barbara Digital Earth (spatiotemporal database of everything) 19 February 2009 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
  • University of California, Santa Barbara 19 February 2009 Sources: GeoEye.com 2008, Openstreetmap 2009, Wikimedia 2008 Image Source: GeoEye.com 2008
  • 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 19 February 2009 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