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Dr David Mountain LBS Research @ City

Future of Location Technologies Session 2: Geo-content Why new forms of geo-content are driving the development of location-sensitive applications. Dr David Mountain LBS Research @ City. David Mountain – Bio. Lecturer at City University

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Dr David Mountain LBS Research @ City

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  1. Future of Location TechnologiesSession 2: Geo-contentWhy new forms of geo-content are driving the development of location-sensitive applications Dr David Mountain LBS Research @ City

  2. David Mountain – Bio • Lecturer at City University • Research interests in GI science and location-based services since 2000 • Technical director of Placr Ltd • Start-up offering products and solutions for mobile, location-aware systems since 2008

  3. 11.45 – 13.00 Session 2: Geo-content • New forms of geo-content are driving the development of location-sensitive applications • Background mapping: • Sources of map data and online APIs • provide context for location apps • Foreground content: • Georeferenced feeds and POI databases • provide content for local search

  4. 2.1 BACKGROUND MAPPINGSources of Mapping data • Where does the raw spatial data for maps come from? • Diverse industry: different organisations create products with v different characteristics: • Coverage: spatial extent, resolution, completeness • Accuracy: collected to a defined standard? • Commercial arrangement: free, one-off payment, annual licensed, pay per use, ad-based revenue?

  5. Mapping organisations • National Mapping Organisations (NMOs): • Role has changed from producers of map products, to providers of geospatial data. Increasingly, providers of geospatial services • NMOs usually have published quality standards: currency, accuracy, coverage, completeness. • Ordnance Survey (UK): latest strategy (April 2009) sees growing commercial role: simpler licensing frameworks, cost reduction, ‘free services’, innovative mapping services

  6. Crubenmore Lodge, Scottish Highlands:Ordnance Survey Detail

  7. Commercial spatial data providers • Niches in the GI data market filled by private companies. • Street networks / remotely sensed imagery / geodemographics • Market consolidation as market matures • TomTom acquire Tele Atlas; ($3bn, 2008) • Nokia acquire NavTeq ($8bn, 2007) • Data acquired from wide sources. Wide variation in coverage and completeness. • Follow the money …

  8. Navteq: London and Kinshasa

  9. Open Source Spatial data • Since 2005, OpenStreetMap (OSM) has been creating an open source map of the world. • Bottom up approach: features are tagged, no formal attributes. No formal definition of what will be surveyed, to what level of accuracy, how this will be done, or frequency of update • Sources include enthusiastic amateur surveyors, and public available data

  10. Growth of OpenStreetMap 1mn users, 1bn points

  11. OpenStreetMap (OSM) • Impressive growth in users coverage • Quality measured by ‘completeness’: number of features they have for a region compared with alt suppliers • By mapping regions and features that other orgs ignore, they can surpass 100% ‘completeness’

  12. Kinshasa: NavTeq vs OSM

  13. St Albans: Ordnance Survey vs OSM

  14. OSM • But away from the main centres of popn, coverage can be poor

  15. Tarbert, Kintyre Peninsular:Ordnance Survey vs OSM

  16. Online mapping APIs • How can this data be accessed in an online environment? • Application-programming interfaces (APIs): • Software to software interfaces, not GUIs • Standards and functions for accessing web-based software • Released to allow developers to design services based on this software. • Online mapping APIs often accessed using scripting languages processed by web browser, such as javascript

  17. Controlling Google map: API vs UI

  18. Mapping APIs: functions • Dozens of mapping APIs available • Similar base functionality: pan, zoom, centre, set map size, overlay features. • Distinctions between them based on: • Source data; • Advanced functionality (alternative cartography, 3D interfaces, geocoding services, routing APIs); • Commercial terms: free, price based on web traffic, ad-based revenue;

  19. Google Maps API • De facto standard mapping API • Raw data from diverse sources: $bns pa • Global coverage, free for developers • Advanced functionality includes: • Geocoding placenames –> coords • Overlay objects • Support for directions and routing • Local Search • Support for 3D (Google Earth) • StreetView • Integrating georeferenced web feeds

  20. Other commercial mapping APIs • Most are free, have global coverage, allow geocoding, display alternate layers as backdrop, and overlay features as foreground. • Yahoo maps: • Innovative mapping API: pipes allows you to develop apps without code! • Microsoft: virtual earth / bing maps • 2D and 3D mapping

  21. Yahoo pipes – API

  22. Yahoo pipes – Flickr ‘beach’ search

  23. NMOs: Ordnance Survey OpenSpace • Based on OpenLayers (online mapping API) in development since 2006. • Now being pushed in response to OS’s mission to innovate and compete commercially • Free limited use • UK coverage: mapping, geocoding, alt layers. • Main benefits: map detail, quality assurances, breadth of coverage

  24. City Uni – OpenSpace API

  25. City Uni – Google Maps API

  26. Cloudmade and OpenStreetMap • Opensource data (OSM - global coverage) • Commercial services (Cloudmade) • Biz model: free, then ad-based revenue • Innovative API • Routing / overlay • Support for mobile apps • Configuration of cartographic style

  27. Cloudmade: style editor Midnight commander Original Pale dawn

  28. 2.2 FOREGROUND CONTENT • Previous section focused on contextual mapping for location-aware web apps: background geo-content • This section focussed foreground geo-content: • documents, multimedia, blogs, new articles, physical features, etc.. • Structure: • What are web feeds? • Spatial markup • Existing georeferenced feeds • Geocoding nonspatial web feeds

  29. Web feeds • A data format used by content providers to publish frequently updated information • Web feeds imply dynamic content, but static content is also available in structured formats that can be reused • Key distinction: structured data • People subscribe to feeds, and can view them using feed readers, or web browsers, which check periodically for updates • Really simple syndication (RSS) mostly widely used format, but there are others (e.g. ATOM) • Many content providers now provide an RSS feed: BBC, Reuters, Stephen Fry blog, City University London

  30. BBC news feed

  31. Spatial mark-up • Most web feeds use XML to structure their content • Many XML-based languages allow geographic information to be represented: • OGC Geography Markup Language (GML) • Google’s Keyhole Markup Language (KML) • Wiki formats using |coord| • GeoRSS: geographic referencing in RSS feeds

  32. Spatial Markup examples

  33. GeoRSS feeds • Simple to integrate into web maps using mapping APIs • Services are emerging which aggregate spatial content: map mashups: • Flickrvision: http://www.flickrvision.com/ overlays flickr’s most recent GeoRSS feed on Google Maps • Twittervision: http://beta.twittervision.com/: does the same for Twitter • KML and GeoRSS content can also be published as layers in Google Earth • Increasing volumes of geo-content are now available this way

  34. Google Earth GeoContent

  35. Geocoding non-spatial data • How do we spatially enable the whole web? • Geoparsers can recognise placenames in natural language documents • Geocoders can find the coords associated with those placenames. • But how do we disambiguate? • I was reading in Reading • I stoke the fire • I am reading a book by Jack London

  36. POI databases • Until now, the dominant form of geo-content • Databases of features storing geometry, attributes, and categories • E.g. Yahoo / Google maps / Vodafone live / POI friend • Search combination of category / keyword and current location • Tend to focus on facilities / services (cf Yellow pages) rather than information (cf guidebook) • Brand provides a service guarantee

  37. POI databases • Point X from OS: just points • Data retrieval • Most popular categories (mCommerce)

  38. OS PointX dataset

  39. Filtering GeoContent Temporal proximity Spatial proximity Speed heading prediction Visibility

  40. Scenarios of use

  41. The future • A world where you are the search engine? • Agents regularly repeat searches for content matching your trigger phrases, based on location • E.g. a walk around central London searching for ‘Great Fire’, or Banksy • A drive up the M1 searching for comedy • Some info needs may expire, some may endure

  42. Searching Google Earth community pages for Banksy in London

  43. 230 miles of love

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