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Mashups Beyond Google Maps from a Geospatial Semantic Web Perspective

Mashups Beyond Google Maps from a Geospatial Semantic Web Perspective. Harry Chen Image Matters LLC (Geospatial Semantic Web Blog) Networking Geospatial Information Technology for Interoperability and Spatial Ontology Workshop NSF, Washington DC June 20, 2006. Outline. Introduction

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Mashups Beyond Google Maps from a Geospatial Semantic Web Perspective

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  1. Mashups Beyond Google Mapsfrom a Geospatial Semantic Web Perspective Harry Chen Image Matters LLC (Geospatial Semantic Web Blog) Networking Geospatial Information Technology for Interoperability and Spatial Ontology Workshop NSF, Washington DC June 20, 2006

  2. Outline • Introduction • Google Maps & Google Earth • Shortcomings in the current mashups • How Semantics Can Help • Semantic Web vs. semantic web • Semantic Web Mashup Example • From triples to Google Maps • Concluding Remarks

  3. Visiting the White House The White House in Google Maps The White House in Google Earth

  4. Google Maps vs. Google Earth

  5. Special Features in Google Earth 3D buildings and terrian Measure Distances

  6. An Explosion of Mashups A mashup is a website or web application that uses content from more than one source to create a completely new service. Source: Wikipedia -- http://en.wikipedia.org/wiki/Mashup_(web_application_hybrid) Source: New Scientist (2006-05-12) Check Real Estate Value Track Ski Conditions Track Storms

  7. Questions • Why is there a sudden explosion of “mashups”? Is it the “holy grail” in building the next generation Web? • What’s the use of semantic technology in building mashups? • Do we have the right semantic technology?

  8. Mashups are Growing Fast • Ubiquitous web service API • Google Maps, Yahoo! Maps, Amazon, Flickr, del.icio.us, etc. • People can create new applications by reusing the existing parts • The whole is more than the sum of its parts • Maps are intuitive UI interface.

  9. Mashup Issues (1 of 3) • The present Web is built for human users. Information is meant for humans to consume and not for computer programs. • A map image is a map to the humans, but is a image to the machines. Map! GIF!

  10. Mashup Issues (2 of 3) • It’s difficult to discover and integrate legacy data into new mashup applications. Where can I find real estate data? Data format? Permission to use it? Real Estate Value Mashup Where can I find weather data? Data format? Permission to use it? National Ski Condition Mashup

  11. Mashup Issues (3 of 3) • Too many wrongly think that mashups must be Google Maps on “steroid”. • Web 2.0 Mashup Matrix • Records 104 Web 2.0 API • 104 x 104 possibilities • Google Maps 1 of 104 http://www.programmableweb.com/matrix

  12. II. How Semantic Web Can Help

  13. How the Semantic Web Can Help • Shared Semantic Web ontologies will enable mashups to share data and interoperate • Expressively defined knowledge on the Web will enable mashups to better discover and access existing information • Non-geographical semantic knowledge will encourage the innovation of non-map-based mashups

  14. Semantic Technology on the Web • Semantic Web vs. semantic web • Publishing geospatial data on the Web • Exporting legacy data onto the Web • Searching semantic data on the Web RDFS Structured Blogging hCard XML GML RDF/A KML RSS GeoRSS RDF rel-tag XNF OWL Geo Microformat

  15. Semantic Web vs. semantic web

  16. Publishing Geospatial Data • Describing Geo coordinates • W3C RDF Geo Vocabulary (WGS 84) • Geo of Microformat (WGS 84) • GeoRSS – encoding GML geometry in RSS • Describing geographical locations • CIA Fact Book • http://www-ksl-svc.stanford.edu:5915/doc/wfb/index.html • Open Cyc Spatial Ontology • http://www.cyc.com/cyc-2-1/cyc-vocab.daml

  17. Using W3C Geo <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:geo="http://www.w3.org/2003/01/geo/wgs84_pos#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns="http://xmlns.com/foaf/0.1/"> <Person> <name>Dan Brickley</name> <homepage dc:title="Dan's home page“ rdf:resource="http://danbri.org/"/> <based_near geo:lat="51.47026" geo:long="-2.59466"/> <rdfs:seeAlso rdf:resource="http:/danbri.org/foaf.rdf"/> </Person> </rdf:RDF> Source: http://www.w3.org/2003/01/geo/

  18. Using Microformat Geo (1)

  19. Using Microformat (2) <p class="vcard"> <a class="url fn" href="http://harry.hchen1.com">Harry Chen</a> was born in Shanghai, China. He moved to Hong Kong with his parents when he was ten. During the last year of his high school, he studied in the US as an exchange student . He completed undergraduate and graduate studies in Computer Science at the <a title="UMBC" class="org" href="http://www.umbc.edu">University of Maryland, Baltimore County</a>. He was awarded a PhD fellowship from HP Labs for his work on intelligent agents in mobile and pervasive computing. </p> … Currently he lives in Columbia, Maryland ( <span class="geo"> <span class="latitude">391425N</span>, <span class="longitude">0765022W</span> ) with his wife Gigi. </span> …

  20. Technorati: Microformat Search Not yet understand “geo”, but that’s okay. At least it works! http://kitchen.technorati.com

  21. Exporting Legacy Data • Much data is hidden in our legacy systems. We must find ways to export this data onto the Web • Web pages are designed for people. For the Semantic Web we need to look at existing databases and the data in them. • Tim Berners-Lee, March 2006. • http://www.bcs.org/server.php?show=ConWebDoc.3337

  22. Getting Data onto the Web • Approach 1: Consolidate everything into a single database

  23. Getting Data onto the Web • Approach 2: Dynamically integrate data into a uniformed representation

  24. Data Integration Systems • Oracle RDF database (Oracle) • Supports full RDF and RDFS • Support SQL query over RDF graph model • Built-in subsumption support: subClassOf and subPropertyOf • D2RQ (Freie Universität Berlin): • Declarative language for describing mappings between relational DB schemas and RDFS/OWL ontologies • Support SQL • D2RQ Server allows accesses to SQL using SPARQL queries over HTTP • KnowledgeSmarts (Image Matters LLC) • A middle-ware system for knowledge integration over heterogeneous datastores • Supports SQL, Shapefiles, XML, WFS and more. • Optimized for applications that require spatial and temporal computation support.

  25. Searching Semantic Data • Swoogle: a Semantic Web search engine • The Ebiquity Research Group at UMBC • Indexes 1.5 million SW documents (as of 2006/06) • Performs sophisticated statistic analysis on triples, OWL classes, OWL properties, and documents (similar to Page Rank) • How to search “geo” ontology using Swoolge • http://geospatialsemanticweb.com/2006/06/06/searching-geospatial-ontologies-in-swoogle http://swoogle.umbc.edu

  26. III. Semantic Web Mashup Example

  27. Semantic Mashup: Piggy Bank • Piggy Bank is a Firefox extension that uses JavaScript to scrape RDF triples from the Web. • Part of MIT’s SIMILE project • http://simile.mit.edu/piggy-bank

  28. Movies at Toronto.Com Typical movies listing Piggy Bank this information

  29. Semantic Data in a Piggy Bank Location information Movies!!!!

  30. Location! Location! Location!

  31. IV. Concluding Remarks

  32. Mashups are HOT • An explosion of “mashups” is fueled by • (1) ubiquitous Web Service API (esp. Google Maps API) • (2) the idea that “everyone can create new applications by reusing the existing parts” • (3) the rediscovery of the power of “maps”

  33. Semantics is the Key • Developing more sophisticated mashups will require the use of Semantic Web technology • For publishing data on the Web • For exporting legacy data onto the Web • For search semantic data on the Web • We should embrace both “Semantic Web” and “semantic web” technology

  34. You Mashup? By Cathy Wilcox, the Sydney Morning Herald

  35. Resources • Geospatial Semantic Web Blog • http://geospatialsemanticweb.com • Bookmarks, links to podcasts and more • Questions? • Email: harryc@imagem.cc • http://harry.hchen1.com

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