Semantic Web: In Quest for the Next Generation Killer Apps

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  • Only comment. What about 'Killer Users' instead of 'Killer App'? The problem with 'Killer App' is that its a retrospective moniker. Whereas, 'Killer User' is prospective. I see this presentation as being prospective in orientation :-)
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  • One of the first examples of a killer application is generally agreed to be the VisiCalc spreadsheet on the Apple II platform.[1] The machine was purchased in the thousands by finance workers (in particular, bond traders) on the strength of this program
  • For Windows
  • Once the most popular browser
    Promote WWW
  • The currently most successful Social Network
  • HTML, XML
  • Expedia, Mint, Zillow all provide different solutions
    Reinvent the wheel
  • http://products.semweb.bestbuy.com/products/9316073/semanticweb.rdf
  • Lunch is social event
  • For this demo, we used RDF data derived from ozone and visibility readings provided by the EPA's Castnet project. This RDF combines raw data on Castnet readings (ozone and visibility) with corresponding geographic information on the sites of readings, which the raw Castnet data lacks. On the provided map of the US, every yellow dot represents a single Casetnet site and dot size corresponds to an average Ozone reading for that site, where larger dots represent larger averages. When a Castnet site is clicked, a small pop-up opens, displaying more information on that site, along with a link. This link takes the user to another page that displays in a timeline all the Ozone and Visibility data available for that site. This timeline uses the Google Visualization API giving users added functionality in how they view the data in the timeline. To allow users to filter through Castnet readings, a faceted browsing interface (from the MIT Simile Exhibit API) is provided.
  • This application presents a mashup of foreign aid data (represented in US Dollars) from the United States Agency for International Development (USAID) and UK Department for International Development (DFID) for the 2007 US Fiscal Year.
  • Gartner, Inc. (NYSE: IT) is the world's leading information technology research and advisory company
  • Semantic Web: In Quest for the Next Generation Killer Apps

    1. 1. Semantic Web: In Quest for the Next Generation Killer Apps Jie Bao Tetherless World Constellation Rensselaer Polytechnic Institute baojie@cs.rpi.edu http://www.cs.rpi.edu/~baojie Oct 22nd, 2010 @ UMass Lowell 1
    2. 2. Outline • Why Semantic Web? • Key SW Standards • Opening Data for SW • Building SW Applications 2
    3. 3. What is a Killer App ? 3
    4. 4. A Killer App is • …Any computer program that is so necessary or desirable that it proves the core value of some larger technology, […]. A killer app can substantially increase sales of the platform on which it runs. -- Wikipedia 4 http://en.wikipedia.org/wiki/Killer_application
    5. 5. Visicalc 5
    6. 6. Excel 6
    7. 7. Netscape 7
    8. 8. Facebook 8
    9. 9. Web Itself 9 Sir Tim Berners-Lee As an app of the Internet Picture Source: http://commons.wikimedia.org/wiki/File:InternetProtocolStack.png
    10. 10. ATM 10 A killer app of database and network technologies Picture source: http://en.wikipedia.org/wiki/File:ATM_750x1300.jpg
    11. 11. Where are the killer apps for the Semantic Web? 11
    12. 12. What is Semantic Web? 12
    13. 13. Web of Documents 13
    14. 14. from a Web of Documents to a Web of Data 14
    15. 15. Web of Data 15 Travel Data
    16. 16. Web of Data 16 Financial Data
    17. 17. Web of Data 17 Housing Data
    18. 18. But data integration is difficult 18
    19. 19. and is often ad-hoc 19
    20. 20. and there are other issues 20
    21. 21. Inconsistency 21
    22. 22. Inconsistency 22
    23. 23. Inconsistency 23
    24. 24. Different Naming 24#iswc2010 is #iswc
    25. 25. Different Naming 25
    26. 26. Inference 26 From: hotwire.com
    27. 27. Inference 27 From: travelocity.com Can this be automated? (Li Ding teaches me this trick)
    28. 28. What We Need • A standard data interchange format • A standard representation of the meaning of data • A standard way to link data 28
    29. 29. Semantic Web Languages 29 Source: W3C's Semantic Web Activity / Semantic Web overview http://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/#%2824%29 The Layer Cake
    30. 30. RDF = Resource Description Framework 30 affiliation affiliation knows
    31. 31. RDF 31 swrc:affiliation swrc:affiliation foaf:knows <http://www.cs.rpi.edu/~baojie> <http://www.rpi.edu> < http://www.cs.rpi.edu/~hendler> swrc:=http://swrc.ontoware.org/ontology# foaf:=http://xmlns.com/foaf/0.1/
    32. 32. RDF @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix swrc: <http://swrc.ontoware.org/ontology#> . @prefix foaf: <http://xmlns.com/foaf/0.1> . @prefix rpics: < http://www.cs.rpi.edu/~> . rpics:baojie swrc:affiliation <http://www.rpi.edu> . rpics:baojie foaf:knows rpics:hendler . rpics:hendler swrc:affiliation <http://www.rpi.edu> . 32
    33. 33. SPARQL= SPARQL Protocol And RDF Query Language A query language for RDF SELECT ?person ?org WHERE{ ?person foaf:knows rpics:hendler . ?person swrc:affiliation ?org . } (find all people (and their affiliations) who know Hendler) 33
    34. 34. OWL = Web Ontology Language • A much more powerful ontology language • Examples (informally) – If twitter:baojie and linkedin:baojie both use email baojie@cs.rpi.edu, then they belong to the same person. – If Westin hotel is in Palo Alto, and Palo Alto is in the Bay Area, then Westin hotel is in the Bay Area. • OWL 1 (2004), OWL 2 (2009) 34
    35. 35. How they work in the real world? 35
    36. 36. You may not be aware that there are already plenty of semantic data around. 36
    37. 37. BestBuy 37 http://www.bestbuy.com/site/The+Matrix+-+DVD/9316073.p?id=29857&skuId=9316073&st=9316073&lp=1&cp=1
    38. 38. BestBuy (GoodRelations) 38 http://products.semweb.bestbuy.com/products/9316073/semanticweb.rdf
    39. 39. Facebook 39
    40. 40. Facebook (Open Graph) 40
    41. 41. LinkedIn 41 http://www.linkedin.com/in/jiebao
    42. 42. LinkedIn (Microformat) 42 http://microformatique.com/optimus/?uri=http://www.linkedin.com/in/jiebao
    43. 43. SlideShare 43 http://www.slideshare.net/baojie_iowa/semantic-history-towards-modeling-and-publishing-changes-of-online-semantic-data
    44. 44. SlideShare (RDFa) 44http://www.w3.org/2007/08/pyRdfa/extract?uri=http://www.slideshare.net/baojie_iowa/semantic-history-towards-modeling-and-publishing- changes-of-online-semantic-data
    45. 45. IMDB 45 http://www.imdb.com/name/nm0000125/
    46. 46. IMDB (OG+Microformat) 46 http://www.w3.org/2007/08/pyRdfa/extract?uri=http://www.imdb.com/name/nm0000125/
    47. 47. Sig.ma (Data Aggregation) 47 http://sig.ma/search?q=Jie+Bao
    48. 48. Sig.ma 48 http://sig.ma/search?q=Jie+Bao
    49. 49. Data From Spreadsheet 49 Dominic DiFranzo and Li Ding - http://data-gov.tw.rpi.edu/wiki/Demo:_White_House_Visitor_Search
    50. 50. Data From Spreadsheet 50 6.46 billion RDF triples now.
    51. 51. Data From Relational DB 51 http://demo.openlinksw.com/about/html/http/demo.openlinksw.com/Northwind/Customer/ALFKI
    52. 52. 52 Many Many More
    53. 53. Then, how semantic data help us to build (killer) apps? 53
    54. 54. Semantic Twitter 54 Joshua Shinavier, TwitLogic SPARQL widget
    55. 55. Financial Data 55Perry Grossman, Devin Mcqueeney, Graham G Rong, Lorin Wilde, Danny Yuan, Jie Bao (coach). FinanceSphere, MIT LinkedData IAP 2010 Project
    56. 56. Financial Data 56 Bao, J., Rong, G., Li, X., and Ding, L. Representing Financial Reports on the Semantic Web - A Faithful Translation from XBRL to OWL. In The 4th International Web Rule Symposium (RuleML). 2010 XBRL= eXtensible Business Reporting Language
    57. 57. RPI Map http://map.rpi.edu Jie Bao , Jin Guang Zheng, Rui Huang & Li Ding. Mesh-up Map and Events on Semantic Wiki: Applications in e-Science and Campus Information System. SemanticWiki mini-series Session-4. Jan. 22, 2009. ontolog.cim3.net
    58. 58. Semantic Email 58
    59. 59. Data-gov Wiki Li Ding and James Michaelis and Deborah L. McGuinness and Jim Hendler, Making Sense of Open Government Data, in Proceedings of WebSci2010, 2010.
    60. 60. Data Mashup and Visualization 60DiFranzo, D.: Developer Diary: CASTNET Ozone Map Demo. In WebSci 2010 poster. http://data-gov.tw.rpi.edu/wiki/Demo:_Clean_Air_Status_and_Trends_-_Ozone
    61. 61. Data Mashup and Visualization 61James Michaelis: http://data-gov.tw.rpi.edu/wiki/Demo:_Comparing_US-USAID_and_UK-DFID_Global_Foreign_Aid
    62. 62. Where are we? 62
    63. 63. Where are we? 63 Picture source: Wikipedia (http://en.wikipedia.org/wiki/Technology_adoption_lifecycle) Adapted from “Semantic Web Adoption and Applications”, Ivan Herman, W3C. 2010-10-07 Slide 5 2005
    64. 64. Where are we? 64 Picture source: Wikipedia (http://en.wikipedia.org/wiki/Technology_adoption_lifecycle) Adapted from “Semantic Web Adoption and Applications”, Ivan Herman, W3C. 2010-10-07 Slide 5 2010
    65. 65. The 2007 Gartner predictions • By 2012, 80% of public Web sites will use some level of semantic hypertext to create SW documents […] 15% of public Web sites will use more extensive Semantic Web-based ontologies to create semantic databases • By 2017, we expect the vision of the Semantic Web […] to coalesce […] and the majority of Web pages are decorated with some form of semantic hypertext. 65“Finding and Exploiting Value in Semantic Web Technologies on the Web”, Gartner Report, May 2007
    66. 66. Imagine a world where data are linked and make sense 66
    67. 67. On ATM 67 You can check transactions by their categories, and the ATM knows that not all items from BestBuy are electronics (e.g., office supplies), since it is connected to the BestBuy product database.
    68. 68. On TV 68 It can generate a personalized program list of movies starred by Sean Connery, since it is connected to IMDB
    69. 69. In Your Car 69 Picture from: http://electronics.howstuffworks.com/gadgets/automotive/car-gps-accidents.htm/printable The in-car GPS tells you attractions of the revolutionary war era, since it can read a semantic version of Wikipedia and a geo-location database from the US government.
    70. 70. We are only limited by our imaginations 70
    71. 71. That’s why I believe the Semantic Web is a beautiful thing 71
    72. 72. Thank you! Slides are available @ http://slidesha.re/aimhRY 72

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