semantic web: in quest for the next generation killer apps

Semantic Web: In Quest for the Next

Generation Killer Apps

Jie BaoTetherless World ConstellationRensselaer Polytechnic Institutebaojie@cs.rpi.eduhttp://www.cs.rpi.edu/~baojie

Oct 22nd, 2010 @ UMass Lowell 1

Outline

• Why Semantic Web?

• Key SW Standards

• Opening Data for SW

• Building SW Applications

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What is a Killer App ?

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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

Visicalc

5

Excel

6

Netscape

7

Facebook

8

Web Itself

9Sir Tim Berners-Lee

As an app of the Internet

Picture Source: http://commons.wikimedia.org/wiki/File:InternetProtocolStack.png

ATM

10A killer app of database and network technologies

Picture source: http://en.wikipedia.org/wiki/File:ATM_750x1300.jpg

Where are the killer apps for the Semantic Web?

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What is Semantic Web?

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Web of Documents

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from a

Web of Documents

to a

Web of Data

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Web of Data

15Travel Data

Web of Data

16Financial Data

Web of Data

17Housing Data

But data integration is difficult

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and is often ad-hoc

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and there are other issues

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Inconsistency

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Inconsistency

22

Inconsistency

23

Different Naming

24#iswc2010 is #iswc

Different Naming

25

Inference

26

From: hotwire.com

Inference

27From: travelocity.com

Can this be automated?

(Li Ding teaches me this trick)

What We Need

• A standard data interchange format

• A standard representation of the meaning of data

• A standard way to link data

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Semantic Web Languages

29Source: W3C's Semantic Web Activity / Semantic Web overviewhttp://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/#%2824%29

The Layer Cake

RDF = Resource Description Framework

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affiliation

affiliation

knows

RDF

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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/

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> .

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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)

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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)

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How they work in the real world?

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You may not be aware that there are already plenty of semantic data around.

36

BestBuy

37http://www.bestbuy.com/site/The+Matrix+-+DVD/9316073.p?id=29857&skuId=9316073&st=9316073&lp=1&cp=1

BestBuy (GoodRelations)

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http://products.semweb.bestbuy.com/products/9316073/semanticweb.rdf

Facebook

39

Facebook (Open Graph)

40

LinkedIn

41

http://www.linkedin.com/in/jiebao

LinkedIn (Microformat)

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http://microformatique.com/optimus/?uri=http://www.linkedin.com/in/jiebao

SlideShare

43

http://www.slideshare.net/baojie_iowa/semantic-history-towards-modeling-and-publishing-changes-of-online-semantic-data

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

IMDB

45http://www.imdb.com/name/nm0000125/

IMDB (OG+Microformat)

46

http://www.w3.org/2007/08/pyRdfa/extract?uri=http://www.imdb.com/name/nm0000125/

Sig.ma (Data Aggregation)

47

http://sig.ma/search?q=Jie+Bao

Sig.ma

48

http://sig.ma/search?q=Jie+Bao

Data From Spreadsheet

49Dominic DiFranzo and Li Ding - http://data-gov.tw.rpi.edu/wiki/Demo:_White_House_Visitor_Search

Data From Spreadsheet

506.46 billion RDF triples now.

Data From Relational DB

51

http://demo.openlinksw.com/about/html/http/demo.openlinksw.com/Northwind/Customer/ALFKI

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Many Many More

Then, how semantic data help us to build (killer) apps?

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Semantic Twitter

54Joshua Shinavier, TwitLogic SPARQL widget

Financial Data

55Perry Grossman, Devin Mcqueeney, Graham G Rong, Lorin Wilde, Danny Yuan, Jie Bao (coach). FinanceSphere, MIT LinkedData IAP 2010 Project

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

RPI Map

http://map.rpi.eduJie 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

Semantic Email

58

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.

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

Data Mashup and Visualization

61James Michaelis: http://data-gov.tw.rpi.edu/wiki/Demo:_Comparing_US-USAID_and_UK-DFID_Global_Foreign_Aid

Where are we?

62

Where are we?

63Picture 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

Where are we?

64Picture 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

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

Imagine a world where data are linked and make sense

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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.

On TV

68It can generate a personalized program list of movies starred by Sean Connery, since it is connected to IMDB

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.

We are only limited by our imaginations

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That’s why I believe the Semantic Web is a beautiful thing

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Thank you!

Slides are available @ http://slidesha.re/aimhRY

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