Using Semantics to Enhance Content Publishing

Post on 05-Dec-2014

4,965 views 0 download

description

Integrating the cloud into content. Web2.0 Expo NY 2009 Workshop

transcript

Integrating the Cloud into ContentUsing Semantics to Enhance Content Publishing

http://semprog.com/presentations/web20ny

Jamie Taylor

What do y'all mean"Semantics"

KNOCK

misfortune

bad luck

sound

occurrence

zing

vroomzizz

bump

knocking

bashbelt

bang

roast

critique

blow

rap whack

LJOMF

misfortune

bad luck

sound

occurrence

zing

vroomzizz

bump

knocking

bashbelt

bang

roast

critique

blow

rap whack

IBM

Head

qu

art

ers

CEO

Legal S

tructu

re

Operating Incom

e

Ticker Symbol

CIK

SIC

NAIC

Founders

Date Founded

Su

bsid

iari

es

So

ftware

Develo

ped

0000051143

NYSE:IBM

Sam Palmisano

17,604,000,000USD 2006

SANSF, ViaVoiceLotus Notes

CognosCross Worlds

334111:ElectronicComputer Manufacturing

3571:ElectronicComputers

1889

Thomas Watson

1 New Orchard RoadArmonk, New YorkPublicaly Listed

Company

IBM

Head

qu

art

ers

CEO

Legal S

tructu

re

Operating Incom

e

Ticker Symbol

CIK

SIC

NAIC

Founders

Date Founded

Su

bsid

iari

es

So

ftware

Develo

ped

0000051143

NYSE:IBM

Sam Palmisano

17,604,000,000USD 2006

SANSF, ViaVoiceLotus Notes

CognosCross Worlds

334111:ElectronicComputer Manufacturing

3571:ElectronicComputers

1889

Thomas Watson

1 New Orchard RoadArmonk, New YorkPublicaly Listed

Company

PageRanktm

0000051143

NYSE:IBM

Sam Palmisano

17,604,000,000USD 2006

SANSF, ViaVoiceLotus Notes

CognosCross Worlds

334111:ElectronicComputer Manufacturing

3571:ElectronicComputers

1889

Thomas Watson

1 New Orchard RoadArmonk, New YorkPublicaly Listed

Company

Earlier this year, the AP slashed prices to try to hold on to subscribers.

That's not the answer, says Jeff Jarvis, journalism professor at City University of New York.

JEFF JARVIS: The fundamentals of the media economy are changing, from a content economy to a link-based economy.

Jarvis says the AP needs to become the broker for those links, like helping the Baltimore Sun link to a story about GM from the Detroit Free Press.

http://www.flickr.com/photos/pagedooley/

Jarvis resorts to the concept of a "gift economy" to explain the link economy

I am a behavioral economist.

Gift economics are frequently used as explanations for what we don't understand

Worse I am a Behaviorist

Only talk about what you can observe

Semantics

Process of communicating enough meaning to result in an action

Link Economy

• Enriching links focuses meaning• Improves "findability" (SEO)

• Increased usability

• Better ad selection

Link Economy

• Semantics Benefit• Site owners

• Site users

• Developers

• You

At the end of this talk - you should be able to say how semantics benefits each of these groups

Wish it were real

Might be real

Is real, but don't believe it

Is very useful

Build Flexible Applications with

Graph Data

Not Your TypicalSemantic Web Talk

The Caketaken from http://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/layerCake-4.png

The W3C Layer Cake

Ontologies

<http://rdf.freebase.com/ns/guid.9202a8c04000641f8000000005b7ab1a> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://rdf.freebase.com/ns/business.employment_tenure>.<http://rdf.freebase.com/ns/guid.9202a8c04000641f8000000005b7ab1a> <http://rdf.freebase.com/ns/business.employment_tenure.company> <http://rdf.freebase.com/ns/en.determine_software>.<http://rdf.freebase.com/ns/guid.9202a8c04000641f8000000007e53e16> <http://rdf.freebase.com/ns/education.education.institution> <http://rdf.freebase.com/ns/en.mounds_view_high_school>.<http://rdf.freebase.com/ns/guid.9202a8c04000641f8000000007e53e16> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://rdf.freebase.com/ns/education.education>.<http://rdf.freebase.com/ns/guid.9202a8c04000641f8000000007e53e16> <http://rdf.freebase.com/ns/education.education.student> <http://rdf.freebase.com/ns/en.jamie_taylor>.<http://rdf.freebase.com/ns/en.jamie_taylor> <http://rdf.freebase.com/ns/business.company_founder.companies_founded> <http://rdf.freebase.com/ns/en.mobius_net>.<http://rdf.freebase.com/ns/en.jamie_taylor> <http://creativecommons.org/ns#attributionName> "Source: Freebase - The World's database".<http://rdf.freebase.com/ns/en.jamie_taylor> <http://rdf.freebase.com/ns/people.person.nationality> <http://rdf.freebase.com/ns/en.united_states>.<http://rdf.freebase.com/ns/en.jamie_taylor> <http://rdf.freebase.com/ns/common.topic.image> <http://rdf.freebase.com/ns/en.jamie_headshot>.<http://rdf.freebase.com/ns/en.jamie_taylor> <http://rdf.freebase.com/ns/type.object.name> "Jamie Taylor"@en.<http://rdf.freebase.com/ns/en.jamie_taylor> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://rdf.freebase.com/ns/user.skud.freebase_events.tshirt_recipient>.<http://rdf.freebase.com/ns/en.jamie_taylor> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://rdf.freebase.com/ns/user.skud.freebase_events.topic>.<http://rdf.freebase.com/ns/en.jamie_taylor> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://rdf.freebase.com/ns/book.author>.<http://rdf.freebase.com/ns/en.jamie_taylor> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://rdf.freebase.com/ns/people.person>.

RDF Serialization Formats

Instead....

• Part I• Why

• Uses, Benefits

• Part II• How

• Representation, Concepts

Part I- so you can explain to other

Part II- so you can do what you say

Part IWhy

Is very useful

Build Flexible Applications with

Graph Data

Graph Data Model

John Krasinski

Person, Actor

The Office (US)TV Program

stars in starred in

Leatherheads

Film

Brown UniversityCollege/university

attended

A socially managed semantic database

Freebase has Many Types of Things

9,547,107 Topics

government position held

topic:United States

Senator

topic:Barack Obama

Freebase

topic:UBS AG

took money from

topic:Switzerland

is based in

Contributions over $50000 made to members of the US congress in the 2008 election cycle by companies

headquartered outside of the United States

Industry Browser Identity Model

Industry (USCB)NAICS

Industry (SEC)SIC

NAICS/SIC MapFreebase

CompanyCIKSEC

PeopleCIKSEC

PersonWikipediaFreebase

CompanyCRP IDCRP

DonationsCRP IDCRP

LocationZIP Code

Freebase

CompanyTicker

SEC

Article

Wikipedia

Industry Browser

http://kiwitobes.com/industry_mashup/

Web 2.0 + Semantics

Barriers between science and the humanities impede solving humanities important problems

"Smoov"Ankolekar et al.2007

Patrick Sinclair (BBC)

About the Content (and visitor?)

MIT Simile

Simile

http://dev.mqlx.com/~jamie/simile/timeline.html

Data Portability

Data

Data

Data

Data

Semantics allows data to be utilized by unanticipated new applications

Simile

MIT Simile: Exhibit

User Experience

Topic Hubs

Open Calais

Open Calais

<rdf:Description rdf:nodeID="A1"> <att:lastupdated>2009-06-18T21:22:28</att:lastupdated> <att:text>IBM Corporation And Siemens Announce Integrated Solutions To Help Companies</att:text> </rdf:Description> <rdf:Description rdf:nodeID="A2"> <att:code>3577</att:code> <att:description>Computer Periph'L Equipment, Nec</att:description> </rdf:Description> <rdf:Description rdf:nodeID="A3"> <att:code>7371</att:code> <att:description>Computer Programming Services</att:description> </rdf:Description> <rdf:Description rdf:nodeID="A4"> <att:age>46</att:age> <att:lastname>Iwata</att:lastname> <att:officerurl rdf:resource="http://www.reuters.com/finance/stocks/officerProfile?symbol=IBM.N&amp;officerId=222727"/> <att:firstname>Jon</att:firstname> <att:title>Senior Vice President - Marketing and Communications</att:title> <att:middle>C.</att:middle> </rdf:Description>

http://p.opencalais.com/er/company/ralg-tr1r/9e3f6c34-aa6b-3a3b-b221-a07aa7933633

Open Calais

Herman Tolentino et al. http://epispider.net/index.php

Epispider

guardian.co.uk Open Platform

Chris Thorpe

Vocabulary

Do you understand the words that are coming out of my mouth?

-Chris Tucker, Rush Hour

Head

qu

art

ers

CEO

Legal S

tructu

re

Operating Incom

e

Ticker Symbol

CIK

SIC

NAIC

Founders

Date Founded

Su

bsid

iari

es

So

ftware

Develo

ped

0000051143

NYSE:IBM

Sam Palmisano

17,604,000,000USD 2006

SANSF, ViaVoiceLotus Notes

CognosCross Worlds

334111:ElectronicComputer Manufacturing

3571:ElectronicComputers

1889

Thomas Watson

1 New Orchard RoadArmonk, New YorkPublicaly Listed

Company

Herman Tolentino et al. http://epispider.net/index.php

Epispider

vocabularies...are everywhere

The Twitter Vocabulary

@

#Short URLs

Pivot on an @ tag

Pivot on a # tag

Vocabularies make links more understandable

...and thus content more findable

microformats

Annotate existing HTML so the content can be "extracted by software and indexed, searched for, saved, cross-referenced or combined. "

microformats

microformats<div class="vcard">..... <div id="view"> <div id="home">

<table> <tr> <td class="f">address</td> <td class="v"> <div class="adr"> <span class="locality">Berkeley</span>, <span class="region">CA</span> <div class="country-name">United States</div>

</div> </td> </tr> <tr> <td class="f">aim</td> <td class="v"><a id="aim" class="url im offline" href="aim:goim?screenname=jaredhanson@mac.com">jaredhanson@mac.com</a></td> </tr>

microformats.org

microformats

•(Relatively) easy to use

•Small, fixed vocabulary

•No standard parsing pattern

•No strong identifiers

• Limits utility

RDFa

Annotate HTML with machine readable RDF

RDFa

•Unambiguous identifiers

•Extensible vocabulary

•Standard parsing pattern

• Produces RDF

•Hard to use

• Rules about formatting based on RDF

What “concepts” are covered in content

Like existing tagging,

but with strong identifiers!<resource>

Tag

tagged

meanslabel

<resource>"text"

taggingDate "2001-01-01"

Strong identifier goes here!

<div class="rdfa" xmlns:ctag="http://commontag.org/ns#">

NASA's

<a typeof="ctag:Tag"

rel="ctag:means"

href="http://rdf.freebase.com/ns/en.phoenix_mars_mission"

property="ctag:label">Phoenix Mars Lander</a>

has deployed its robotic arm.

</div>

<resource>

Tag

tagged

meanslabel

<resource>"text"

taggingDate "2001-01-01"

And the winner is....

HTML5 MicroData

• Annotate HTML with machine readable data

• Simple Name-Value Pair design

HTML5 MicroData

Sometimes, it is desirable to annotate content with specific machine-readable labels, e.g. to allow generic scripts to provide services that are customised to the page, or to enable content from a variety of cooperating authors to be processed by a single script in a consistent manner.

HTML5

Simple! 15 pages of 657 page spec

HTML5 MicroData

<section itemscope itemtype="http://example.org/animals#cat" itemid="http://semprog.com/jamiestuff/hedral">

<h1 itemprop="name">Hedral</h1> <p itemprop="desc">Hedral is a male american domestic

shorthair, that is <span itemprop="http://example.com/color">black</span> and <span itemprop="http://example.com/color">white</span>.</p>

<img itemprop="img" src="hedral.jpeg" alt="" title="Hedral, age 18 months">

</section>

MicroData Widgets

HTML5 MicroData

• Easy to use

• Strong identifiers

• Extensible vocabulary

• Easy to parse

• In last call for comments stage!• Usable! Now!

Vocabulary Powered SearchSearch Applications:- Enhanced results- Info Bar

<div class="hReview-aggregate"><div class="item vcard"> <h1 class="fn org">Taylor&#39;s Automatic Refresher</h1> <div class=rating>

<img class="stars_3_half rating average" width="83" height="325" title="3.5 star rating" alt="3.5 star rating"

src="http://static1.px.yelp.com/static/2843250757/i/new/ico/stars/stars_map.png"/></div> <em>based on <span class="count">888</span> reviews</em>

</div>

<div id="bizInfoContent"> <p id="bizCategories">Category: <span id="cat_display"><a href="/c/sf/burgers">Burgers</a> </span><address class="adr"> Neighborhood: Embarcadero<br/>

<span class="street-address">1 Ferry Bldg<br />Marketplace Shop #6</span><br /><span class="locality">San Francisco</span>, <span class="region">CA</span> <span class="postal-code">94111</span><br />

</address><span id="bizPhone" class="tel">(866) 328-3663</span>

<div class="hReview-aggregate"><div class="item vcard"> <h1 class="fn org">Taylor&#39;s Automatic Refresher</h1> <div class=rating>

<img class="stars_3_half rating average" width="83" height="325" title="3.5 star rating" alt="3.5 star rating" src="http://static1.px.yelp.com/static/2843250757/i/new/ico/stars/stars_map.png"/></div>

<em>based on <span class="count">888</span> reviews</em></div>

<div id="bizInfoContent"> <p id="bizCategories">Category: <span id="cat_display"><a href="/c/sf/burgers">Burgers</a> </span><address class="adr"> Neighborhood: Embarcadero<br/>

<span class="street-address">1 Ferry Bldg<br />Marketplace Shop #6</span><br /><span class="locality">San Francisco</span>, <span class="region">CA</span> <span class="postal-code">94111</span><br />

</address><span id="bizPhone" class="tel">(866) 328-3663</span>

Search Monkey Vocabulary

Search Monkey Vocabulary

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"><rdf:Description rdf:about="http://dbpedia.org/ontology/areaTotal"><rdfs:domain rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:nodeID="b29203"><rdf:first rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:about="http://dbpedia.org/ontology/Place/nickname"><rdfs:domain rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:about="http://dbpedia.org/ontology/Place/location"><rdfs:range rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:about="http://dbpedia.org/ontology/maximumDepth"><rdfs:domain rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:about="http://dbpedia.org/ontology/Place/maximumElevation"><rdfs:domain rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:nodeID="b29250"><rdf:first rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:about="http://dbpedia.org/ontology/nearestCity"><rdfs:domain rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:about="http://dbpedia.org/ontology/PopulatedPlace"><rdfs:subClassOf rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:about="http://dbpedia.org/ontology/Place/maximumDepth"><rdfs:domain rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:about="http://dbpedia.org/ontology/Place/location"><rdfs:domain rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description><rdf:Description rdf:nodeID="b29225"><rdf:first rdf:resource="http://dbpedia.org/ontology/Place"/></rdf:Description>

DBPedia Place Vocabulary

Rich Snippet Vocabulary

http://data-vocabulary.org

• name • affiliation • nickname • price • postal-code • dtReviewed• photo • country-name• locality• reviewer• region• count• address• itemReviewed• title• brand• category• role

<rdf:Property rdf:ID="affiliation"> <rdfs:comment>An affiliation can be specified by a string literal or an Organization instance.</rdfs:comment> <rdfs:domain rdf:resource="#Person"/> <rdfs:range> <owl:Class> <owl:unionOf rdf:parseType="Collection"> <owl:Class rdf:about="#Organization"/> <owl:Class rdf:about="xsd:string"/> </owl:unionOf> </owl:Class> </rdfs:range></rdf:Property>

<rdf:Property rdf:ID="brand"> <rdfs:domain rdf:resource="#Product"/></rdf:Property>

<rdf:Property rdf:ID="category"> <rdfs:domain> <owl:Class> <owl:unionOf rdf:parseType="Collection"> <owl:Class rdf:about="#Organization"/> <owl:Class rdf:about="#Product"/> </owl:unionOf> </owl:Class> </rdfs:domain></rdf:Property>

Rich Snippet Vocabulary

HTML5 Vocabularies

Vocab Hubhttp://microdata.freebaseapps.com/

Part IIHow

(or why we wrote the book)

Rich Graph Data

John Krasinski

Person, Actor

The Office (US)TV Program

stars in starred in

Leatherheads

Film

Brown UniversityCollege/university

attended

Connected to other rich sources

Where does your data live?

Traditional data-modeling

The beloved spreadsheet

Restaurant Address Cuisine Price OpenDeli Lllama Peachtree Rd Deli $ Mon, Tue, Wed, Thu, FriPeking Inn Lake St Chinese $$$ Thur, Fri, SatThai Tanic Branch Dr Thai $$ Tue, Wed, Thu, Fri, Sat, Sun

Lord of the Fries Flower Ave Fast food $$ Tue, Wed, Thu, Fri, Sat, SunMarquis de Salade Main St French $$$ Thur, Fri, Sat

Wok this way Second St Chinese $ Mon, Tue, Wed, Thu, Fri, Sat, SunLuna Sea Autumn Dr Seafood $$$ Tue, Thu, Fri, SatPita Pan Thunder Rd Middle Eastern $$ Mon, Tue, Wed, Thu, Fri, Sat, Sun

Award Weiners Dorfold Mews Fast food $ Mon, Tue, Wed, Thu, Fri, SatLettuce Eat Rustic Parkway Deli $$ Mon, Tue, Wed, Thu, Fri

Tabular data

Too much information, not enough cells

Restaurant Address Cuisine Price Open

Deli Lllama Peachtree Rd Deli $ Mon (11a-4p), Tue (11-4), Wed (11-4), Thu (11-7), Fri (11-8)

Peking Inn Lake St Chinese $$$ Thur (5p-10p), Fri (5p-1a), Sat (5p-1a)

etc…

Tabular Data

Allows for simple queries

Restaurantidnameaddresscuisine_id

Hoursrestaurant_iddayopenclose

Cuisineidname

A simple schema

Filled with data

id name address price

1 Deli Lllama Peachtree Rd

$

2 Peking Inn Lake St $$$

...

restaurant_id day open close1 Mon 11 161 Tue 11 161 Thu 11 192 Fri 5 23...

A simple schema

This doesn’t fit into our schema...

Bar Address DJ Best Drink

The Bitter End 14th Ave No Beer

Peking Inn Lake St No Scorpion Bowl

Hammer Time Wildcat Dr Yes Hennessey

Marquis de Salade Main St Yes Martini

Some new data

Maybe ok now, but can’t this keep happening?

Restaurant Address Price DJ Best DrinkDeli Lllama Peachtree Rd $Peking Inn Lake St $$$ No Scorpion BowlThai Tanic Branch Dr $$

Lord of the Fries Flower Ave $$Marquis de Salade Main St $$$ Yes Martini

Wok this way Second St $Luna Sea Autumn Dr $$$Pita Pan Thunder Rd $$

Award Weiners Dorfold Mews $Lettuce Eat Rustic Parkway $$

Hammer Time Wildcat Dr Yes HennesseyThe Bitter End 14th St No Beer

Half-empty columns

But now the information is duplicated :(

Restaurantidnameaddresscuisine_id

RB_Linkrestaurant_idbar_id

Baridnamedjbest_drink

Link the tables

Better, but now we have to “migrate”

Venueidnameaddress

Hoursvenue_iddayopenclose

Restaurantidvenue_idcuisine_id

Baridvenue_iddjbest_drink

Split place / purpose

A small section of a limited product

Large schemas

Does this look familiar?

Venueidnameaddress

Propertiesvenue_idfield_idvalue

fieldidname

A flexible schema

simple enough...

id name address

1 Deli Lllama Peachtree Rd

2 Peking Inn Lake St

...

venue_id field_id value

1 1 Deli

1 2 $

2 1 Chinese

2 2 $$$

2 3 Scorpion Bowl

2 4 No

id name1 Cuisine2 Price3 Specialty Cocktail4 DJ?

Add some data

No schema change required

id name address

1 Deli Lllama Peachtree Rd

2 Peking Inn Lake St

3 Thai Tanic Branch Dr

venue_id field_id value1 1 Deli1 2 $2 1 Chinese2 2 $$$2 3 Scorpion Bowl2 4 No3 5 Yes3 6 Jazz

id name1 Cuisine2 Price3 Specialty Cocktail4 DJ?5 Live Music6 Music Genre

Add live music info

Explicit semantics

Remember this from grammar class?

subject predicate object

The basic data unit

Machine readable and almost human readable

subject predicate objectS1 cuisine “Deli”S1 price “$”S1 name “Deli Llama”S2 cuisine “Chinese”S2 price “$”S2 name “Peking Inn”S2 best drink “Scorpion Bowl”S2 address “Lake St”S2 DJ? “No”S4 name “Fendalton”S4 contained-by S5S5 name “Christchurch”S1 location S4S6 name “Downtown”S6 contained-by S7S7 name “Wellington, NZ”S2 location S6

Restaurants as triples

...or as a graph

Deli Liiama

$

DeliS1Cuisine

Price

Name

Restaurant Graph

Deli Liiama

Christchurch

Fendalton

$

DeliS1

S4

Cuisine

Price

Name

Name

Contained-by

Location

Peking Inn

Name

S2

Location

Chinese

Cuisine

Extending The Restaurant Model

Deli Liiama

Christchurch

Fendalton

$

DeliS1

S4

Cuisine

Price

Name

Name

Contained-by

Location

Live DJ

Music

Urban ChicDecor

Integrating Graph Data Models

Deli Liiama

$

DeliS1Cuisine

Price

Name

OnTap

LeinenkugelZ6

Pabst BRBrand

Brand

Deli Liiama

A2

Name

What Went Wrong?

Things change

Requirements change

User expectations change

Data structures change

Our data models aren’t keeping up

Scripting Languagesfacilitate change

....where is the data model that does the same?

Semantic Representation

Relationships are represented explicitly

Schema can be represented as a graph

Data integration is the union of two graphs

This makes creating, extending, and combining data much easier than before

Just enough RDF

Just Enough RDF

RDF is a Data Model

A very simple model!

Cosmos was written by Carl Sagan

Subject ObjectPredicate

(Cosmos) (was written by) (Carl Sagan)

authorCosmosCarl

Sagan

(Cosmos)

Subject Which Cosmos?

(Cosmos)

Subject Which Cosmos?

Identifiers are Everywhere

#w2e

The humble URI

•URI’s provide strong references

•Much like pointing in the physical world

“this is red”“this is a pen”

•a URIref is an unambiguous pointer to something of meaning

(Cosmos)

Subject

http://rdf.freebase.com/ns/authority.openlibrary.book.OL3568862M

Which Cosmos?

authorCosmosCarl

Sagan

http://rdf.freebase.com/ns/book.written_work.author

What do you mean, author?

vocabulary

authorCosmos

There are billions of Carl Sagans...http://rdf.freebase.com/ns/en.carl_sagan

authorCosmosCarl

Sagan

published “1980”

RDF Data Model

Nodes (“Subjects”)

connect via Links (“Predicates”)

to Objects• either Nodes or Literals

Expressions of RDF

RDF has many (inconvenient) serializations

•RDF-XML•N3

•Turtle•NTriples

•RDFa

URIs provide identityhttp://rdf.freebase.com/ns/en.robert_cook

Stability

Simplicity

Manageability

Not all URL’s are good identifiers

Data

Data

Data

Data

Semantics allows an application to utilize unanticipated new data sources

Plugable Data

Plugable Data

Data Portability

Data

Data

Data

Data

Semantics allows data to be utilized by unanticipated new applications

Data Portability

http://dev.mqlx.com/~jamie/simile/timeline.html

Data Portability

Semantics facilitate shared meaning through

• Subject Identity

• Strong and Consistent Semantics

• Open APIS + Open Data

These principles make it much easier to extend, combine, and integrate data

Why Does This Work?

RDF Graphs

CarrieFisher

Star Wars

Harrison Ford

Blade Runner

Daryl Hannah

Starred In

Starred In

Starred In

Starred In

Triple Stores(aka Graph Stores)

Allegro Graph

Keep your data as flexible as the source

+

+

Strong Identifiers

Strong Semantics(strong vocabularies)

Open Data

Can describe?!

• Semantics Benefit• Site owners

• Site users

• Developers

• You

At the end of this talk - you should be able to say how semantics benefits each of these groups