SEO Meets Semantic Web - Saint Patrick's Day 2015-Meetup

©2015 Eric Axel Franzon

SEO Meets Semantic Web(Meets St. Patrick’s Day)

Welcome!


Eric FranzonManaging PartnerSemantic Fuse

A Roadmap for SEO Today and Tomorrow

SemanticWeb:


Semantic Webis like the harmonica


Easy to play


Easy to play; takes work to master.


What we’ll discuss

• What is Semantic Web?• Who’s using it?• What makes it work?


What Is Semantic Web?

• A Web-scale architecture• A metadata technology• A layer of meaning on the Web• In use TODAY!


What Is it Not?• A software package

• Something that will everbe “done”

• A replacement for thecurrent Web


What Is it Not?• Limited to the public WWW

• A pipe dream

• A silver bullet

• HAL 9000 or Skynet

©2015 Eric Axel FranzonIoT Enhancements by Eric Franzon

IoT


• Globally• Inexpensively• In Real-Time

(public)WorldWideWeb

HTTP

HTML

Based on W3C Standards



Behind the Firewall

(public)WorldWideWeb

HTTP

HTML




SemanticWeb

RDF

SPARQL

OWL




Behind the Firewall

SemanticWeb

RDF

SPARQL

OWL



• to connect DATA• to make information

interpretable by machines

Semantic Web Standardsare used…


Machine Interpretationas the Web Evolves…


Web 1.0 – Linking Documents


Web 1.0

“I see: characters + formatting + images”--my Computer


Web 1.0 – Linking DocumentsWeb 2.0 – Linking People


Web 2.0

“I see: characters + formatting + images”--my Computer


It’s hard to interpret meaning when all you see are characters,

images, and formatting.

Context is critical.


Web 1.0 – Linking DocumentsWeb 2.0 – Linking PeopleWeb 3.0 – Linking Data


Web 3.0 – Linking DataTitle

Price

Format

Cover

Band


Web 3.0 – Linking DataTitle

Price

Format

Cover

Band“I see: things + relationships. This is about a collection of music.”


Q: What does “Linked Data” have to do with Semantic Web?


A Quick word of disambiguation…

Semantic Web- A vision for a web of data

Semantic Web Standards- A specific set of standards

Linked Data- One application area of those

standards


Semantic WebStandards

SemanticWeb

LinkedOpenData


Semantic WebStandards

SemanticWeb

LinkedOpenData

LinkedData


Linking Open Data ProjectMay, 2007


September 2011


August 2014


Data from these trusted sourcesis available for you

to use in your applications TODAY.

Data you can LINK to.


Semantic Data that is machine READABLE.

…and machine INTERPRETABLE!


Who’s Using Semantic Web Standards?


• Healthcare / Life Sciences• Financial Services• Manufacturing / Retail• Marketing, Advertising• SEO/SEM• Libraries• Archives• Museums • Governments

Who’s Using Sem Web?


What it looks like


• Activities• Businesses• Groups• Organizations• People• Places• Products and Entertainment• Websites

Used to Describe


What it looks like


What it looks like<meta property='og:image' content="http://ia.media-imdb.com/images/M/MV5BMjA0MDYyNzczN15BMl5BanBnXkFtZTYwNjMzNjMz._V1_.jpg" />

<meta property='og:type' content="actor" /><meta property='fb:app_id' content='115109575169727' /><meta property='og:title' content="Peter O'Toole" /><meta property='og:site_name' content='IMDb' /><meta property="og:description" content="Peter O'Toole,

Actor: Lawrence of Arabia. A leading man of prodigious talents, Peter O'Toole was raised in Leeds, England, the son of Constance Jane Eliot (Ferguson), a Scottish nurse, and Patrick Joseph O'Toole, an Irish bookie. As a boy, he decided to become a journalist, beginning as a newspaper copy boy. Although he succeeded in becoming a reporter, he discovered the theater and made his stage debut at 17. He served as a radioman in ..." />


What is schema.org?

“…A collection of schemas, i.e., html tags, that webmasters can use to markup their pages in ways recognized by major search providers.”


e.g. Product Markup


What it looks like


e.g. TV Episode Markup


What it looks like


e.g. Company


What it looks like


Based on a sample of 12 billion web pages:

• ~5 million domains (6% of domains)

• 15 billion entities

• 65 billion triples

• 2.5 billion pages (~21% of pages)-Reported in an August 2014 SemTechBiz Keynote by R. V. Guha, Google Fellow

Schema.org Adoption


A work in progress


Growing Up• ~ 100 categories at launch in 2011• ~1200 by Sept. 2014

• Bibliographic Relationships & Periodicals (Sept. 2, 2014)

• Music, Video Games, Sports, breadcrumbs, itemList (Dec. 11, 2014)

• VisualArtwork, Invoices (Feb. 5, 2015)• Fixes to documentation, examples, &

general bugs (ongoing)


Growing Pains

• Immature tools for• Publishing• Parsing• Evaluating

• Lack of understanding/Misinformation


• Incorrect Signals being sent

• Global companies showing as local• Old data• Entities mismatched to concepts

Feeling the Pain


When it does work, though…


What makes SemWeb work?


The Technologies of SemWeb

• Data• Schemas• Query Language


The Data Language

ResourceDescriptionFramework


“RDF is good for distributing dataacross the Web and pretendingit’s in one place.”

-Dean Allemang, Author, Semantic Web for the Working Ontologist


• to connect DATA• to make it interpretable

by machines

RDF is used…

RDF is made up of triples!


1. By uniquely identifying THINGS2. By uniquely identifying RELATIONSHIPS3. By using TRIPLES

Machine Interpretable - How?


So, what’s a THING?

1. By uniquely identifying THINGS


A THING is anything that can be uniquely identified by a URI or a literal (string)

Me

My postal code

The White House

L.A. County’s sales tax rate

http://ericaxel.com/eric.rdf#me

http://www.city-data.com/zips/59801.html

Lat: 38.89859 Long: -77.035971

9.750 %

http://ericfranzon.com/harpcase.jpg


This is a collection of THINGS:

t_peopleName City State Post codeBill Carlsbad CA 92008Eric Missoula MT 59801


Who’s your daddy?

1. By uniquely identifying THINGS2. By uniquely identifying RELATIONSHIPS


Is Father of


Is Father ofhttp://ericaxel.com/eric.rdf#me


<owl:ObjectProperty rdf:ID="isFather"><rdfs:domain rdf:resource="#Person"/><rdfs:range rdf:resource="#Person"/>

</owl:ObjectProperty>

http://ericaxel.com/eric.rdf#mens:isFather


Is Father of







ns:isFather


1. By uniquely identifying THINGS2. By uniquely identifying RELATIONSHIPS3. By using TRIPLES

What’s a triple?


The Building block of RDF

The Triple


Triples? It’s Elementary! (School)

song has title.



song has title.

Relationship


Predicate


song has title.



song has title.

That is a Triple!


“This band recorded a song.”

“This recording is part of a collection.”

“This item has a barcode.”

“I like blues.”

“I like B.L.U.E.S.”

“This image can be used non-commercially.”

“My email address is [email protected].”

Triples? It’s Elementary!


Song Has Title “Title”

Eric Created Webpage

Image Has License CC Non-Commercial

Make AssertionsSu

bjec

ts

Obj

ects

Predicates


Song

Author Title

PublisherLyrics

A Simple Graph


The Trouble with Triples


Visualization of graph from Pharma space- Cytoscape.org


Where does one store triples?

In a “triple store”


Where does one store triples?

• Native Semantic Web stores• RDBMS databases• As native files (.rdf)• Woven into documents (RDFa)• Generated on the fly


Just so you know…There are many ways of representing RDF:

• RDF/XML• N3• JSON-LD• N-Triples

• Turtle• RDFa• Microdata• Microformats

Each has pros and cons, but they all connect THINGS and RELATIONSHIPS into TRIPLES


The Schemata

Linked Data schemas consist of:

Your RDF relationships (predicates)+

Relationship descriptions


SemWeb Schemata

id First Name Last Name

1 Barbara Starr

Schema

Data

Initial Schema

hasIDhasFirstName hasLastName

Barbara Starr1

owl:sameAs

hasSurname

Relationshipdescription


Choosing Relationships

• Reuse popular vocabularies– FOAF (Friend-of-a-friend)– Dublin Core (library/publisher metadata)– SIOC (Semantically-Interlinked Online

Communities)– Schema.org

• ...or make up your own!


1. Resource Description Framework Schema (RDFS): Simple, hierarchical classes

2. Simple Knowledge Organization System (SKOS): Port taxonomies to the Semantic Web

3. Web Ontology Language (OWL): Complex logical relationships

Relationship Descriptions


Worldcat.org

• A project of the OCLC


Vocabulary Combination “in the wild”


The query language

SPARQLProtocolAndRDFQueryLanguage

SPARQL


SPARQL allows us to:

• Pull values from structured & semi-structured data

• Explore data by querying unknown relationships

• Perform complex joins of disparate databases in a single, simple query

• Transform RDF data from one vocabulary to another

--Lee Feigenbaum, Cambridge Semantics


Eric


<hasDepiction>

Eric


<hasLicense>

<hasDepiction>

Eric


<hasLicense>

<hasDepiction>

<likes>

Eric


<hasLicense>

<hasDepiction>

<likes>

<likes>

<likes>

Eric


Chicago, Illinois

On the shores of Lake Michigan, Chicago is one of the major…

<hasLicense>

<wrote><hasDepiction>

<likes>

<likes>

<likes>

Eric

Bob


Chicago, Illinois


<hasLicense>

<wrote>

<isAbout>

<hasDepiction>

<likes>

<likes>

<likes>

Eric

Bob


Chicago, Illinois


<hasLicense>

<wrote>

<isAbout>

<livedIn>

<hasDepiction>

<likes>

<likes>

<likes>

Eric

Bob


Chicago, Illinois


<hasLicense>

<hasLicense> <wrote>

<isAbout>

<livedIn>

<hasDepiction>

<likes>

<likes>

<likes>

Eric

Bob


What can we ask of a system like this?


Chicago, Illinois


<hasLicense>


<isAbout>

<livedIn>

<hasDepiction>

<likes>

<likes>

<likes>

Bob

Eric


Chicago, Illinois


<hasLicense>


<isAbout>

<livedIn>

<hasDepiction>

<likes>

<likes>

<likes>

What does Eric Like?

Bob

Eric


Chicago, Illinois


<hasLicense>


<isAbout>

<livedIn>

<hasDepiction>

<likes>

<likes>

<likes>

What has a Creative Commons License?

Bob

Eric


Chicago, Illinois


<hasLicense>


<isAbout>

<livedIn>

<hasDepiction>

<likes>

<likes>

<likes>

What license does THIS document have?

Bob

Eric


Chicago, Illinois


<hasLicense>


<isAbout>

<livedIn>

<hasDepiction>

<likes>

<likes>

<likes>

What is liked by anyone who has lived somewhere that is the subject of a document Bob has written?

Bob

Eric


SPARQL Queries


SPARQL Example #1(specific endpoint – dbPedia)

Artists/Albums produced by PharrellPREFIX d: <http://dbpedia.org/ontology/>SELECT ?artistName ?albumNameWHERE {

?album d:producer :Pharrell_Williams .?album d:musicalArtist ?artist .?album rdfs:label ?albumName .?artist rdfs:label ?artistName .FILTER ( lang(?artistName) = "en" )FILTER (lang(?albumName) = "en" )

}


SPARQL Example #1



Musical artists who were born in or have a hometown in Irelandand the acts they performed with.



PREFIX dbo: <http://dbpedia.org/ontology/>

SELECT DISTINCT ?name ?person ?artist WHERE {?person foaf:name ?name .?person rdf:type <http://dbpedia.org/ontology/MusicalArtist> .?person <http://dbpedia.org/ontology/associatedMusicalArtist>

?artist .{?person dbo:hometown

<http://dbpedia.org/resource/Republic_of_Ireland> .}UNION {?person dbo:birthPlace

<http://dbpedia.org/resource/Republic_of_Ireland> .}

}ORDER BY ?name


SPARQL Example #2


SPARQL Example #2

A major retailer ran this query…

associated it with the catalog of albums it sells…

and delivered a set of recommended purchases for St. Patrick’s Day!


SPARQL Query #3

• Show me all landlocked countries• With populations > 50,000• Display the country names in English• Eliminate duplicates


SPARQL Query #3


PREFIX type: <http://dbpedia.org/class/yago/>PREFIX prop: <http://dbpedia.org/property/>SELECT ?country_name ?populationWHERE {

?country a type:LandlockedCountries ;rdfs:label ?country_name ;prop:populationEstimate ?population .

FILTER (?population > 15000000 && langMatches(lang(?country_name), "EN")) .} ORDER BY DESC(?population)


SPARQL Query #3 Results


SPARQL Query #3


PREFIX type: <http://dbpedia.org/class/yago/>PREFIX prop: <http://dbpedia.org/property/>SELECT ?country_name ?populationWHERE {

?country a type:LandlockedCountries ;rdfs:label ?country_name ;prop:populationEstimate ?population .

FILTER (?population > 15000000 && langMatches(lang(?country_name), "RU")) .} ORDER BY DESC(?population)


SPARQL Query #3 Results


• 8 KB text file with the .rdf extension• Hosted on my website• Information on me, my interests, and

people I know

My FOAF Profile


SPARQL Example #4(generic endpoint)

FOAF (some people that Eric Franzon knows)

PREFIX foaf: <http://xmlns.com/foaf/0.1/>SELECT ?nameFROM <http://ericaxel.com/eric.rdf>WHERE {

?knower foaf:knows ?known .?known foaf:name ?name .

}


SPARQL Example #4


Example #4 - Results


2 Disparate Data Sources:2 FOAF Profiles


SPARQL Example #5Querying two FOAF Profiles

PREFIX foaf: <http://xmlns.com/foaf/0.1/>PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>SELECT ?nameFROM <http://ericaxel.com/eric.rdf>FROM <http://bosatsu.net/foaf/brian.rdf>WHERE {

?x rdf:type foaf:Person .?x foaf:name ?name .

}


Where’s the Data?

What’sThe

Question?


Another Benefit of querying Linked Data…

Data link to other data!

SPARQL Example #6


1. Find these pieces of information:• Episode number• Airdate • Guest star • Chalkboard gag • Couch gag

2. Order them by Episode number

SPARQL Example #6


SPARQL Example #6Bart Simpson's Linked Data (DBPedia)

SELECT ?epnum ?airdate ?guest_star ?chalkboard_gag?couch_gag WHERE {?s dbpedia2:airdate ?airdate .?s dbpedia2:blackboard ?chalkboard_gag .?s dbpedia2:guestStar ?guest_star .?s dbpedia2:episodeNo ?epnum .?s dbpedia2:couchGag ?couch_gag .} order by ?epnum


SPARQL Example #6


Following the Trail…


One More Thing…


A little bit can be powerful!


Questions? Operators are standing by.

THANK YOU!

[email protected]@EricAxelhttp://linkedin.com/in/ericfranzonhttps://plus.google.com/+EricFranzon


• Semantic Markup Infusion• Semantic Data Fusion• Semantic SEO• Semantic Roadmap/Audit• Semantic Streamlining of Product Feeds/Catalogs• Semantic Consulting/Training• Semantic Interest Graph Generation


Resourceshttps://flic.kr/p/6krdsM

https://flic.kr/p/p9jiDK

https://flic.kr/p/3q8afL

https://flic.kr/p/brJs4G

https://flic.kr/p/78rsTc

https://flic.kr/p/bpSeR2

http://www.flickr.com/photos/dawnmanser/3532853278/

http://www.flickr.com/photos/artolog/3983764041/

http://www.flickr.com/photos/97964364@N00/59780745/

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

http://aldobucchi.com

http://www.addletters.com/pictures/bart-simpson-generator/3024046.htm

http://richard.cyganiak.de/2007/10/lod/

SEO Meets Semantic Web - Saint Patrick's Day 2015-Meetup

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