An Introduction to the Semantic Web
Will Strinz
The Internet Is Your New Database
What’s this all about then?
Today we have the World Wide Web
What’s this all about then?
Today we have the World Wide Web
What’s this all about then?
Its
Distributed
Accessible using all sorts of devices and software
Document Based
This is very...
What’s this all about then?
Database software is powerful but rarely interacted with
directly
Often accessed through the w...
Wat Do?
Move from a web of documents to a web of data
Needs to be
Structured, but still flexible
Distributed
Accessible to...
What is this Semantic Web Thing?
Represents information using Subject Predicate Object
Subject Predicate Object
Will Strin...
What is this Semantic Web Thing?
With URIs and typed literals
Subject Predicate Object
example.org/Will_Strinz example.org...
Example
Lets start with a resource, or “thing”
Example
Lets start with a resource, or “thing”
We’ll call it http://example.org/Fresh, or ex:Fresh for short
Example
What can we say about ex:Fresh?
S P O
ex:Fresh ex:enjoys “B-Ball”
ex:Fresh ex:aunt ex:Vivian_Banks
ex:aunt
ex:enjo...
Example
ex:Vivian_Banks is also a resource
ex:aunt
“B-Ball”
ex:Fresh ex:enjoys
ex:Vivian_Banks
S P O
ex:Fresh ex:enjoys “B...
Example
So now we can say things about her too!
S P O
ex:Fresh ex:enjoys “B-Ball”
ex:Fresh ex:aunt ex:Vivian_Banks
ex:Vivi...
Vocabularies
We’ve been defining our own predicates and objects so far
Could add details about each predicate
Isn’t this a...
FOAF Vocabulary
“Friend Of A Friend”
Located at http://xmlns.com/foaf/0.1/
foaf:name a rdf:Property,
owl:DatatypeProperty;...
Example
S P O
ex:Fresh
foaf:based_nea
r
ex:West_Philedelphia
ex:Fresh foaf:age 20
Will ‘The Fresh
ex:aunt
ex:enjoys “B-Bal...
Example
S P O
ex:Fresh
foaf:based_nea
r
ex:West_Philedelphia
ex:Fresh foaf:age 20
Will ‘The Fresh
ex:aunt
ex:enjoys “B-Bal...
Lets look at what we have
Human readable
Simple and flexible
Rigid when necessary
Atomic statements
Dual representation
Id...
Serialization
Multiple formats
All of which are
Standardized
Interoperable
Information preserving
File or Triple Store
Serialization
NTriples
<http://example.orgfresh> <http://xmlns.com/foaf/0.1/name> "Will 'The Fresh Prince' Smith" .
<http:...
Serialization
JSON-LD
{
"@context": { "ex": "http://example.org",
"foaf": "http://xmlns.com/foaf/0.1/" },
"@graph": [ { "@...
Serialization
RDF/XML
<?xml version='1.0' encoding='utf-8' ?>
<rdf:RDF xmlns:ex='http://example.org' xmlns:foaf='http://xm...
Serialization
Other Formats
TRiG/TRiX
RDFa
N3
NQuads
Mappings onto SQLite, Mongo, etc
Querying
What new language do I have to learn just to query
SPARQL!
But stick with me, its not so bad
Syntax similar to SQ...
Querying
How old is Will ‘The Fresh Prince’ Smith?
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
PREFIX ex: <http://example.or...
Querying
What is Will ‘The Fresh Prince’ Smith’s Aunt’s
nickname?
SELECT (?nick) WHERE {
ex:Fresh ex:aunt ?aunt .
?aunt ex...
Querying
What do we know about Will ‘The Fresh Prince’ Smith?
SELECT (?prop) WHERE {
ex:Fresh ?prop ?value .
}
=> foaf:nam...
Querying
• Update, Insert, and
Delete
• Logical / Regex filters
• Subqueries
• Order and Offset
• Aggregates
Many other fe...
Getting Connected
So, RDF has some cool features
• Flexible yet structured
• Atomic
• Graph Based
• W3C Backed
• Human Fri...
Getting Connected
Remember our ex:Fresh URI?
http://example.org/Fresh
Its not dereferencable.
What if instead we used
http...
Getting Connected
Suddenly we have more information
dbpedia:Will_Smith_(character) a yago:FictionalCharacter,
dbpedia-owl:...
Getting Connected
A lot more information
dbpedia-owl:abstract "William "Will" Smith (born July 3, 1973) is a fictional cha...
Getting Connected
dbpprop:first ""The Fresh Prince Project""@en;
dbpprop:hasPhotoCollection informatik:Will_Smith_(charact...
Getting Connected
Human AND Machine Readable
Getting Connected
DBPedia has a SPARQL Endpoint
Lots of fun queries
SELECT * WHERE {
?episode dc:subject dbpcategory:The_S...
Getting Connected
Larger goal of connecting the whole web
I have a dream for the Web [in which computers] become capable o...
http://dgallery.s3.amazonaws.com/lod-cloud_colored.png
Going Further
Templating with RDFa or XSLT
Ontologies / OWL
Reasoning
Libraries
Ruby-RDF
Spira
Publisci and Publisci Serve...
Disclaimers
Relatively young
Less engineering time
SPARQL changing and not fully implemented in all
triple stores
Flexibil...
End
Thanks Bendyconf Attendees and Organizers!
Questions?
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The Internet Is Your New Database: An Introduction To The Semantic Web

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The Internet Is Your New Database: An Introduction To The Semantic Web

  1. 1. An Introduction to the Semantic Web Will Strinz The Internet Is Your New Database
  2. 2. What’s this all about then? Today we have the World Wide Web
  3. 3. What’s this all about then? Today we have the World Wide Web
  4. 4. What’s this all about then? Its Distributed Accessible using all sorts of devices and software Document Based This is very flexible. But Hard to search Unstructured and context-less - hard to consume automatically Easy to share, hard to compose and remix Full of all sorts of ‘homebrew’ databases and ad-hoc schema
  5. 5. What’s this all about then? Database software is powerful but rarely interacted with directly Often accessed through the web, but indirectly Still ultimately siloed Hard to compose and remix What if the internet acted as one big distributed database?
  6. 6. Wat Do? Move from a web of documents to a web of data Needs to be Structured, but still flexible Distributed Accessible to machine and human alike
  7. 7. What is this Semantic Web Thing? Represents information using Subject Predicate Object Subject Predicate Object Will Strinz years old 24 Bendyworks a Company Will Strinz works at Bendyworks
  8. 8. What is this Semantic Web Thing? With URIs and typed literals Subject Predicate Object example.org/Will_Strinz example.org/years_old 24 example.org/Bendyworks example.org/is_a example.org/Company example.org/Will_Strinz example.org/works_for example.org/Bendyworks • Called Resource Description Format (RDF)
  9. 9. Example Lets start with a resource, or “thing”
  10. 10. Example Lets start with a resource, or “thing” We’ll call it http://example.org/Fresh, or ex:Fresh for short
  11. 11. Example What can we say about ex:Fresh? S P O ex:Fresh ex:enjoys “B-Ball” ex:Fresh ex:aunt ex:Vivian_Banks ex:aunt ex:enjoys ex:Vivian_Banks “B-Ball”ex:Fresh
  12. 12. Example ex:Vivian_Banks is also a resource ex:aunt “B-Ball” ex:Fresh ex:enjoys ex:Vivian_Banks S P O ex:Fresh ex:enjoys “B-Ball” ex:Fresh ex:aunt ex:Vivian_Banks
  13. 13. Example So now we can say things about her too! S P O ex:Fresh ex:enjoys “B-Ball” ex:Fresh ex:aunt ex:Vivian_Banks ex:Vivian_Banks ex:nickname “Aunt Viv” 1 ex:nickname “Aunt Viv” ex:aunt “B-Ball” ex:Fresh ex:enjoys ex:Vivian_Banks
  14. 14. Vocabularies We’ve been defining our own predicates and objects so far Could add details about each predicate Isn’t this a waste of time? Yes! Use RDF Vocabularies Define new namespaces, terms, and objects ‘Imported’ simply by reference Are described in RDF
  15. 15. FOAF Vocabulary “Friend Of A Friend” Located at http://xmlns.com/foaf/0.1/ foaf:name a rdf:Property, owl:DatatypeProperty; rdfs:label "name"; rdfs:comment "A name for some thing."; rdfs:domain owl:Thing; rdfs:isDefinedBy foaf:; rdfs:range rdfs:Literal; rdfs:subPropertyOf rdfs:label; sw_ns:term_status "testing" .
  16. 16. Example S P O ex:Fresh foaf:based_nea r ex:West_Philedelphia ex:Fresh foaf:age 20 Will ‘The Fresh ex:aunt ex:enjoys “B-Ball” ex:Vivian_Banks ex:Fresh ex:nickname “Aunt Viv” foaf:based_near ex:West_Philadelphia foaf:age 22 foaf:name “Will ‘The Fresh Prince’ Smith”
  17. 17. Example S P O ex:Fresh foaf:based_nea r ex:West_Philedelphia ex:Fresh foaf:age 20 Will ‘The Fresh ex:aunt ex:enjoys “B-Ball” ex:Vivian_Banks ex:Fresh ex:nickname “Aunt Viv” foaf:based_near ex:West_Philadelphia foaf:age 22 foaf:name “Will ‘The Fresh Prince’ Smith”
  18. 18. Lets look at what we have Human readable Simple and flexible Rigid when necessary Atomic statements Dual representation Ideally Dereferencable Structured, Machine understandable
  19. 19. Serialization Multiple formats All of which are Standardized Interoperable Information preserving File or Triple Store
  20. 20. Serialization NTriples <http://example.orgfresh> <http://xmlns.com/foaf/0.1/name> "Will 'The Fresh Prince' Smith" . <http://example.orgfresh> <http://example.orgenjoys> "B-Ball" . <http://example.orgfresh> <http://xmlns.com/foaf/0.1/age> "22"^^<http://www.w3.org/2001/XMLSchema#integer> . <http://example.orgfresh> <http://example.orgaunt> <http://example.orgVivian_Banks> . <http://example.orgfresh> <http://xmlns.com/foaf/0.1/based_near> <http://example.orgWest_Philadelphia> . <http://example.orgVivian_Banks> <http://example.orgnickname> "Aunt Viv" . Turtle @prefix ex: <http://example.org> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . ex:fresh foaf:name "Will 'The Fresh Prince' Smith" ; ex:enjoys "B-Ball" ; foaf:age 22 ; ex:aunt ex:Vivian_Banks ; foaf:based_near ex:West_Philadelphia . ex:Vivian_Banks ex:nickname "Aunt Viv" .
  21. 21. Serialization JSON-LD { "@context": { "ex": "http://example.org", "foaf": "http://xmlns.com/foaf/0.1/" }, "@graph": [ { "@id": "ex:Vivian_Banks", "ex:nickname": "Aunt Viv" }, { "@id": "ex:fresh", "ex:aunt": { "@id": "ex:Vivian_Banks" }, "ex:enjoys": "B-Ball", "foaf:age": { "@value": "22", "@type": "http://www.w3.org/2001/XMLSchema#integer" }, "foaf:based_near": { "@id": "ex:West_Philadelphia" }, "foaf:name": "Will 'The Fresh Prince' Smith" } ] }
  22. 22. Serialization RDF/XML <?xml version='1.0' encoding='utf-8' ?> <rdf:RDF xmlns:ex='http://example.org' xmlns:foaf='http://xmlns.com/foaf/0.1/' xmlns:rdf='http://www.w3.org/1999/02/22-rdf- syntax-ns#' xmlns:xsd='http://www.w3.org/2001/XMLSchema#'> <rdf:Description rdf:about='http://example.orgVivian_Banks'> <ex:nickname>Aunt Viv</ex:nickname> </rdf:Description> <rdf:Description rdf:about='http://example.orgfresh'> <ex:aunt rdf:resource='http://example.orgVivian_Banks' /> <ex:enjoys>B-Ball</ex:enjoys> <foaf:age rdf:datatype='http://www.w3.org/2001/XMLSchema#integer'>22</foaf:age> <foaf:based_near rdf:resource='http://example.orgWest_Philadelphia' /> <foaf:name>Will 'The Fresh Prince' Smith</foaf:name> </rdf:Description> </rdf:RDF>
  23. 23. Serialization Other Formats TRiG/TRiX RDFa N3 NQuads Mappings onto SQLite, Mongo, etc
  24. 24. Querying What new language do I have to learn just to query SPARQL! But stick with me, its not so bad Syntax similar to SQL, but joins are free! Much more consistent across endpoints and triple stores
  25. 25. Querying How old is Will ‘The Fresh Prince’ Smith? PREFIX foaf: <http://xmlns.com/foaf/0.1/> PREFIX ex: <http://example.org> SELECT (?age) WHERE { ex:Fresh foaf:age ?age } => 22
  26. 26. Querying What is Will ‘The Fresh Prince’ Smith’s Aunt’s nickname? SELECT (?nick) WHERE { ex:Fresh ex:aunt ?aunt . ?aunt ex:nickname ?nick . } => “Aunt Viv”
  27. 27. Querying What do we know about Will ‘The Fresh Prince’ Smith? SELECT (?prop) WHERE { ex:Fresh ?prop ?value . } => foaf:name, ex:enjoys, foaf:age, ex:aunt, foaf:based_near
  28. 28. Querying • Update, Insert, and Delete • Logical / Regex filters • Subqueries • Order and Offset • Aggregates Many other features in SPARQL • Data Types • Construct, Describe, and Ask modes • Order and Offset • Property Paths • Math functions
  29. 29. Getting Connected So, RDF has some cool features • Flexible yet structured • Atomic • Graph Based • W3C Backed • Human Friendly • Queryable • Serializable • Extensible And I can say things about Will Smith with it But how different is that really from any other database? Connections!
  30. 30. Getting Connected Remember our ex:Fresh URI? http://example.org/Fresh Its not dereferencable. What if instead we used http://dbpedia.org/resource/Will_Smith_(character)
  31. 31. Getting Connected Suddenly we have more information dbpedia:Will_Smith_(character) a yago:FictionalCharacter, dbpedia-owl:FictionalCharacter, yago:FictionalVersionsOfRealPeople, yago:ImaginaryBeing109483738, dbpedia-owl:Person, dbpedia-owl:Agent, yago:SitcomCharacters, owl:Thing, foaf:Person; rdfs:label "Will Smith (character)”@en;
  32. 32. Getting Connected A lot more information dbpedia-owl:abstract "William "Will" Smith (born July 3, 1973) is a fictional character in the NBC television series, The Fresh Prince of Bel-Air."@en; dbpedia-owl:birthDate "1973-07-02+02:00"^^xsd:date; dbpedia-owl:portrayer dbp:Will_Smith; dbpedia-owl:series dbp:The_Fresh_Prince_of_Bel-Air; dbpedia-owl:wikiPageExternalLink <http://www.imdb.com/character/ch0020905/>; dbpprop:born "1973-07-02+02:00"^^xsd:date; dbpprop:family "Janice Smith"@en, "Hilary Banks"@en, "Carlton Banks"@en, "Vy Smith-Wilkes"@en, "Lisa Wilkes"@en, "Lou Smith"@en, "Ashley Banks"@en, "Helen Smith"@en, "Fred Wilkes"@en, "Phillip Banks"@en, "Vivian Banks"@en;
  33. 33. Getting Connected dbpprop:first ""The Fresh Prince Project""@en; dbpprop:hasPhotoCollection informatik:Will_Smith_(character); dbpprop:name "Will Smith"@en; dbpprop:nicknames "Master William, Prince, Fresh Prince, Will"@en; dbpprop:portrayer dbp:Will_Smith; dbpprop:series dbp:The_Fresh_Prince_of_Bel-Air; dbpprop:wordnet_type wn:synset-character-noun-4; dcterms:subject category:Fictional_characters_introduced_in_1990, category:Fictional_African-American_people, category:Fictional_versions_of_real_people, dbpcategory:Fictional_characters_from_Philadelphia,_Pennsylvania, category:Sitcom_characters; rdfs:comment "William "Will" Smith (born July 3, 1973) is a fictional character in the NBC television series, The Fresh Prince of Bel-Air."@en; owl:sameAs <http://rdf.freebase.com/ns/m.0417_vv>, <http://yago-knowledge.org/resource/Will_Smith_(character)>, <http://dbpedia.org/resource/Will_Smith_(character)>; foaf:isPrimaryTopicOf <http://en.wikipedia.org/wiki/Will_Smith_(character)>; foaf:name "Will Smith"@en .
  34. 34. Getting Connected Human AND Machine Readable
  35. 35. Getting Connected DBPedia has a SPARQL Endpoint Lots of fun queries SELECT * WHERE { ?episode dc:subject dbpcategory:The_Simpsons_%28season_14%29_episodes ?episode dbpedia2:blackboard ?chalkboard_gag . }
  36. 36. Getting Connected Larger goal of connecting the whole web I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A "Semantic Web", which makes this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The "intelligent agents" people have touted for ages will finally materialize. — Sir Tim Berners-Lee (1999)
  37. 37. http://dgallery.s3.amazonaws.com/lod-cloud_colored.png
  38. 38. Going Further Templating with RDFa or XSLT Ontologies / OWL Reasoning Libraries Ruby-RDF Spira Publisci and Publisci Server Tools and interfaces - Build them!
  39. 39. Disclaimers Relatively young Less engineering time SPARQL changing and not fully implemented in all triple stores Flexibility has its downsides; Garbage in Garbage out No agreed upon method for schema constraints
  40. 40. End Thanks Bendyconf Attendees and Organizers! Questions?

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