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Introduction to the Semantic Web @arnoutboks Arnout Boks #phpce17 04 nov 2017

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@arnoutboks #phpce17 What this talk is NOT about…

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@arnoutboks #phpce17 Finding info on the web An example

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@arnoutboks #phpce17 “Web 1.0”

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@arnoutboks #phpce17 “Web 1.0”

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@arnoutboks #phpce17 “Web 1.0”

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@arnoutboks #phpce17 Web 1.0 Web of Documents for human consumption

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@arnoutboks #phpce17 “Web 2.0” Feed of events • iCalendar or vCalendar? • Different types of events?

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@arnoutboks #phpce17 “Web 2.0” Weather forecast API • XML or JSON? • Which fields and properties? • Which units?

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@arnoutboks #phpce17 Web 2.0 Web of (individual) API’s for consumption by specialized software

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@arnoutboks #phpce17 Semantic web • Question to agent (e.g. Siri) • Agent searches across different sources • Agent combines data • Agent answers question

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@arnoutboks #phpce17 Semantic Web (“Web 3.0”?) Web of Linked Data for consumption by intelligent agents/PA’s

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@arnoutboks #phpce17 Revolutionary? Term coined by Tim Berners-Lee in 2001

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@arnoutboks #phpce17 Revolutionary? Based on W3C-standards • RDF (1998) • RDFS (1998) • SPARQL (2008) • OWL (2004) • …

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@arnoutboks #phpce17 RDF Cornerstone of the Semantic Web Resource Description Framework Cornerstone of the Semantic Web

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@arnoutboks #phpce17 Records statements about things

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@arnoutboks #phpce17 RDF allows reading, merging, relaying and inferring statements without fully understanding them

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@arnoutboks #phpce17 RDF (triples) Subject Predicate Object

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@arnoutboks #phpce17 RDF (triples) Subject Predicate Object Arnout worksAt Moxio

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@arnoutboks #phpce17 RDF (triples) Subject Predicate Object Arnout worksAt Moxio Arnout twitterHandle “@arnoutboks” Arnout livesIn Delft Delft cityIn The Netherlands Moxio basedIn Delft

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@arnoutboks #phpce17 RDF (graph) Arnout Moxio Delft @arnoutboks worksAt basedIn The Netherlands Subject Predicate Object Arnout worksAt Moxio Arnout twitterHandle “@arnoutboks” Arnout livesIn Delft Delft cityIn The Netherlands Moxio basedIn Delft

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@arnoutboks #phpce17 Merging RDF (triples) Subject Predicate Object Arnout worksAt Moxio Arnout twitterHandle “@arnoutboks” Arnout livesIn Delft Delft cityIn The Netherlands Moxio basedIn Delft Subject Predicate Object The Netherlands hasCapital Amsterdam The Netherlands population “17.000.000”

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@arnoutboks #phpce17 Merging RDF (triples) Subject Predicate Object Arnout worksAt Moxio Arnout twitterHandle “@arnoutboks” Arnout livesIn Delft Delft cityIn The Netherlands Moxio basedIn Delft The Netherlands hasCapital Amsterdam The Netherlands population “17.000.000”

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@arnoutboks #phpce17 Merging RDF (graph) Arnout Moxio Delft @arnoutboks worksAt basedIn The Netherlands Amsterdam hasCapital 17.000.000 population

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@arnoutboks #phpce17 Serializing RDF: Turtle @prefix : . @prefix rdf: . @prefix xsd: . @base . :Arnout :livesIn :Delft ; :worksAt :Moxio ; :twitterHandle "@arnoutboks"^^xsd:string . :Delft :cityIn :The_Netherlands . :Moxio :basedIn :Delft .

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@arnoutboks #phpce17 Serializing RDF: RDF/XML > @a rnoutboks

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@arnoutboks #phpce17 Serializing RDF: JSON-LD [ { "@id" : "http://www.example.com/#Arnout", "http://www.example.com/#livesIn" : [ { "@id" : "http://www.example.com/#Delft" } ], "http://www.example.com/#twitterHandle" : [ { "@value" : "@arnoutboks" } ], "http://www.example.com/#worksAt" : [ { "@id" : "http://www.example.com/#Moxio" } ] }, ... ]

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@arnoutboks #phpce17 RDF is an abstract data model with different serialization formats

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@arnoutboks #phpce17 Identity Because there are multiple things named “Amsterdam”

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@arnoutboks #phpce17 Identity Subject Predicate Object Amsterdam numberOfGuns “42” Amsterdam status Wrecked National Maritime Museum (“Scheepvaartmuseum”)

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@arnoutboks #phpce17 Identity Subject Predicate Object Amsterdam numberOfGuns “42” Amsterdam status Wrecked Subject Predicate Object The Netherlands hasCapital Amsterdam The Netherlands population “17.000.000” National Maritime Museum (“Scheepvaartmuseum”) Lonely Planet

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@arnoutboks #phpce17 Identity The Netherlands Amsterdam hasCapital 17.000.000 population 42 Wrecked

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@arnoutboks #phpce17 URI’s for namespacing National Maritime Museum (“Scheepvaartmuseum”) https://www.hetscheepvaartmuseum.nl/ships/Amsterdam https://www.hetscheepvaartmuseum.nl/ships/numberOfGuns Lonely Planet https://www.lonelyplanet.com/Amsterdam https://www.lonelyplanet.com/hasCapital

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@arnoutboks #phpce17 Prefixes & QNames lonelyplanet:Amsterdam === https://www.lonelyplanet.com/Amsterdam QName URI local name local name namespace prefix

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@arnoutboks #phpce17 Prefixes & QNames National Maritime Museum (“Scheepvaartmuseum”) nmm:Amsterdam nmm:numberOfGuns Lonely Planet lonelyplanet:Amsterdam lonelyplanet:hasCapital

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@arnoutboks #phpce17 Three fundamental laws of the (Semantic) Web

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@arnoutboks #phpce17 Different name, different concept? lonelyplanet-en:Brussels lonelyplanet-nl:Brussel lonelyplanet-fr:Bruxelles lonelyplanet-zh:布魯塞爾

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@arnoutboks #phpce17 Different name, different concept? mi6:007 mi6:JamesBond

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@arnoutboks #phpce17 Nonunique Naming Assumption Different names do not imply different concepts

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@arnoutboks #phpce17 Truth & authority Subject Predicate Object whitehouse:Obama nsa:tapped whitehouse:Trump Donald Trump

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@arnoutboks #phpce17 Truth & authority Subject Predicate Object php-fig:CakePHP fw:isBetterThan php-fig:Symfony Donald Trump

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@arnoutboks #phpce17 The AAA Slogan “[On the web] Anyone can say Anything about Any topic”

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@arnoutboks #phpce17 (this slide intentionally left blank)

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@arnoutboks #phpce17 Absence of information Subject Predicate Object whitehouse:Trump fw:knows php-fig:Symfony whitehouse:Trump fw:knows php-fig:CakePHP whitehouse:Trump fw:knows php-fig:CodeIgniter

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@arnoutboks #phpce17 Open World Assumption We never have all information

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@arnoutboks #phpce17 SPARQL Query language for Semantic Web data

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@arnoutboks #phpce17 Triple Store Database for RDF triples

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@arnoutboks #phpce17 SPARQL SELECT ?employee ?company WHERE { ?employee :worksAt ?company . ?company :basedIn :Delft . }

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@arnoutboks #phpce17 SPARQL SELECT ?employee ?company WHERE { ?employee :worksAt ?company . ?company :basedIn :Delft . } ?employee ?company :Arnout :Moxio

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@arnoutboks #phpce17 SPARQL SELECT ?employee ?company ?city WHERE { ?employee :worksAt ?company . ?company :basedIn ?city . ?employee :livesIn ?city . } ?employee ?company ?city :Arnout :Moxio :Delft

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@arnoutboks #phpce17 Online SPARQL endpoints http://dbpedia.org/sparql

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@arnoutboks #phpce17 Online SPARQL endpoints PREFIX dbo: PREFIX dbr: SELECT ?song ?runtime WHERE { ?song dbo:artist dbr:The_Beatles . ?song dbo:runtime ?runtime . ?song rdf:type dbo:Song . } ORDER BY DESC (?runtime)

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@arnoutboks #phpce17 Online SPARQL endpoints

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@arnoutboks #phpce17 RDF Schema Schema language for Semantic Web data

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@arnoutboks #phpce17 RDF Schema (RDFS) Describes the structure of RDF-data… in RDF • Classes • Properties • Domain and range of properties • Inheritance of classes • ‘Inheritance’ of properties

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@arnoutboks #phpce17 RDF Schema (RDFS) Subject Predicate Object :DonaldTrump :isFatherOf :IvankaTrump

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@arnoutboks #phpce17 RDF Schema (RDFS) Subject Predicate Object :DonaldTrump :isFatherOf :IvankaTrump :isFatherOf rdfs:range :Person :isFatherOf rdfs:domain :Father :Father rdfs:subclassOf :Parent :Parent rdfs:subclassOf :Person :isFatherOf rdfs:subpropertyOf :isParentOf

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@arnoutboks #phpce17 RDF Schema & Inference Subject Predicate Object :DonaldTrump :isFatherOf :IvankaTrump :isFatherOf rdfs:range :Person :isFatherOf rdfs:domain :Father :Father rdfs:subclassOf :Parent :Parent rdfs:subclassOf :Person :isFatherOf rdfs:subpropertyOf :isParentOf :IvankaTrump rdf:type :Person :DonaldTrump rdf:type :Father :DonaldTrump rdf:type :Parent :DonaldTrump rdf:type :Person :DonaldTrump :isParentOf :IvankaTrump

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@arnoutboks #phpce17 Inference Reasoner (asserted) triples inferred/virtual triples

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@arnoutboks #phpce17 Inference Reasoner (asserted) triples inferred/virtual triples

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@arnoutboks #phpce17 SPARQL & Inference SELECT ?person WHERE { ?person rdf:type :Person . } ?person :IvankaTrump :DonaldTrump

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@arnoutboks #phpce17 Combining data using inference Subject Predicate Object a:DonaldTrump rdf:type a:Person Datasource A Subject Predicate Object b:MelaniaTrump rdf:type b:Human Datasource B

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@arnoutboks #phpce17 Combining data using inference Subject Predicate Object a:DonaldTrump rdf:type a:Person Datasource A Subject Predicate Object b:MelaniaTrump rdf:type b:Human Datasource B Subject Predicate Object a:Person rdfs:subclassOf b:Human b:Human rdfs:subclassOf a:Person Mapping rules

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@arnoutboks #phpce17 Combining data using inference Subject Predicate Object a:DonaldTrump rdf:type a:Person b:MelaniaTrump rdf:type b:Human a:Person rdfs:subclassOf b:Human b:Human rdfs:subclassOf a:Person a:DonaldTrump rdf:type b:Human b:MelaniaTrump rdf:type a:Person

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@arnoutboks #phpce17 Query different sources as if they were one

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@arnoutboks #phpce17 RDF Schema vs. JSON/XML Schema Subject Predicate Object mi6:JamesBond rdf:type mi6:SecretAgent mi6:JamesBond nmm:numberOfGuns “1” MI6 files

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@arnoutboks #phpce17 RDF Schema vs. JSON/XML Schema Subject Predicate Object mi6:JamesBond rdf:type mi6:SecretAgent mi6:JamesBond nmm:numberOfGuns “1” MI6 files

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@arnoutboks #phpce17 RDF Schema vs. JSON/XML Schema Subject Predicate Object mi6:JamesBond rdf:type mi6:SecretAgent mi6:JamesBond nmm:numberOfGuns “1” MI6 files Subject Predicate Object nmm:numberOfGuns rdf:domain nmm:Ship National Maritime Museum (“Scheepvaartmuseum”)

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@arnoutboks #phpce17 RDF Schema vs. JSON/XML Schema Subject Predicate Object mi6:JamesBond rdf:type mi6:SecretAgent mi6:JamesBond nmm:numberOfGuns “1” nmm:numberOfGuns rdf:domain nmm:Ship mi6:JamesBond rdf:type nmm:Ship

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@arnoutboks #phpce17 RDF Schema vs. JSON/XML Schema

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@arnoutboks #phpce17 RDF Schema will never consider data to be invalid

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@arnoutboks #phpce17 Web Ontology Language (OWL) Even smarter inferencing Web Ontology Language (OWL) Even smarter inferencing

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@arnoutboks #phpce17 OWL OWL ≈ RDFS++

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@arnoutboks #phpce17 OWL Power comes at a price…

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@arnoutboks #phpce17 OWL: Inverse properties Subject Predicate Object :DonaldTrump :isParentOf :IvankaTrump :isParentOf owl:inverseOf :isChildOf :IvankaTrump :isChildOf :DonaldTrump

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@arnoutboks #phpce17 OWL: Symmetric properties Subject Predicate Object :DonaldTrump :isMarriedTo :MelaniaTrump :isMarriedTo rdf:type owl:SymmetricProperty :MelaniaTrump :isMarriedTo :DonaldTrump

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@arnoutboks #phpce17 OWL: Equality Subject Predicate Object :DonaldTrump :isMarriedTo :MelaniaTrump :DonaldTrump owl:sameAs :TheDon :TheDon :isMarriedTo :MelaniaTrump

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@arnoutboks #phpce17 OWL: Functional properties Subject Predicate Object :IvankaTrump :hasFather :DonaldTrump :IvankaTrump :hasFather :TheDon :hasFather rdf:type owl:FunctionalProperty :TheDon owl:sameAs :DonaldTrump

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@arnoutboks #phpce17 Inconsistency Subject Predicate Object :IvankaTrump :hasFather :DonaldTrump :IvankaTrump :hasFather :TheDon :hasFather rdf:type owl:FunctionalProperty :TheDon owl:differentFrom :DonaldTrump

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@arnoutboks #phpce17 Inconsistency

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@arnoutboks #phpce17 Inconsistency

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@arnoutboks #phpce17 It’s okay to be inconsistent… (remember the AAA slogan)

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@arnoutboks #phpce17 It’s okay to be inconsistent… (remember the AAA slogan) …but the reasoner won’t help you anymore

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@arnoutboks #phpce17 Further steps Get going with the Semantic Web

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@arnoutboks #phpce17 Self-test Subject Predicate Object :George :hasChild :Michelle :George :hasChild :James How many children does George have?

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@arnoutboks #phpce17 Leveraging the Semantic Web Network effect

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@arnoutboks #phpce17 Leveraging the Semantic Web Only useful when multiple parties speak the same ‘language’

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@arnoutboks #phpce17 Align with existing vocabularies

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@arnoutboks #phpce17 Leveraging the Semantic Web Mapping between vocabularies: • rdfs:subclassOf • rdfs:subpropertyOf • owl:inverseOf • owl:sameAs

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@arnoutboks #phpce17 Existing vocabularies • Dublin Core • Metadata about publications and authors • Friend of a Friend • People, connections, social networks • GoodRelations • Products, prices, eCommerce • CB-NL • Construction, infrastructure, spatial planning • QUDT • Quantities, units, dimensions, conversions

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@arnoutboks #phpce17 Resources • Apache Jena • Semantic web framework/tools (written in Java) • easyrdf/easyrdf • RDF parser/writer for PHP • semsol/arc2 • PHP RDF library and MySQL-based triple store • FaCT++, HermiT & Pellet • Open source OWL reasoners • Protégé • RDF/OWL IDE with various reasoner plugins

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@arnoutboks #phpce17 Resources

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@arnoutboks #phpce17 Resources • https://www.w3.org/2013/data/ • https://www.w3.org/2001/sw/wiki/ • https://www.w3.org/TR/rdf11-primer/ • https://www.w3.org/TR/owl2-primer/ • https://www.w3.org/TR/sparql11-query/ • http://wiki.dbpedia.org/OnlineAccess • https://www.data.gov/ • http://lod-cloud.net/

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@arnoutboks #phpce17 Feedback & Questions @arnoutboks @arnoutboks @aboks Arnout Boks Please leave your feedback on joind.in

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@arnoutboks #phpce17 Image Credits • https://www.flickr.com/photos/lex-photographic/32521124574 • https://www.flickr.com/photos/flamesworddragon/19686463141 • https://www.flickr.com/photos/littlehuw/15236543728 • https://www.flickr.com/photos/crdominguez/422517106 • https://www.flickr.com/photos/pamwood707/5646757752 • https://www.flickr.com/photos/blair25/3240686470 • https://www.flickr.com/photos/tylerbeaulawrence/15167523690 • https://www.flickr.com/photos/23975018@N04/3675503072 • https://www.flickr.com/photos/borkurdotnet/9682277597