Introducing Linked Data
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- Charla Lambert
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1 Introducing Linked Data (Part of this work was funded by PlanetData NoE FP7/ ) Irini Fundulaki 1 1 Institute of Computer Science FORTH & W3C Greece Office Manager EICOS : 4th Meeting, Athens, Greece March 29, 2013 Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
2 Outline 1 Going from the Web of Documents to the Web of Data 2 Web Architecture Items of Interest Naming Resources: URIs Resource Description Framework (RDF) 3 Adding Semantics to Linked Data A Short Introduction RDF Vocabulary Description Language (RDFS) Ontology Web Language (OWL) 4 Linked Data LifeCycle Extraction Interlinking/Fusing Storage/Querying 5 Conclusions rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
3 Going from the Web of Documents to the Web of Data Traditional Web: Web of Documents single information space: global filesystem designed for human consumption documents are the primary objects with a loose structure untyped hyperlinks between documents URLs are the globally unique IDs and part of the retrieval mechanism cannot ask expressive queries Web Browsers Search Engines hyperlinks hyperlinks hyperlinks c Hartig, Cyganiac, Bizer, Hausenblas, Heath How to Publish Linked Data on the Web Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
4 Going from the Web of Documents to the Web of Data Going from a Web of Documents to a Web of Data a global database designed for machines first, humans later things are the primary objects with a well defined structure typed links between things ability to express structured queries Don t link the documents, link the things The Web of Linked Data c Tom Heath, An Introduction to Linked Data Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
5 Going from the Web of Documents to the Web of Data Publishing Data on the Web: Web APIs APIs expose structured data enable the development of new applications provide simple query access over the HTTP protocol proprietary interfaces based on a fixed set of sources deep structure is not visible mashup creation mashup creation data data Web APIs create data silos in the Web Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
6 Going from the Web of Documents to the Web of Data Publishing Data on the Web: Web APIs APIs expose structured data enable the development of new applications provide simple query access over the HTTP protocol proprietary interfaces based on a fixed set of sources deep structure is not visible mashup creation mashup creation data data Web APIs create data silos in the Web rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
7 Going from the Web of Documents to the Web of Data Publishing Data on the Web: Microformats embed structured data into HTML pages describing specific types of entities compatible with the idea of Web as a single information space applications can extract data from the pages using microformats only a fixed set of microformats exist (restricting the domain of interest) no way to connect to data items cannot share arbitrary data on the Web 1. <div class="geo">tim?berners-?lee's location is: 2. <span class="latitude"> </span>, 3. <span class="longitude"> </span>. 4. </div> geo ( denotes the latitude and longitude of the resource tied to the embedding web page Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
8 Going from the Web of Documents to the Web of Data Linked Data Beyond Web APIs and Microformats publishing and interlinking structured data on the Web using Semantic Web technologies sharing structured data on the Web as easily as documents are shared today is about using the Web to create typed links between different sources accessed through a single, standardized access mechanism Web Of Data, Semantic Web (Data Commons) a space where people and organizations can post and consume data about anything Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
9 Going from the Web of Documents to the Web of Data Linked Data Principles 1. Use URIs as names for things 2. Use HTTPs URIs so that people can look up those names 3. When someone looks up a URI, provide useful RDF information 4. Include RDF statements that link to other URIs so that they can discover related things Tim Berners-Lee, 2007 Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
10 Going from the Web of Documents to the Web of Data Is Linked Data Real? Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
11 Going from the Web of Documents to the Web of Data Linking Open Data Linking Open Datasets on the Web (LOD) publish public open data as Linked Data on the Web interlink entities between heterogeneous sources Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
12 Going from the Web of Documents to the Web of Data Evolution of Linked Open Datasets May 2007 Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
13 Going from the Web of Documents to the Web of Data Evolution of Linked Open Datasets September 2008 Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
14 Going from the Web of Documents to the Web of Data Evolution of Linked Open Datasets March 2009 Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
15 Going from the Web of Documents to the Web of Data Linked Data in numbers (September 2011) Domain # datasets Triples % (Out)-Links % Media 25 1,841,852, % 50,440, % Geographic 31 6,145,532, % 35,812, % Government 49 13,315,009, % 19,343, % Publications 87 2,950,720, % 139,925, % Cross-domain 41 4,184,635, % 63,183, % Life sciences 41 3,036,336, % 191,844, % User-gen. cont ,127, % 3,449, % ,634,213, ,998,829 (a) Distribution of links per domain (b) Distribution of triples per domain Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
16 Going from the Web of Documents to the Web of Data LinkedData: GeoNames Geographical Database covers all countries contains over eight million placenames considers facets/features integrates data from various datasources: National Geospatial-Intelligence Agency s (NGA), U.S. Geological Survey Geographic Names Information System, Brasileiro de Geografia Estatística (IBGE),... Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
17 Going from the Web of Documents to the Web of Data The DBPedia Knowledge Base crowd-sourced community effort to extract structured information from Wikipedia links available datasets on the Web to data extracted from Wikipedia versions of DBPedia in 111 languages data is published in a consistent ontology accessible through different SPARQL end-points DBPedia Live enables such a continuous synchronization between DBpedia and Wikipedia: Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
18 Going from the Web of Documents to the Web of Data The DBPedia Knowledge Base crowd-sourced community effort to extract structured information from Wikipedia links available datasets on the Web to data extracted from Wikipedia versions of DBPedia in 111 languages data is published in a consistent ontology accessible through different SPARQL end-points DBPedia Live enables such a continuous synchronization between DBpedia and Wikipedia: rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
19 Going from the Web of Documents to the Web of Data Linked Data Applications Linked Data Browsers Linked Data Mashups Search Engines Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
20 Going from the Web of Documents to the Web of Data Linked Data Applications Linked Data Browsers Linked Data Mashups Search Engines rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
21 Going from the Web of Documents to the Web of Data Linked Data Browsers Linked Data Browser explores the Linked Data Cloud: recognizes and follows RDF links to RDF resources Tabulator Browser Marbles (FU Berlin, DE) OpenLink RDF Browser (OpenLink, UK) Zitgist RDF Browser (Zitgist, USA) Disco Hyperdata Browser (FU Berlin, DE) Fenfire (DERI, Ireland) installed and configured as add-ons to existing browsers Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
22 Going from the Web of Documents to the Web of Data Linked Data Browsers Linked Data Browser explores the Linked Data Cloud: recognizes and follows RDF links to RDF resources Tabulator Browser Marbles (FU Berlin, DE) OpenLink RDF Browser (OpenLink, UK) Zitgist RDF Browser (Zitgist, USA) Disco Hyperdata Browser (FU Berlin, DE) Fenfire (DERI, Ireland) installed and configured as add-ons to existing browsers rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
23 Going from the Web of Documents to the Web of Data Linked Data Browsers Linked Data Browser explores the Linked Data Cloud: recognizes and follows RDF links to RDF resources Tabulator Browser Marbles (FU Berlin, DE) OpenLink RDF Browser (OpenLink, UK) Zitgist RDF Browser (Zitgist, USA) Disco Hyperdata Browser (FU Berlin, DE) Fenfire (DERI, Ireland) installed and configured as add-ons to existing browsers rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
24 Going from the Web of Documents to the Web of Data Linked Data Mashups Linked Data Mashups: Domain-specific applications that use Linked Data Revyu.com: everything you can review, uses Linked Data to enrich ratings, accessed through SPARQL endpoint DBtune Slashfacet: Visualizes music-related Linked Data data from LastFM, MySpace, BBC, Magnatune 14 billion triples accessed through SPARQL endpoints Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
25 Going from the Web of Documents to the Web of Data Linked Data Mashups DERI Semantic Web Pipes build open source,extendable, embeddable Web Data mashups in the spirit of Yahoo! Pipes produce as output a stream of data in different formats (XML, RDF, JSON) to be used by applications. Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
26 Going from the Web of Documents to the Web of Data Linked Data Search Engines Falcons (IWS, China) supports keyword based search to objects, concepts (classes and properties), ontologies and RDF datasets Sindice (DERI, Ireland) explores and integrates RDF content keyword based search structured search through SPARQL queries MicroSearch (Yahooo, Spain) enriched Yahoo! search extracts and displays the metadata of pages Watson (Open University, UK) supports keyword based search graphical representation of datasets Semantic Web Search Engine (SWSE) (DERI, Ireland) Semantic Web Ontology Swoogle (UMBC, USA) supports keyword based search to objects, concepts (classes and properties), ontologies and RDF datasets Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
27 Outline Web Architecture Items of Interest 1 Going from the Web of Documents to the Web of Data 2 Web Architecture Items of Interest Naming Resources: URIs Resource Description Framework (RDF) 3 Adding Semantics to Linked Data A Short Introduction RDF Vocabulary Description Language (RDFS) Ontology Web Language (OWL) 4 Linked Data LifeCycle Extraction Interlinking/Fusing Storage/Querying 5 Conclusions rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
28 Web Architecture Items of Interest Web Architecture: Items of Interest Resources things whose properties and relationships we want to describe in the data identified using Uniform Resource Identifiers (URIs) Distinguished into: URI Aliases Information Resources: documents, images, media files,... Non-Information Resources: people, places, proteins, cars,... different information providers talk about the same non-information resource using different URIs DBpedia: identifies place Berlin GeoNames: identifies place Berlin Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
29 Web Architecture Items of Interest Web Architecture: Items of Interest Resources things whose properties and relationships we want to describe in the data identified using Uniform Resource Identifiers (URIs) Distinguished into: URI Aliases Information Resources: documents, images, media files,... Non-Information Resources: people, places, proteins, cars,... different information providers talk about the same non-information resource using different URIs DBpedia: identifies place Berlin GeoNames: identifies place Berlin rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
30 Web Architecture Items of Interest Web Architecture: Items of Interest Representation : stream of bytes in a certain format such as HTML, RDF/XML, Turtle, NTriples, JSON, JPEG, PDF,.... HTML chosen to represent descriptions read by humans RDF/XML, Turtle, NTriples,... to represent descriptions managed by machines (RDF data serialization formats) Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
31 Web Architecture Items of Interest Web Architecture: Items of Interest Dereferencing URIs looking up a URI on the Web in order to get information about the referenced resource. Information Resource server of the URI owner returns a snapshot of the resource s current state and returns it in the requested format Non-Information Resource are dereferenced indirectly. Content Negotiation clients send HTTP requests with a header indicating the kind of preferred representation Associated Description is the result of dereferencing the URI of a non-information resource the description of a non-information resource can have multiple representations Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
32 Outline Web Architecture Naming Resources: URIs 1 Going from the Web of Documents to the Web of Data 2 Web Architecture Items of Interest Naming Resources: URIs Resource Description Framework (RDF) 3 Adding Semantics to Linked Data A Short Introduction RDF Vocabulary Description Language (RDFS) Ontology Web Language (OWL) 4 Linked Data LifeCycle Extraction Interlinking/Fusing Storage/Querying 5 Conclusions rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
33 Web Architecture Naming Resources: URIs Naming Resource: URIs provide a simple way to create globally unique names in a decentralized fashion used as a name but also as a means of accessing information is the only scheme that is supported by all browsers stable and persistent, defined in a controlled namespace defined independently of any implementation dereferencable: HTTP clients can look up the URI using the HTTP protocol URIs that refer to information resources, return documents URIs that identify real-world objects and abstract concepts (non-information resources) return the descriptions Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
34 Web Architecture Naming Resources: URIs URIs for Information and Non-Information Resources by Example Big Lynx independent television production company with website staff members: non-information resources RDF/XML file that stores information about staff members: information resources Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
35 Web Architecture Naming Resources: URIs Dereferencing URIs for non-information resources (1) 1 GET /people/libby-miller HTTP/1.1 2 Host: biglynx.co.uk 3 Accept: text/html (2) 1 HTTP/ See Other 2 Location: 3 Vary: Accept (3) (4) 1 GET /people/libby-miller.rdf HTTP/1.1 2 Host: biglynx.co.uk 3 Accept: text/html;q=0.5, application/rdf+xml 1 HTTP/ OK 2 Content-Type: application/rdf+xml <?xml version="1.0" encoding="utf-8"?> 6 <rdf:rdf 7 xmlns:rdf=" 8 xmlns:foaf=" <rdf:description rdf:about=" 11 <rdf:type rdf:resource=" 12 <foaf:name>libby Miller</foaf:name> Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
36 Outline Web Architecture Resource Description Framework (RDF) 1 Going from the Web of Documents to the Web of Data 2 Web Architecture Items of Interest Naming Resources: URIs Resource Description Framework (RDF) 3 Adding Semantics to Linked Data A Short Introduction RDF Vocabulary Description Language (RDFS) Ontology Web Language (OWL) 4 Linked Data LifeCycle Extraction Interlinking/Fusing Storage/Querying 5 Conclusions rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
37 Web Architecture Resource Description Framework Resource Description Framework (RDF) RDF is the W3C standard for representing information in the Web U Subject Predicate Object U = set of URIs B = set of Blank nodes L = set of Literals U B U B L (s, p, o) (U B) U (U B L) is called an RDF triple set of RDF triples is an RDF graph RDF graph is a node and edge-labeled directed graph Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
38 Web Architecture Resource Description Framework (RDF) RDF by Example (subject) (predicate) (object) t 1 csail:libby rdf:type foaf:person t 2 csail:libby foaf:name Libby Miller t 3 csail:libby owl:sameas webwho:libby miller subject: the URI identifying the described resource object: can either be a simple literal value or the URI of another resource predicate: the URI indicating the relation between subject and object csail:libby: subject URI of the resource of interest rdf:type, foaf:name, owl:sameas: predicate URIs coming from vocabularies Resource Description Framework - RDF Friend Of A Friend - FOAF Ontology Web Language - OWL. Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
39 Web Architecture Resource Description Framework (RDF) RDF by Example (subject) (predicate) (object) t 1 csail:libby rdf:type foaf:person t 2 csail:libby foaf:name Libby Miller t 3 csail:libby owl:sameas webwho:libby miller subject: the URI identifying the described resource object: can either be a simple literal value or the URI of another resource predicate: the URI indicating the relation between subject and object csail:libby: subject URI of the resource of interest rdf:type, foaf:name, owl:sameas: predicate URIs coming from vocabularies Resource Description Framework - RDF Friend Of A Friend - FOAF Ontology Web Language - OWL. rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
40 Web Architecture Resource Description Framework (RDF) RDF by Example (subject) (predicate) (object) t 1 csail:libby rdf:type foaf:person t 2 csail:libby foaf:name Libby Miller t 3 csail:libby owl:sameas webwho:libby miller subject: the URI identifying the described resource object: can either be a simple literal value or the URI of another resource predicate: the URI indicating the relation between subject and object csail:libby: subject URI of the resource of interest rdf:type, foaf:name, owl:sameas: predicate URIs coming from vocabularies Resource Description Framework - RDF Friend Of A Friend - FOAF Ontology Web Language - OWL. rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
41 Web Architecture Resource Description Framework (RDF) RDF by Example (subject) (predicate) (object) t 1 csail:libby rdf:type foaf:person t 2 csail:libby foaf:name Libby Miller t 3 csail:libby owl:sameas webwho:libby miller subject: the URI identifying the described resource object: can either be a simple literal value or the URI of another resource predicate: the URI indicating the relation between subject and object csail:libby: subject URI of the resource of interest rdf:type, foaf:name, owl:sameas: predicate URIs coming from vocabularies Resource Description Framework - RDF Friend Of A Friend - FOAF Ontology Web Language - OWL. rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
42 Web Architecture Resource Description Framework (RDF) RDF by Example (subject) (predicate) (object) t 1 csail:libby rdf:type foaf:person t 2 csail:libby foaf:name Libby Miller t 3 csail:libby foaf:mbox mailto:libby.miller@biglynx.co.uk t 4 csail:libby foaf:img t 5 csail:libby owl:sameas webwho:libby miller the above set of RDF triples form an RDF graph webwho:libby_miller owl:sameas csail:lilly rdf:type foaf:person foaf:img foaf:name Lilly Miller foaf:mbox mailto:libby.miller@biglynx.co.uk Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
43 Web Architecture Resource Description Framework (RDF) Resource Description Framework Benefits of the RDF Data Model generic and simple graph-based data model information from heterogeneous sources merges naturally: resources with the same URIs denote the same non-information resource schemas are transparent: information is in the URIS structure is added using schema languages and represented as RDF triples Web browsers use URIs to retrieve information Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
44 Web Architecture Resource Description Framework (RDF) Resource Description Framework Benefits of the RDF Data Model generic and simple graph-based data model information from heterogeneous sources merges naturally: resources with the same URIs denote the same non-information resource schemas are transparent: information is in the URIS structure is added using schema languages and represented as RDF triples Web browsers use URIs to retrieve information rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
45 Web Architecture Resource Description Framework (RDF) Resource Description Framework Benefits of the RDF Data Model generic and simple graph-based data model information from heterogeneous sources merges naturally: resources with the same URIs denote the same non-information resource schemas are transparent: information is in the URIS structure is added using schema languages and represented as RDF triples Web browsers use URIs to retrieve information rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
46 Web Architecture Resource Description Framework (RDF) Resource Description Framework Benefits of the RDF Data Model generic and simple graph-based data model information from heterogeneous sources merges naturally: resources with the same URIs denote the same non-information resource schemas are transparent: information is in the URIS structure is added using schema languages and represented as RDF triples Web browsers use URIs to retrieve information rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
47 Web Architecture Resource Description Framework (RDF) Resource Description Framework Benefits of the RDF Data Model generic and simple graph-based data model information from heterogeneous sources merges naturally: resources with the same URIs denote the same non-information resource schemas are transparent: information is in the URIS structure is added using schema languages and represented as RDF triples Web browsers use URIs to retrieve information rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
48 Web Architecture Resource Description Framework (RDF) Resource Description Framework Benefits of the RDF Data Model generic and simple graph-based data model information from heterogeneous sources merges naturally: resources with the same URIs denote the same non-information resource schemas are transparent: information is in the URIS structure is added using schema languages and represented as RDF triples Web browsers use URIs to retrieve information rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
49 Web Architecture Resource Description Framework (RDF) Resource Description Framework Benefits of the RDF Data Model generic and simple graph-based data model information from heterogeneous sources merges naturally: resources with the same URIs denote the same non-information resource schemas are transparent: information is in the URIS structure is added using schema languages and represented as RDF triples Web browsers use URIs to retrieve information rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
50 Web Architecture RDF Serialization Formats Resource Description Framework (RDF) Serialization Formats: Creating information resources out of non-information resources RDF/XML: standardized by the W3C and is widely used to publish Linked Data on the Web but is heavy and difficult for humans to write and read 1 <?xml version="1.0" encoding="utf-8"?> 2 <rdf:rdf 3 xmlns:rdf=" 4 xmlns:foaf=" 5 xmlns:csail=" 6 7 <rdf:description rdf:about="csail:libby"> 8 <rdf:type rdf:resource=" 9 <foaf:name>libby Miller</foaf:name> 10 </rdf:description> 11 </rdf:rdf> Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
51 Web Architecture RDF Serialization Formats Resource Description Framework (RDF) RDFa: RDF triples are interwoven in HTML code but publishing infrastructure is not yet in place 1 <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML+RDFa 1.0//EN" " 2 <html xmlns=" xmlns:rdf=" xmlns:foaf=" xmlns:csail=" 3 4 <head> 5 <meta http-equiv="content-type" content="application/xhtml+xml; charset=utf-8"/> 6 <title>profile Page for Libby Miller 7 </head> 8 9 <body> 10 <div about="csail:libby" typeof="foaf:person"> 11 <span property="foaf:name">libby Miller</span></div> 12 </body> 13 </html> Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
52 Web Architecture RDF Serialization Formats Resource Description Framework (RDF) Turtle is a plain text format and is the format of choice for reading RDF triples or writing them by hand rdf: < foaf: < csail: < 3 4 csail:libby_miller 5 rdf:type foaf:person ; 6 foaf:name "Libby Miller". N-Triples is a subset of Turtle, minus features such as namespace prefixes and shorthands leading to redundancy but allows parsing and loading one line at a time, compression to handle big files, exchange, main memory parsing 1 < < < 2 < < "Libby Miller". Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
53 Web Architecture Creating Linked Data: RDF Links Resource Description Framework (RDF) Literal Triples: have an RDF literal as the object used to describe the properties of resources Object Triples: represent typed links between two resources ( the subject and object are URIs) RDF Links Relationship Links: point at related things in other data sources Identity Links: point at URI aliases used by other data sources to identify the same real-world object or abstract concept. Vocabulary Links point from data to the definitions of the vocabulary terms that are used to represent the data Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
54 Web Architecture Creating Linked Data: RDF Links Resource Description Framework (RDF) Literal Triples: have an RDF literal as the object used to describe the properties of resources Object Triples: represent typed links between two resources ( the subject and object are URIs) RDF Links Relationship Links: point at related things in other data sources Identity Links: point at URI aliases used by other data sources to identify the same real-world object or abstract concept. Vocabulary Links point from data to the definitions of the vocabulary terms that are used to represent the data rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
55 Web Architecture Creating Linked Data: RDF Links Resource Description Framework (RDF) Literal Triples: have an RDF literal as the object used to describe the properties of resources Object Triples: represent typed links between two resources ( the subject and object are URIs) RDF Links Relationship Links: point at related things in other data sources Identity Links: point at URI aliases used by other data sources to identify the same real-world object or abstract concept. Vocabulary Links point from data to the definitions of the vocabulary terms that are used to represent the data rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
56 Web Architecture Resource Description Framework (RDF) Creating Linked Data: RDF Links rdf:type csail:lilly foaf:person Relationship Links foaf:based_near foaf:name Lilly Miller dbpedia:munich Identity Links webwho:libby_miller owl:sameas csail:lilly sorg:containedin sorg:isicv4 xsd:string Vocabulary Links sorg:place rdfs:subclassof sorg:geo sorg:geoshape csail:libby_hometown rdf:type sorg:city Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
57 Web Architecture Creating Linked Data: RDF Links Resource Description Framework (RDF) RDF links: Foundation of Linked Data csail:lilly rdf:type foaf:person sorg:containedin foaf:name sorg:isicv4 Lilly Miller sorg:place foaf:based_near sorg:geo rdfs:subclassof owl:sameas rdf:type dbpedia:munich sorg:city webwho:libby_miller db-ont:country db-ont:populationtotal xsd:string sorg:geoshape dbpedia:germany 1,1305,522 Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
58 Outline Adding Semantics to Linked Data A Short Introduction 1 Going from the Web of Documents to the Web of Data 2 Web Architecture Items of Interest Naming Resources: URIs Resource Description Framework (RDF) 3 Adding Semantics to Linked Data A Short Introduction RDF Vocabulary Description Language (RDFS) Ontology Web Language (OWL) 4 Linked Data LifeCycle Extraction Interlinking/Fusing Storage/Querying 5 Conclusions rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
59 Adding Semantics to Linked Data A Short Introduction Adding Semantics to Linked Data RDF is a generic, abstract data model for describing resources in the form of triples does not provide ways of defining classes, properties, constraints etc. Languages Simple Knowledge Organization System (SKOS) to define taxonomies/thesauri RDF Vocabulary Description Language (RDF Schema - RDFS) to define vocabularies Ontology Web Language (OWL) to define ontologies Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
60 Adding Semantics to Linked Data A Short Introduction Adding Semantics to Linked Data RDF is a generic, abstract data model for describing resources in the form of triples does not provide ways of defining classes, properties, constraints etc. Languages Simple Knowledge Organization System (SKOS) to define taxonomies/thesauri RDF Vocabulary Description Language (RDF Schema - RDFS) to define vocabularies Ontology Web Language (OWL) to define ontologies rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
61 Outline Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) 1 Going from the Web of Documents to the Web of Data 2 Web Architecture Items of Interest Naming Resources: URIs Resource Description Framework (RDF) 3 Adding Semantics to Linked Data A Short Introduction RDF Vocabulary Description Language (RDFS) Ontology Web Language (OWL) 4 Linked Data LifeCycle Extraction Interlinking/Fusing Storage/Querying 5 Conclusions rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
62 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDF Vocabulary Description Language: RDF Schema designed to introduce useful semantics to RDF triples typing: defining classes, properties, instances relationships between types and instances: subsumption and instantiation constraints: domain and range for properties inference rules to entail new, inferred knowledge schemas are represented as RDF triples (subject) (predicate) (object) t 1 sorg:place rdf:type rdfs:class t 2 sorg:city rdfs:subclassof sorg:place t 3 sorg:containedin rdf:type rdf:property t 4 sorg:containedin rdfs:domain sorg:place t 5 sorg:containedin rdfs:range sorg:place t 6 csail:libby home town rdf:type sorg:city Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
63 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDF Vocabulary Description Language: RDF Schema designed to introduce useful semantics to RDF triples typing: defining classes, properties, instances relationships between types and instances: subsumption and instantiation constraints: domain and range for properties inference rules to entail new, inferred knowledge schemas are represented as RDF triples (subject) (predicate) (object) t 1 sorg:place rdf:type rdfs:class t 2 sorg:city rdfs:subclassof sorg:place t 3 sorg:containedin rdf:type rdf:property t 4 sorg:containedin rdfs:domain sorg:place t 5 sorg:containedin rdfs:range sorg:place t 6 csail:libby home town rdf:type sorg:city Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
64 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDF Vocabulary Description Language: RDF Schema designed to introduce useful semantics to RDF triples typing: defining classes, properties, instances relationships between types and instances: subsumption and instantiation constraints: domain and range for properties inference rules to entail new, inferred knowledge schemas are represented as RDF triples (subject) (predicate) (object) t 1 sorg:place rdf:type rdfs:class t 2 sorg:city rdfs:subclassof sorg:place t 3 sorg:containedin rdf:type rdf:property t 4 sorg:containedin rdfs:domain sorg:place t 5 sorg:containedin rdfs:range sorg:place t 6 csail:libby home town rdf:type sorg:city Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
65 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDF Vocabulary Description Language: RDF Schema designed to introduce useful semantics to RDF triples typing: defining classes, properties, instances relationships between types and instances: subsumption and instantiation constraints: domain and range for properties inference rules to entail new, inferred knowledge schemas are represented as RDF triples (subject) (predicate) (object) t 1 sorg:place rdf:type rdfs:class t 2 sorg:city rdfs:subclassof sorg:place t 3 sorg:containedin rdf:type rdf:property t 4 sorg:containedin rdfs:domain sorg:place t 5 sorg:containedin rdfs:range sorg:place t 6 csail:libby home town rdf:type sorg:city Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
66 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDF Vocabulary Description Language: RDF Schema designed to introduce useful semantics to RDF triples typing: defining classes, properties, instances relationships between types and instances: subsumption and instantiation constraints: domain and range for properties inference rules to entail new, inferred knowledge schemas are represented as RDF triples (subject) (predicate) (object) t 1 sorg:place rdf:type rdfs:class t 2 sorg:city rdfs:subclassof sorg:place t 3 sorg:containedin rdf:type rdf:property t 4 sorg:containedin rdfs:domain sorg:place t 5 sorg:containedin rdfs:range sorg:place t 6 csail:libby home town rdf:type sorg:city Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
67 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDF Vocabulary Description Language: RDF Schema designed to introduce useful semantics to RDF triples typing: defining classes, properties, instances relationships between types and instances: subsumption and instantiation constraints: domain and range for properties inference rules to entail new, inferred knowledge schemas are represented as RDF triples (subject) (predicate) (object) t 1 sorg:place rdf:type rdfs:class t 2 sorg:city rdfs:subclassof sorg:place t 3 sorg:containedin rdf:type rdf:property t 4 sorg:containedin rdfs:domain sorg:place t 5 sorg:containedin rdfs:range sorg:place t 6 csail:libby home town rdf:type sorg:city Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
68 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDFS Inference Used to entail new information from the one that is explicitly stated transitive closure along the class and property hierarchies (P 1, rdfs:subpropertyof, P 2), (P 2, rdfs:subpropertyof, P 3) R 1 : (P 1, rdfs:subpropertyof, P 3) R 2 : (C 1, rdfs:subclassofc 2,, )(C 2, rdfs:subclassof, C 3) (C 1, rdfs:subclassof, C 3) transitive closure along the type and class/property hierarchies (P 1, rdfs:subpropertyof, P 2), (r 1, P 1, r 2) R 3 : (r 1, P 2, r 2) R 4 : (C 1, rdfs:subclassof, C 2), (r 1, rdf:type, C 1) (r 1, rdf:type, C 2) Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
69 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDFS Inference (subject) (predicate) (object) t 1 sorg:place rdf:type rdfs:class t 2 sorg:city rdfs:subclassof sorg:place t 6 csail:libby home town rdf:type sorg:city transitive closure along the type and class/property hierarchies R 4 : (C 1, rdfs:subclassof, C 2), (r 1, rdf:type, C 1) (r 1, rdf:type, C 2) (subject) (predicate) (object) t 7 sorg:city rdf:type rdfs:class t 8 csail:libby home town rdf:type sorg:place Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
70 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDFS Inference (subject) (predicate) (object) t 1 sorg:place rdf:type rdfs:class t 2 sorg:city rdfs:subclassof sorg:place t 6 csail:libby home town rdf:type sorg:city transitive closure along the type and class/property hierarchies R 4 : (C 1, rdfs:subclassof, C 2), (r 1, rdf:type, C 1) (r 1, rdf:type, C 2) (subject) (predicate) (object) t 7 sorg:city rdf:type rdfs:class t 8 csail:libby home town rdf:type sorg:place rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
71 Adding Semantics to Linked Data RDF Vocabulary Description Language (RDFS) RDFS Inference (subject) (predicate) (object) t 1 sorg:place rdf:type rdfs:class t 2 sorg:city rdfs:subclassof sorg:place t 6 csail:libby home town rdf:type sorg:city transitive closure along the type and class/property hierarchies R 4 : (C 1, rdfs:subclassof, C 2), (r 1, rdf:type, C 1) (r 1, rdf:type, C 2) (subject) (predicate) (object) t 7 sorg:city rdf:type rdfs:class t 8 csail:libby home town rdf:type sorg:place rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
72 Outline Adding Semantics to Linked Data Ontology Web Language (OWL) 1 Going from the Web of Documents to the Web of Data 2 Web Architecture Items of Interest Naming Resources: URIs Resource Description Framework (RDF) 3 Adding Semantics to Linked Data A Short Introduction RDF Vocabulary Description Language (RDFS) Ontology Web Language (OWL) 4 Linked Data LifeCycle Extraction Interlinking/Fusing Storage/Querying 5 Conclusions rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
73 Adding Semantics to Linked Data Ontology Web Language (OWL) Ontology Web Language: OWL RDFS is useful but has limited capabilities regarding schema constraints class/property hierarchies, constraining property domain and range Ontologies define the concepts, relationships and complex constraints to describe and represent an area of knowledge Ontology Web Language used to create and reason about ontologies: terminology/vocabulary used in a specific context constraints on terms and properties equivalence of vocabulary terms etc. rich semantics but must be computational tractable and implementable Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
74 Adding Semantics to Linked Data Ontology Web Language (OWL) Ontology Web Language: OWL RDFS is useful but has limited capabilities regarding schema constraints class/property hierarchies, constraining property domain and range Ontologies define the concepts, relationships and complex constraints to describe and represent an area of knowledge Ontology Web Language used to create and reason about ontologies: terminology/vocabulary used in a specific context constraints on terms and properties equivalence of vocabulary terms etc. rich semantics but must be computational tractable and implementable rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
75 Adding Semantics to Linked Data Ontology Web Language (OWL) Ontology Web Language: OWL RDFS is useful but has limited capabilities regarding schema constraints class/property hierarchies, constraining property domain and range Ontologies define the concepts, relationships and complex constraints to describe and represent an area of knowledge Ontology Web Language used to create and reason about ontologies: terminology/vocabulary used in a specific context constraints on terms and properties equivalence of vocabulary terms etc. rich semantics but must be computational tractable and implementable rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
76 Adding Semantics to Linked Data Ontology Web Language (OWL) Ontology Web Language OWL expresses a small subset of First Order Logic defines a structure (classes, properties, datatypes) and axioms inference based on OWL is restricted in this framework but can be extremely complex Ontologies can be hard full ontology-based application is a complex system hard to implement and run three layers of OWL are defined (in decreasing levels of complexity) OWL sublanguages OWL Full: superset of RDFS, but an OWL Full ontology can be undecidable OWL DL (Description Logic): maximal subset of OWL Full but decidable reasoning procedures OWL Lite: minimal, useful subset, easily implementable Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
77 Adding Semantics to Linked Data Ontology Web Language (OWL) Ontology Web Language: OWL class construction content enumeration intersection, union, complementation property restrictions property restrictions value constraints (interpreted as restrictions on value ranges) cardinality constraints: maximum, minimum, exact property characterization symmetric, transitive, functional, etc. differentiation between datatype and object properties term equivalence classes are equivalent (owl:equivalentclass) or disjoint (owl:disjointwith) properties are equivalent (owl:equivalentproperty) or inverse (owl:inverseof) URIs refer to the same (owl:sameas) or distinct individual (owl:differentfrom) Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
78 Adding Semantics to Linked Data Ontology Web Language (OWL) Ontology Web Language: OWL class construction content enumeration intersection, union, complementation property restrictions property restrictions value constraints (interpreted as restrictions on value ranges) cardinality constraints: maximum, minimum, exact property characterization symmetric, transitive, functional, etc. differentiation between datatype and object properties term equivalence classes are equivalent (owl:equivalentclass) or disjoint (owl:disjointwith) properties are equivalent (owl:equivalentproperty) or inverse (owl:inverseof) URIs refer to the same (owl:sameas) or distinct individual (owl:differentfrom) rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
79 Adding Semantics to Linked Data Ontology Web Language (OWL) Ontology Web Language: OWL class construction content enumeration intersection, union, complementation property restrictions property restrictions value constraints (interpreted as restrictions on value ranges) cardinality constraints: maximum, minimum, exact property characterization symmetric, transitive, functional, etc. differentiation between datatype and object properties term equivalence classes are equivalent (owl:equivalentclass) or disjoint (owl:disjointwith) properties are equivalent (owl:equivalentproperty) or inverse (owl:inverseof) URIs refer to the same (owl:sameas) or distinct individual (owl:differentfrom) rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
80 Adding Semantics to Linked Data Ontology Web Language (OWL) Ontology Web Language: OWL class construction content enumeration intersection, union, complementation property restrictions property restrictions value constraints (interpreted as restrictions on value ranges) cardinality constraints: maximum, minimum, exact property characterization symmetric, transitive, functional, etc. differentiation between datatype and object properties term equivalence classes are equivalent (owl:equivalentclass) or disjoint (owl:disjointwith) properties are equivalent (owl:equivalentproperty) or inverse (owl:inverseof) URIs refer to the same (owl:sameas) or distinct individual (owl:differentfrom) rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
81 Adding Semantics to Linked Data Ontology Web Language (OWL) Ontology Web Language: OWL class construction content enumeration intersection, union, complementation property restrictions property restrictions value constraints (interpreted as restrictions on value ranges) cardinality constraints: maximum, minimum, exact property characterization symmetric, transitive, functional, etc. differentiation between datatype and object properties term equivalence classes are equivalent (owl:equivalentclass) or disjoint (owl:disjointwith) properties are equivalent (owl:equivalentproperty) or inverse (owl:inverseof) URIs refer to the same (owl:sameas) or distinct individual (owl:differentfrom) rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
82 Linked Data LifeCycle Linked Open Data Cloud: The Challenge Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
83 The Challenge Linked Data LifeCycle Classical data management approaches assume complete control over schema, data and data generation But the Web is distributed and open control is lacking Linked Data LifeCycle Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
84 Outline Linked Data LifeCycle Extraction 1 Going from the Web of Documents to the Web of Data 2 Web Architecture Items of Interest Naming Resources: URIs Resource Description Framework (RDF) 3 Adding Semantics to Linked Data A Short Introduction RDF Vocabulary Description Language (RDFS) Ontology Web Language (OWL) 4 Linked Data LifeCycle Extraction Interlinking/Fusing Storage/Querying 5 Conclusions rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
85 Linked Data LifeCycle Extraction Extraction Extraction: refers to the process of extracting data from unstructured and structured sources and representing it in the RDF data model Extraction from Unstructured Sources: sub-disciplines of NLP Named Entity Extraction: extracting entity labels from text Keyword/Keyphrase Extraction: recognition of central topics Relationship Extraction: mining the properties which link the entities and keywords described in the input data Linked Data Context: extraction of suitable URIs for the discovered entities and relationships extracted from knowledge bases such as DBPedia by comparing the name of the entity and relationship with the label or accompanied comments of the DBPedia entities Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
86 Linked Data LifeCycle Extraction Extraction Extraction: refers to the process of extracting data from unstructured and structured sources and representing it in the RDF data model Extraction from Unstructured Sources: sub-disciplines of NLP Named Entity Extraction: extracting entity labels from text Keyword/Keyphrase Extraction: recognition of central topics Relationship Extraction: mining the properties which link the entities and keywords described in the input data Linked Data Context: extraction of suitable URIs for the discovered entities and relationships extracted from knowledge bases such as DBPedia by comparing the name of the entity and relationship with the label or accompanied comments of the DBPedia entities rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
87 Linked Data LifeCycle Extraction Extraction Extraction: refers to the process of extracting data from unstructured and structured sources and representing it in the RDF data model Extraction from Unstructured Sources: sub-disciplines of NLP Named Entity Extraction: extracting entity labels from text Keyword/Keyphrase Extraction: recognition of central topics Relationship Extraction: mining the properties which link the entities and keywords described in the input data Linked Data Context: extraction of suitable URIs for the discovered entities and relationships extracted from knowledge bases such as DBPedia by comparing the name of the entity and relationship with the label or accompanied comments of the DBPedia entities rini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
88 Extraction Linked Data LifeCycle Extraction Extraction from Structured Sources (relational and XML) R2RML Relational to RDF Mapping Language Virtuoso SPARQL EndPoint Relational Database (RDB) RDF Graph (set of RDF triples) Query Access (SPARQL) Entity Level Access (HTTP GET) RDB 2 RDF Access via dump (HTTP GET) Relational to RDF Extraction Irini Fundulaki (Institute of Computer Science - FORTH) Introducing Linked Data March 29, / 80
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