linked data
TRANSCRIPT
Linked Data -
Evolving the Web into a Global Dataspace
Anja Jentzsch - @anjeve Hasso Plattner Institute, Potsdam, Germany
!!!
Open Data Lecture, HTW Berlin 2015/01/12
Architecture of the classic Web
B C
HTMLHTML
Web Browsers
Search Engines
hyper- links
A
HTML
• Single global document space • Small set of simple standards • HTML as document format • HTTP URLs as globally unique IDs !
• Retrieval mechanism: Hyperlinks to connect everything
Web 2.0 APIs and Mashups
No single global dataspace !Shortcomings 1. APIs have proprietary interfaces 2. Mashups are based on a fixed set of
data sources 3. No hyperlinks between data items
within different APIsWeb API
A
Mashup
Web API
B
Web API
C
Web API
D
Web APIs slice the Web into Walled Gardens
Image: Bob Jagensdorf, http://flickr.com/photos/darwinbell/, CC-BY
Extend the Web with a single global dataspace 1. by using RDF to publish structured data on the Web 2. by setting links between data items within different data sources
Linked Data
B C
RDF
RDF Links
A D E
RDF Links
RDF Links
RDF Links
RDF
RDF
RDF
RDF
RDF RDF
RDF
RDF
RDF
Linked Data Principles
Set of best practices for publishing structured data on the Web in accordance with the general architecture of the Web.
1. Use URIs as names for things. 2. Use HTTP 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, http://www.w3.org/DesignIssues/LinkedData.html, 2006
The RDF Data Model
Anja Jentzsch
dbpedia:Berlin
foaf:name
foaf:based_near
foaf:Personrdf:typens:anja
Data Items are identified with HTTP URIs
ns:anja = http://www.anjeve.de#anjadbpedia:Berlin = http://dbpedia.org/resource/Berlin
foaf:name
foaf:based_near
foaf:Personrdf:typens:anja
dbpedia:Berlin
Anja Jentzsch
Resolving URIs over the Web
dp:Cities_in_Germany
3.499.879dp:population
skos:subjectdbpedia:Berlin
foaf:name
foaf:based_near
foaf:Personrdf:typens:anja
Anja Jentzsch
Dereferencing URIs over the Web
dbpedia:Hamburg
dbpedia:Muenchen
skos:subject
skos:subjectdp:Cities_in_Germany
3.499.879dp:population
skos:subjectdbpedia:Berlin
foaf:name
foaf:based_near
foaf:Personrdf:typens:anja
Anja Jentzsch
RDF Representation Formats
• RDF/XML <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:foaf="http://xmlns.com/foaf/0.1/"> <foaf:Person rdf:about="http://anjeve.de#anja"> <foaf:name>Anja Jentzsch</foaf:name> </foaf:Person>
!• RDF N-Triples <http://anjeve.de#anja> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person> . <http://anjeve.de#anja> <http://xmlns.com/foaf/0.1/name> „Anja Jentzsch“ .
RDF Representation Formats
!!!<http://anjeve.de#anja> <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://xmlns.com/foaf/0.1/Person>. !
<Subject> <Predicate> <Object> .
!In the end it‘s all triples!
foaf:Personrdf:typens:anja
Properties of the Web of Linked Data
• Global, distributed dataspace build on a simple set of standards • RDF, URIs, HTTP
• Entities are connected by links • creating a global data graph that spans data sets and • enables the discovery of new data sources
• Provides for data-coexistence • Everyone can publish data to the Web of Linked Data • Everyone can express their personal view on things • Everybody can use the vocabularies/schemas that they like
W3C Linking Open Data Project
• Grassroots community effort to • publish existing open license datasets as Linked Data on the Web • interlink things between different data sets
LOD Data Sets on the Web: May 2007
• 12 data sets • 500+ million RDF triples • 120,000+ RDF links between data sets
LOD Data Sets on the Web: November 2007
• 28 data sets
LOD Data Sets on the Web: September 2008
• 45 data sets • 2+ billion RDF triples
LOD Data Sets on the Web: July 2009
• 95 data sets • 6.5+ billion RDF triples
LOD Data Sets on the Web: September 2010
• 203 data sets • Over 24,7 billion RDF triples • Over 436 million RDF links between data sets
LOD Data Sets on the Web: September 2011
• 295 data sets • 31+ billion RDF triples • 504+ million RDF links between data sets http://lod-cloud.net
LOD Data Sets on the Web: August 2014
http://lod-cloud.net
• 1,019 data sets • 84+ billion RDF triples • 808+ million RDF links between data sets
LOD Data Set statistics as of 08/2014
LOD Cloud Data Catalog on the Data Hub • http://datahub.io/group/lodcloud More statistics • http://lod-cloud.net/state/
Heterogeneity on the Web of Data
• The Web of Data is heterogeneous • Many different vocabularies are in use (469 as of January 2015) • Different data formats • Many different ways to represent the same information
DBpedia – The Hub on the Web of Data
• DBpedia is a joint project with the following goals • extracting structured information from Wikipedia • publish this information under an open license on the Web • setting links to other data sources
!• Partners
• Universität Mannheim (Germany) • Universität Leipzig (Germany) • OpenLink Software (UK)
Extracting structured data from Wikipedia
Extracting structured data from Wikipediadbpedia:Berlin rdf:type dbpedia-owl:City ,
dbpedia-owl:PopulatedPlace , dbpedia-owl:Place ; rdfs:label "Berlin"@en , "Berlino"@it ; dbpedia-owl:population 3499879 ; wgs84:lat 52.500557 ; wgs84:long 13.398889 .
! dbpedia:SoundCloud dbpedia-owl:location dbpedia:Berlin .
• access to DBpedia data: • dumps • SPARQL endpoint • Linked Data interface
The DBpedia Data Set
• Information on more than 4.58 million “things” • 1,445,000 persons • 241,000 organisations • 735,000 places • 123,000 music albums • 87,000 movies • 251,000 species
• overall more than 3 billion RDF triples • title and abstract in 125 different languages • 25,200,000 links to images • 29,800,000 links to external web pages • 50,000,000 links to other Linked Data sets
DBpedia Mappings
• since March 2010 collaborative editing of • DBpedia ontology • mappings from Wikipedia infoboxes and tables to DBpedia ontology
• curated in a public wiki with instant validation methods • http://mappings.dbpedia.org
• multilingual mappings to the DBpedia ontology: • ar, be, bg, bn, ca, cs, cy, de, el, en, eo, es, et, eu, fr, ga, hi, hr, hu, id, it, ja, ko, nl,
pl, pt, ru, sk, sl, sr, tr, ur, zh !
• allows for a significant increase of the extracted data’s quality • each domain has its experts
DBpedia Use Cases
1. Hub for the growing Web of Data 2. Improvement of Wikipedia search 3. Data source for applications and mashups 4. Text analysis and annotation
DBpedia Mobile
• displays Wikipedia data on a map • aggregates different data sources
Faceted Wikipedia Search
• faceted browsing and free text search
Uptake in the Government Domain
• The EU is pushing Linked Data (LOD2, LATC, EuroStat) • W3C eGovernment Interest Group
Uptake in the Library Community• Libraries publishing Linked Data
• Library of Congress (subject headings) • German National Library (PND dataset and subject headings) • Swedish National Library (Libris - catalog) • Hungarian National Library (OPAC and Digital Library) • Europeana
• W3C Library Linked Data Incubator Group • Goals:
• Integrate library catalogs on global scale • Interconnect resources between repositories (by topic, by location, by
historical period, by ...)
Uptake in Life Sciences
• W3C Linking Open Drug Data Effort • Bio2RDF Project • Allen Brain Atlas !!!!!!
• Goal: Smoothly integrate internal and external data in a pay-as-you-go-fashion.
Uptake in the Media Industry• Publish data as Linked Data or RDFa • Goal: Drive traffic to websites via
search engines
Linked Data Applications
Linked Data Browsers
• Tabulator Browser (MIT, USA) • Marbles (MES / Uni Mannheim, DE) • OpenLink RDF Browser (OpenLink, UK) • Zitgist RDF Browser (Zitgist, USA) • Humboldt (HP Labs, UK) • Disco Hyperdata Browser (Uni Mannheim, DE) • Fenfire (DERI, Irland)
Web of Data Search Engines
• Sig.ma (DERI, Ireland) • Falcons (IWS, China) • Swoogle (UMBC, USA) • VisiNav (DERI, Ireland) • Watson (Open University, UK)
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Finding Linked Data sets
• Search engines • find data sets based on keywords !
• Data catalogs / directories • explore data sets and faceted search !
• Data Marketplaces • explore and consume data sets
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Is your data 5 star?
Tim Berners-Lee, http://www.w3.org/DesignIssues/LinkedData.html, 2010
Make your data available on the Web (in whatever format) under an open license. Make it available as structured data (e.g., Excel instead of image scan of a table) so that it can be reused. Use non-proprietary, open formats (e.g., CSV instead of Excel). !Use URIs to identify things, so that people can point at your stuff and serve RDF from it. Link your data to other data to provide context.
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Economic Opportunities
• Huge reservoir of free content which can be used to provide background facts about
• places,
• people,
• topics
• …
Background Facts
schema.org
• jointly proposed vocabularies for embedding data into HTML pages (Microdata) • available since June 2011
Options for Search Companies
• New vertical search engines • Sig.ma, FalconS, …
• Google Knowledge Graph • 1.6 billion facts (2014)
• Yahoo • Improving text search with background knowledge
Lower Data Integration Costs
Overall data integration effort is split between: !
• Data Publisher – publishes data as RDF – sets identity links – reuses terms or publishes mappings
• Third Parties – set identity links pointing at your data – publish mappings to the Web
• Data Consumer – has to do the rest – using record linkage and schema matching
techniques
Conclusion
• The Web of Data is growing fast • Linked Data provides a standardized data access interface • Allows for easy data integration, enhancement and browsing • Web search is evolving into query answering
• Search engines will increasingly rely on structured data from the Web • Next step: Linked Data within enterprises
• Alternative to data warehouses and EAI middleware • Advantages: schema-less data model, pay-as-you go data integration
Thanks!
References: • Tom Heath, Christian Bizer : Linked Data: Evolving the Web into a Global Data Space
http://linkeddatabook.com/ • Linking Open Data Project Wiki
http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData
Email: [email protected] Twitter : @anjeve