Linked Data Tutorial presented for the open data community on February 16., 2012, Prague.

1. February 16, 2012
Linked Data Tutorial*
Tomáš Knap, Jindřich Mynarz, Martin Nečaský, Jakub Stárka
Faculty of Mathematics and Physics
Charles University in Prague
(*Partially based on slides of Chris Bizer [8])

2. Motivation
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3. Motivational Scenario
Basic Public
Employees Departments Budget Expenses
data contracts
WWW
Business Buyer‘s
page of the ÚFIS ISVZUS gov.cz
Register Profile
institution
Data Consumer: Show me suppliers of the public
contracts for the Ministry of Finance (MF) in the region
Liberec. Show me the data on the Google maps in
iPhone. For every public contract, I am also looking for
the aggregation of all the payments made by MF, link
to their budget and responsible person.
• Where can I get the data about public
contracts, responsible persons, expenses, and
budget of MF?
• How should I aggregate and link the data?
• How can16th February 2012 | data Data the map?
I observe the Linked on Tutorial 3

4. Current Common Practise
Basic Public
Employees Departments Budget Expenses
data contracts
WWW
Business Buyer‘s
page of the ÚFIS ISVZUS gov.cz
Register Profile
institution
3 - Expenses ?
2 – MF public 1 – MF public
contracts + contracts
employees
? Consumer did
not discovered
?
Information Integration very time consuming, boring, and ineffective!
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5. Linked Data - Basics
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6. Linked Data
• Set of best practices for publishing structured
data on the Web in accordance with the
general architecture of the Web
 using Semantic Web technologies and standards
 Semantic Web is the goal, Linked Data provides
the means to reach the goal
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7. Linked Data Principles
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]
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8. Architecture of the Classic Web
 Single global information space
 Small set of simple standards:
‒ HTTP URI
• globally unique ID
• retrieval mechanism
‒ HTML as document format
‒ Hyperlinks to connect everything
 Applications work on top of the
complete information space
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9. Web 2.0 APIs and Mashups
 No single global dataspace
 Shortcomings:
‒ API have proprietary interfaces
‒ No hyperlinks between data items
within different APIs
‒ Mashups are based on a fixed set
of data sources
Web APIs slice the Web into Walled Gardens!
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10. Linked Data
• Extend the Web with a single global dataspace
 By using RDF to publish structured data on the Web
 By setting links between data items within different data
sources.
 Physically distributed, behaves like single dataspace
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11. RDF Data Model
• Flexible graph-based data model [2]
• HTTP URIs take the role of global primary keys.
 pd:cygri = http://richard.cyganiak.de/foaf.rdf#cygri
 dbpedia:Berlin = http://dbpedia.org/resource/Berlin
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12. Resolving URIs over the Web
• The HTTP protocol brings together
identification and retrieval
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13. Following Links deeper into the Web
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14. Pubby – Linked Data Browser
http://dbpedia.org/page/Český_Krumlov
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15. Properties of the Web of Linked Data
• Global, distributed data space build on a simple
set of standards
 RDF, URIs, HTTP
• Entities are connected by links
 creating a global data graph that spans data sources
 enables the discovery of new data sources
• Data-coexistence
 Everyone can publish data to the Web of Linked Data
 Everyone can express their personal view on things
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16. Linked Data Deployment on the Web..
Is it real?
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17. 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 sources
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18. Linked Data Cloud 2007
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19. Linked Data Cloud 2009
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20. Linked Data Cloud 2011
http://richard.cyganiak.de/2007/10/lod/lod-datasets_2011-09-19_colored.pdf
http://thedatahub.org/
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21. More Statistics
http://stats.lod2.eu/stats
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22. Uptake in Governmental Domain
• The EU is publishing LinkedData
 EuroStat
‒ http://estatwrap.ontologycentral.com/
• National efforts
 The Government is releasing public data
‒ http://data.gov.uk/
‒ Lots of initiatives in Great Britain
 Budget in Germany
‒ http://bund.offenerhaushalt.de/
 Open Data in Catalonia
‒ http://opendata.gencat.cat/en/dades-obertes.html
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23. Data.gov.uk
http://data.gov.uk/organogram/cabinet-office
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24. Linked Data Applications
Linked Data Browsers
? ? ??
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25. Search Engines - Sig.ma
http://sig.ma
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26. Mashups – Public Contracts On the Map
http://gd.projekty.ms.mff.cuni.cz:2021/new/map.html
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27. Mashups – Crime, Transport, Education
http://apps.seme4.com/see-uk/
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28. Other Applications
• Browsers:
 Disco Hyperdata Browser
‒ http://www4.wiwiss.fu-berlin.de/rdf_browser/
 OpenLink RDF Browser
‒ http://ode.openlinksw.com/
• Search Engines
 Falcons
‒ http://ws.nju.edu.cn/falcons/
 Watson
‒ http://watson.kmi.open.ac.uk/WatsonWUI/
• Mashups
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29. Linked Data Applications - Summary
Linked Data Browsers Search Engines Linked Data Mashups
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30. Publishing Linked Data
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31. Publishing Tasks – Bizer 38
• 1. Make data available as RDF via HTTP
 Requires ways to serialize RDF data model
• 2. Set RDF links pointing at other data sources
• 3. Make your data self-descriptive
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32. RDF/XML
• W3C Recommendation, 2004 [2]
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33. Turtle Syntax
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix dataModel: <http://www.w3.org/2000/10/swap/pim/contact#> .
@prefix myContact: <http://www.w3.org/People/EM/contact#> .
myContact:me rdf:type dataModel:Person ;
dataModel:fullName "Eric Miller".
dataModel:mailbox <mailto:em@w3.org>.
dataModel:personalTitle "Dr.".
• W3C Team Submission, 2011, [4]
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34. RDFa
• A way to directly add RDF to XHTML pages
 Provides new attributes to handle additional
markup
• W3C Recommendation, 2008 [5]
• HTML is not extendable
• most RDFa parsers will recognize RDFa attributes in any
version of HTML
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35. RDFa
• Provides new attributes to handle additional
markup, reuses existing
 About, resource, …
 Href, src, …
• Used with any supported element, prefered:
 Span, div (in the body)
 a (linking element)
 Meta, link (in the header)
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36. RDFa Example
• XHTML page http://example.com/alice/posts/42
• Original XHTML code
All content on this site is licensed under <a
href="http://cc.org/licenses/by/3.0/"> a Creative Commons License </a>.
• XHTML + RDFa
All content on this site is licensed under <a rel=“cc:license"
href="http://cc.org/licenses/by/3.0/"> a Creative Commons License </a>.
• RDF triples destilled from XHTML+RDFa
<http://example.com/alice/posts/42> cc:license
<http://cc.org/licenses/by/3.0/>.
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37. RDF store + Linked Data Interface
• Virtuoso + pubby
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38. D2R server
• A way how to publish data in relational databases as
Linked Data
• Requests from the Web are rewritten into SQL queries
via the mapping.
 on-the-fly translation
 eliminates the need for replicating the data into a
dedicated RDF triple store.
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39. Publishing Tasks
1. Make data available as RDF via HTTP
2. Set RDF links pointing at other data sources
3. Make your data self-descriptive
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40. 2. Set RDF links
<http://dbpedia.org/resource/Berlin>
owl:sameAs
<http://sws.geonames.org/2950159> .
• There are tools to help you generate links
 Silk [6]
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41. Publishing Tasks
1. Make data available as RDF via HTTP
2. Set RDF links pointing at other data sources
3. Make your data self-descriptive
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42. 3. Make your data self-descriptive
• Increase the usefulness of your data and ease
data integration
• Aspects of self-descriptiveness
 1. Reuse terms from common vocabularies
 2. Enable clients to retrieve the schema
 3. Publish schema mappings for proprietary terms
 4. Metadata
‒ Provide provenance metadata
‒ Provide licensing metadata
‒ Provide data-set-level metadata using voiD
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43. About Vocabularies
• We have to be able to define the meaning of
the subject, properties
 Vocabularies, e.g. Public contracts ontology
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44. Public Contracts Ontology
http://purl.org/procurement/public-contracts#
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45. RDFS
• RDFS = RDF Schema
 W3C recommendation
‒ http://www.w3.org/TR/rdf-schema/
 Vocabulary for RDF
‒ Definition of classes
• is:Student rdf:type rdfs:Class
‒ Definition of properties
• is:name rdf:type rdfs:Property
‒ Domains and ranges of properties
• is:name rdfs:domain is:Student
• is:name rdfs:range xsd:string
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46. OWL
• OWL = Web Ontology Language
 W3C recommendation
‒ http://www.w3.org/TR/owl2-overview/
 Ontologies
‒ More complex constructs
• Class or property equivalences
• Cardinality restrictions
• …
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47. 3. Make your data self-descriptive
• Increase the usefulness of your data and ease
data integration
• Aspects of self-descriptiveness
 1. Reuse terms from common vocabularies
 2. Enable clients to retrieve the schema
 3. Publish schema mappings for proprietary terms
 4. Metadata
‒ Provide provenance metadata
‒ Provide licensing metadata
‒ Provide data-set-level metadata using voiD
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48. 3.1 Reuse Terms from Common
vocabularies
• Common Vocabularies
 Friend-of-a-Friend for describing people and their social network
 SIOC for describing forums and blogs
 SKOS for representing topic taxonomies
 Organization Ontology for describing the structure of organizations
 GoodRelations provides terms for describing products and business
entities
 Music Ontology for describing artists, albums, and performances
 Review Vocabulary provides terms for representing reviews
• Common sources of identifiers (URIs) for real world objects
 LinkedGeoData and Geonames locations
 GeneID and UniProt life science identifiers
 DBpedia wide range of things
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49. 3.2 Enable Clients to retrieve the Schema
• Clients can resolve the URIs that identify vocabulary
terms in order to get their RDFS or OWL definitions.
• If we discover in data URI:
<http://opendata.cz/data/p6/contract/ocz_art_5161>
http://purl.org/procurement/public-contracts#awardDate
"2011-11-11"^^<http://www.w3.org/2001/XMLSchema#date> ;
• We resolve the URI and get the definition:
RDFS or OWL definition
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50. 3.3 Publish Schema Mappings
pc:Tender a owl:Class ;
rdfs:subClassOf gr:Offering .
pc:AwardCriterion a owl:Class ;
owl:equivalentClass loted:AwardCriteria.
• Simple Mappings:
 rdfs:subClassOf, rdfs:subPropertyOf
 owl:equivalentClass, owl:equivalentProperty
• Complex mappings – R2R [7]
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51. 3.4 Metadata
• Licenses
• Data Provenance
• Dataset description
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52. Consuming Linked Data
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53. Overview
• URI -> Description
 Pubby
• Keyword -> Description
 Sig.ma
• SPARQL query language [8]
 SQL for RDF databases
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54. SPARQL Example
• Contracts of the given supplier
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55. SPARQL Example - Result
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56. Issues of the Simple Consuming Scenarios
• How to aggregate the data if the links are
missing, the data models (ontologies) differs?
• How to deal with data quality?
 Everybody can say whatever he wants!
• Solution: We are developing an infrastructure
for cleaning, linking, and aggregating Linked
Data
 Reusing existing technologies, such as Silk
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57. ODCleanStore
• Cleaning the data • Smart data consuming
 Custom cleaners  Data aggregation (due to
• Linking the data links, ontology
mappings)
 Silk
 Conflict resolution
• Graphical user interface  Data provenance
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58. Motivational Scenario - Recall
Basic Public
Employees Departments Budget Expenses
data contracts
WWW
Business Buyer‘s
page of the ÚFIS ISVZUS gov.cz
Register Profile
institution
Data Consumer: Show me suppliers of the public
contracts for the Ministry of Finance (MF) in the
region Liberec. Show the data on the Google maps
in iPhone. For every public contract, I am looking
for the aggregation of all the payments made by
MF, link to their budget and responsible person.
• Where can I get the data about public
contracts, responsible persons, expenses, and
budget of MF?
• How should I aggregate and link the data?
• How can I observer the data on the map?
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59. Goal
Basic Public
Employees Departments Budget Expenses
data contracts
WWW
Business Buyer‘s
page of the ÚFIS ISVZUS gov.cz
Register Profile
institution
ODCleanStore
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60. Conclusions
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61. Linked Data vs. Open Data
Open data are raw data, which are freely
available on the Web to:
• Everyone
• Anytime
• For whatever purpose
• Open data – 3 stars!
 4th star: Single and flexible model (RDF) is missing
 5th star: Links
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62. Conclusions and Take Away Message
The Power Of Linked Data (5 star data)
• Web-scale data publishing with web-based discovery
mechanisms
• Distributed annotation – make comments about
observations, data series, points on the map
• Easy to reuse
 Huge potential when connecting to the cloud, linking the
data, the benefits are growing as the amount of data
published as Linked Data is increasing
• Integration on data level
• Easy to extend (new data properties as required, no
need to be planned up-front)
• Easy to merge – no name clashes!
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63. Future Steps
• If you managed to get interesting data, try to
publish them as Linked Data!
 We can help you with the whole lifecycle – creating,
publishing, maintenance of the data
 Just create RDF data, we will publish it for you
 Just let us know (send us the data), we can publish it
 Publish data in the same way, but use global
identifiers according to LD principles
• When the infrastructure (ODCleanStore) is ready,
you can just send us the RDF data using web
service and we will do all the other stuffs –
clean, link, and provide aggregated views.
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64. Thank You!
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65. References
• Textbook: Tom Heath, Christian Bizer: Linked Data:
Evolving the Web into a Global Data Space.
http://linkeddatabook.com/
• [2] http://www.w3.org/TR/rdf-primer/
• [3] http://www.w3.org/TR/REC-rdf-syntax/
• [4] http://www.w3.org/TeamSubmission/turtle/
• [5] http://www.w3.org/TR/rdfa-syntax/
• [6] http://www4.wiwiss.fu-berlin.de/bizer/silk/
• [7] http://www.w3.org/TR/rdf-sparql-query/
• [8] http://static.lod2.eu/isslod/Bizer-LOD2-
IndianSummerSchool.pdf
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