1. ‫أكاديمية الحكومة اإللكترونية الفلسطينية‬
The Palestinian eGovernment Academy
www.egovacademy.ps
Tutorial II: Data Integration and Open Information Systems
Session 15.1
The Data Web and Linked Data
Dr. Mustafa Jarrar
University of Birzeit
mjarrar@birzeit.edu
www.jarrar.info
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2. About
This tutorial is part of the PalGov project, funded by the TEMPUS IV program of the
Commission of the European Communities, grant agreement 511159-TEMPUS-1-
2010-1-PS-TEMPUS-JPHES. The project website: www.egovacademy.ps
Project Consortium:
Birzeit University, Palestine
University of Trento, Italy
(Coordinator )
Palestine Polytechnic University, Palestine Vrije Universiteit Brussel, Belgium
Palestine Technical University, Palestine
Université de Savoie, France
Ministry of Telecom and IT, Palestine
University of Namur, Belgium
Ministry of Interior, Palestine
TrueTrust, UK
Ministry of Local Government, Palestine
Coordinator:
Dr. Mustafa Jarrar
Birzeit University, P.O.Box 14- Birzeit, Palestine
Telfax:+972 2 2982935 mjarrar@birzeit.eduPalGov © 2011
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3. © Copyright Notes
Everyone is encouraged to use this material, or part of it, but should
properly cite the project (logo and website), and the author of that part.
No part of this tutorial may be reproduced or modified in any form or by
any means, without prior written permission from the project, who have
the full copyrights on the material.
Attribution-NonCommercial-ShareAlike
CC-BY-NC-SA
This license lets others remix, tweak, and build upon your work non-
commercially, as long as they credit you and license their new creations
under the identical terms.
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4. Tutorial Map
Topic h
Intended Learning Objectives
Session 1: XML Basics and Namespaces 3
A: Knowledge and Understanding
Session 2: XML DTD’s 3
2a1: Describe tree and graph data models.
Session 3: XML Schemas 3
2a2: Understand the notation of XML, RDF, RDFS, and OWL.
2a3: Demonstrate knowledge about querying techniques for data Session 4: Lab-XML Schemas 3
models as SPARQL and XPath. Session 5: RDF and RDFs 3
2a4: Explain the concepts of identity management and Linked data. Session 6: Lab-RDF and RDFs 3
2a5: Demonstrate knowledge about Integration &fusion of Session 7: OWL (Ontology Web Language) 3
heterogeneous data. Session 8: Lab-OWL 3
B: Intellectual Skills Session 9: Lab-RDF Stores -Challenges and Solutions 3
2b1: Represent data using tree and graph data models (XML & Session 10: Lab-SPARQL 3
RDF). Session 11: Lab-Oracle Semantic Technology 3
2b2: Describe data semantics using RDFS and OWL. Session 12_1: The problem of Data Integration 1.5
2b3: Manage and query data represented in RDF, XML, OWL. Session 12_2: Architectural Solutions for the Integration Issues 1.5
2b4: Integrate and fuse heterogeneous data. Session 13_1: Data Schema Integration 1
C: Professional and Practical Skills Session 13_2: GAV and LAV Integration 1
2c1: Using Oracle Semantic Technology and/or Virtuoso to store Session 13_3: Data Integration and Fusion using RDF 1
and query RDF stores. Session 14: Lab-Data Integration and Fusion using RDF 3
D: General and Transferable Skills
2d1: Working with team. Session 15_1: Data Web and Linked Data 1.5
2d2: Presenting and defending ideas. Session 15_2: RDFa 1.5
2d3: Use of creativity and innovation in problem solving.
2d4: Develop communication skills and logical reasoning abilities. Session 16: Lab-RDFa 3
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5. Module ILOs
After completing this module students will be
able to:
-Explain the concepts of identity management and
linked data.
- Understand basic concepts of the Data Web.
-Integrate and fuse heterogeneous data.
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6. Semantic/ Data Web/ Web 3.0?
“The goal of the Semantic Web is
to create a universal medium for the
exchange of DATA”, W3C.
“The Semantic Web is a web of data, in
some ways like a global database”,
Tim Berners-Lee – Inventor of the WWW.
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7. Web of Data
• The Data Web envisions the web as a world-wide
interlinked structured data.
• The Web as we know it today is a global information space
of linked documents.
• The same vision is applied to data: publishing and
connecting structured data on the web.
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8. Classical Web
Diagram Source: Christian Bizer
• The classical web a global
information space of linked
documents.
• Primary Units of the hypertext
Web are:
– HTML Documents,
– Connected by Hyperlinks
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9. The challenge
• The problem is that the information on the
classical web is not structured.
– Programs cannot use such information in a useful way.
• The Solution is to increase the structure of
published information.
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10. Web APIs and Mashups
Diagram Source: Christian Bizer
• Many major data sources such as Amazon, Yahoo!, eBay,
and Google provide access to their data through APIs.
• Currently, programmableweb.com lists 3891 APIs and
6101 mashups (up to 14. Sep 2011).
API
API MashUp
API
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11. Web APIs and Mashups
Picture Source: Christian Bizer
• However,
– APIs provide proprietary interfaces,
– Data retrieved from these APIs is represented using different formats
(different data models).
– Mashups created using these APIs are based on a fixed set of data
sources. This is because entities in different APIs are not linked.
– You can not set hyperlinks between entities.
APIs separates
data
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12. Beyond Web APIs and Mashups:
The Data Web and Linked Data
• The Data Web envisions the web as a world-wide
interlinked structured data.
• Linked data refers to the set of best practices for
publishing and connecting structured data on the web.
• Linked data best practices has lead to the extension of the
web connecting data from diverse domains such as:
– People, companies, books, scientific publications, films, music, television
and radio programs, genes, proteins drugs, clinical trials, online
communities, statistical and scientific data, reviews, …
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13. The Data Web and Linked Data
Diagram Source: Christian Bizer
• While the primary units of the hypertext Web are HTML documents
connected by un-typed Hyperlinks, Linked Data relies on documents
containing data in RDF. However, rather than simply connecting these
documents, Linked Data uses RDF to make typed statements that link
arbitrary things in the world.
• The result is a web of things in the world, described by data on the Web
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14. The Data Web and Linked Data
Berners-Lee (2006) outlined a set of 'rules' for publishing
data on the Web in a way that all published data becomes
part of a single global data space:
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
information, using the standards (RDF, SPARQL)
4. Include links to other URIs, so that they can discover
more things
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15. Properties of the Web of Linked Data
• Anyone can publish data to the Web of Linked Data
• Entities are connected by links
– creating a global data graph that spans data sources and enables
the discovery of new data sources.
• Data is self-describing
– If an application encounters data represented using an unfamiliar
vocabulary, the application can resolve the URIs that identify
vocabulary terms in order to find their RDFS or OWL definition.
• The Web of Data is open
– meaning that applications can discover new data sources at run-
time by following links.
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16. Realization: Linking Open Data Project
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17. Realization: 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
• By September 2010 the cloud had grown to 25
billion RDF triples, interlinked by around 395
million RDF links.
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18. Linking Data
• How are same entities described in different datasets linked?
• AGAIN: By linking the Global Identifier, that is, the URI!
• Let’s have a look at real examples from real datasets:
<http://dbpedia.org/resource/Bethlehem> owl:sameAs
<http://sws.geonames.org/284315/>
• Linking the entity “Bethlehem” between the DBPedia dataset and the Geonames dataset
in the Linking Open Data cloud.
• This is done by linking the URIs of “Bethlehem” in both datasets using owl:sameAs.
<http://dbpedia.org/resource/Tim_Berners-Lee> owl:sameAs
<http://www4.wiwiss.fu-berlin.de/dblp/resource/person/100007>
• Linking the entity “Tim Berners-Lee” between the DBPedia dataset and the DBLP dataset .
• This is done by linking the URIs of “Tim Berners-Lee” in both datasets using owl:sameAs.
NOTE: The student is encouraged to visit the URIs specified above.
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19. Resources
 http://dbpedia.org/resource/Bethlehem
(Bethlehem URI in DBPedia)
http://sws.geonames.org/284315/ 
(Bethlehem URI in Geonames)
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20. Applications
Diagram Source: Christian Bizer
• What Can I do with this?
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21. Let’s draw a graph of our example!
v:Person
“George Mousa”
v:nickname
“Geno”
v:Address
v:city
“Nablus”
“Palestine”
“George Mousa”
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22. References
• Christian Bizer: The Emerging Web of Linked Data. Presentation at
SRI International, Artificial Intelligence Center. Menlo Park, USA. 2009.
• W3C: www.w3c.org
• Linking Open Data:
http://www.w3.org/wiki/SweoIG/TaskForces/CommunityProjects/LinkingOpenData
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