1. ‫أكاديمية الحكومة اإللكترونية الفلسطينية‬
The Palestinian eGovernment Academy
www.egovacademy.ps
Tutorial II: Data Integration and Open Information Systems
Session 12.1
The problem of Data Integration
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:
- Understand the importance of Data Integration.
- Understand the problems and challenges of Data Integration.
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6. Example from the government Domain
• Consider all interactions with government agencies in order to register
a new business in Palestine.
• Example: Establishing a new Radio Station.
Ministry of Ministry of Ministry of Chamber of
Ministry of
Information National Economy Finance Commerce
Telecom
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7. Example from the government Domain
• Consider when the business evolves or changes.
• Example: Changing the address of the radio station.
– Address must be changed in 5 different databases.
Ministry of Ministry of Ministry of Chamber of
Ministry of
Information National Economy Finance Commerce
Telecom
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8. Example from the government Domain
• Consider the data registered about the same radio station in the
databases of different ministries and governmental agencies:
ID Name Type Location
Agency 1 R2563I Radio Al-Amal Radio Station Ramallah
B_ID Business Name Activity Type City
Agency 2 LM1847 Al-Amal Radio Ramallah
Broadcast Broadcasting and Bireh
ID Company Name Company Type Location
Agency 3 182NS3 Broadcast Al- Broadcasting Al-Balu’
Amal Station
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9. Example from the government Domain
• From our simple example one can point out to some challenges in
Data Integration:
– No agreed upon naming (name, business name, company name)
– No agreed upon meaning (Does ‟Activity Type‟ mean exactly the same as
„Company Type‟?)
– Different Registered Data: Radio Al-Amal, Al-Amal Broadcast, ….
ID Name Type City
Agency 1 R2563I Radio Al-Amal Radio Station Ramallah
B_ID Business Name Activity Type Province
Agency 2 LM1847 Al-Amal Radio Ramallah
Broadcast Broadcasting and Bireh
ID Company Name Company Type Location
Agency 3 182NS3 Broadcast Al- Broadcasting Al-Balu’
Amal Station
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10. Problem is in all domains
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11. Problem is in all domains
• Problem is now even more challenging with the Web.
• The Data Web envisions the web as a global world-wide database.
• This means that one can query distributed multiple databases on the
web as if he/she is querying a local database.
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12. Challenges of Data Integration:
Heterogeneities in Database Schemas
• One can distinguish between several heterogeneities
between different schemas:
– Name Heterogeneities (difference in used vocabulary).
– Meaning Heterogeneities (different meaning for the same attribute
in two schemas).
– Heterogeneities in the structure and type.
– Heterogeneities in the rules and constraints.
– Data Model Heterogeneities.
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13. Name and Meaning Heterogeneities
• Synonyms – Different names for the same concepts
– employee, clerk
– exam, course
– code, num
• Homonyms – Same name for different concepts (different meanings)
- City as City of birth in one schema,
- City as City of Residence in another schema
Saraly: Net Salary Section A specialized
division of a
Salary: Gross Salary Division large
organization
Homonyms
Synonyms
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14. Heterogeneities in Structure and Type
Source: Carlo Batini
• The same concepts are represented with different conceptual
structures in two schemas:
– Attribute in one schema and derived value in another schema.
– Attribute in one schema and entity in another schema.
– Entity in one schema and relationship in another schema.
– Different abstraction levels for the same concept in two schemas:
e.g. two entities with homonym names related by an IS-A hierarchy
in two schemas.
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15. Heterogeneities in Structure
Source: Carlo Batini
• EXAMPLES:
EMPLOYEE EMPLOYEE
GENDER
Person Person
DEPARTMENT PROJECT
MAN WOMAN
PROJECT
BOOK BOOK PUBLISHER
PUBLISHER
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16. Heterogeneities in Type
 Examples:
 In a single attribute (e.g., Numberic, Alphanumeric). E.g., the
attribute “gender”:
– Male/Female
– M/F
– 0/1
 Year has a four digit domain in one schema and two
digit domain in another schema
 Different currencies (Euros, US Dollars, etc.)
 Different measure systems (kilos vs. pounds, centigrade vs.
Fahrenheit.)
 Different granularities (grams, kilos, etc.)
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17. Heterogeneities in the rules and constraints
Source: Carlo Batini
• EXAMPLES:
– Different cardinalities in the same relationships
– Key conflicts
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18. Model Heterogeneities
• Model Heterogeneities occurs when different databases adheres to
different data models:
– Relational Data Model, XML, RDF, Object-Oriented, OWL, ...
• Solution: Reduce Model Heterogeneity by using one data model.
• Example: Convert the Relational Model to RDF graph model.
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19. References
• Carlo Batini: Course on Data Integration. BZU IT Summer School
2011.
• Stefano Spaccapietra: Information Integration. Presentation at the IFIP
Academy. Porto Alegre. 2005.
• Chris Bizer: The Emerging Web of Linked Data. Presentation at SRI
International, Artificial Intelligence Center. Menlo Park, USA. 2009.
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