RDF and OWL : the powerful duo

1. RDF and OWL the
powerful Duo
Presented by:Tara Raafat

2. • Why go semantic ?
• Should I use RDF or OWL ?
• What is the difference , what is the link ?
• Did you say smart data ?
Questions

3. Data
Wisdom
Knowledge
Information
• Taking decisions using knowledge and
reasoning AI
• Information used with experience
and understanding  Semantic
Web
• Data enriched with context & history
 ERP / CRM / MDM
• TraditionalApplications
SemanticWeb
goes here
Semantic web formalizes knowledge in a way that improves decisioning today, and can form
the basis for autonomous reasoning in the future
The SemanticWeb

4. SemanticWeb Layer Cake
XML/XML Schema
RDF
RDFS
Logic
Proof
URIUnicode
Trust
Query:
SPARQL
RulesOWL

5. RDF
(Resource Description Framework)

6. RDF
• Simple triple based data model
Subject, Predicate, Object
• Graph- based formalism for representing metadata
• Kafka is the author of the book “Trial.”
• Individual things, and not just files, are given unique identifiers.
• XML serialization (RDF/XML) for ease of data exchange
• Various textual representations for ease of human understanding
• No Schema
Kafka Trial
Is Author of
http://www.mybookstore.com/Trial
http://www.mybookstore.com/isAuthorOf
http://www.mybookstore.com/Kafka

7. RDF is the heart of Linked Open Data
7

8. AN RDF Integration
Example

9. 9
English books database: Export data as RDF
http://…isbn/000651409X
Ghosh, Amitav http://www.amitavghosh.com
The Glass Palace
2000
London
Harper Collins
a:name
a:homepage
a:author

10. 10
French books Data Base: Export data as RDF
http://…isbn/000651409X
Ghosh, Amitav
Besse, Christianne
Le palais des miroirs
f:nom
f:traducteur
f:auteur
http://…isbn/202038662
f:nom

11. 11
Merge your data
http://…isbn/000651409X
Ghosh, Amitav
Besse, Christianne
Le palais des miroirs
f:nom
f:traducteur
f:auteur
http://…isbn/2020386682
f:nom
http://…isbn/000651409X
Ghosh, Amitav
http://www.amitavghosh.com
The Glass Palace
2000
London
Harper Collins
a:name
a:homepage
a:author
Same URI!

12. Ghosh, Amitav
Besse, Christianne
Le palais des miroirs
f:original
f:nom
f:traducteur
f:auteur
http://…isbn/2020386682
f:nom
Ghosh, Amitav
http://www.amitavghosh.com
The Glass Palace
2000
London
Harper Collins
a:name
a:homepage
a:author
http://…isbn/000651409X
a:author
same as
f:auteur

13. Merge with external data: Wikipedia
Besse, Christianne
Le palais des miroirs
f:original
f:nom
f:traducteur
f:auteur
http://…isbn/2020386682
f:nom
Ghosh, Amitav http://www.amitavghosh.com
The Glass Palace
2000
London
Harper Collins
a:name
a:homepage
a:author
http://…isbn/000651409X
http://…foaf/Person
r:type
r:type
http://dbpedia.org/../Amitav_Ghosh
http://dbpedia.org/../The_Hungry_Tide
http://dbpedia.org/../The_Calcutta_Chromosome
http://dbpedia.org/../Kolkata
http://dbpedia.org/../The_Glass_Palace
r:type
foaf:name w:reference
w:author_of
w:author_of
w:author_of
w:born_in
w:isbn
w:long w:lat

14. Ontologies & OWL
( Web Ontology Language)

15. 15
Ontology ( according to Tom Gruber (1992))
An ontology is a formal, explicit specification of a shared conceptualization
Machine Readable
Concepts, properties
Relations, functions,
Constraints, axioms,
Are explicitly defined
Consensual
Knowledge Abstract model
and simplified
view of some
phenomenon in
the world that
we want to
represent

16. DifferentTeams: Different Languages …
11/17/2017 16
Business user with a
data need
Business data analyst
Business -technology
liaison
Data architect Data scientist
Data Consumers Design
Dev – Data Source
Application
owner
Developer
Test
Dev – Data Integration
Developer
Dev Ops
Dev – Data consumer
Code
Dev Ops
TestTest
The problem
that we are
trying to solve
Architectural
concerns.
Enterprise vision
Semantics.
Data dictionary
Source system’s
data terminology
Source system’s data
terminology.
Target system’s terminology
Target system’s
data terminology
The problem
that we are
trying to solve
Functional
solution
Timing &
priorities
Dependencies

17. Ontology
• a knowledge model which defines a set of concepts and the relationship
between those concepts within a specific domain
• Supports automated reasoning and inference of data using logical rules
• Provides Knowledge sharing and reuse among people or software agents

18. OWL ( Web Ontology Language)
• RDF based
• A defacto standard for ontology development
• Main components include
Classes : which define concepts in a domain
Properties: which are of two type
Object properties : define relationships between concepts
Datatype properties: define relationships between a concept and a literal
Individuals: instances of classes
Restrictions: Allow definition of cardinality restrictions as well existential and
universal quantifications
• Has three levels
OWL Full
OWL DL
OWl-Lite

19. Project Example

20. Person
Important
Project
Thing
Project
Research
Project
Development
Project
Partner
Consulting
Partner
Employee
Project
Manager
Project
Coordinator
Industrial
Partner
hasProjectManager
hasProjectCoordinator
• hasBudget
• hasStartDate
• hasEndDate
• hasNumberOfEmployees
hasPartner
hasProjectCoordinator min 1
hasProjectManager exactly 1
hasBudget >=2,000,000
End date –Today <=1 month
Biology Department
Cancer Research
Institute

21. Person
Important
Project
Thing
Project
Research
Project
Development
Project
Partner
Consulting
Partner
Employee
Project
Manager
Project
Coordinator
Industrial
Partner
hasProjectManager
hasProjectCoordinator
• hasBudget
• hasStartDate
• hasEndDate
• hasNumberOfEmployees
hasPartner
hasProjectCoordinator min 1
hasProjectManager exactly 1
hasBudget >=2,000,000
End date –Today <=1 month
Biology Department
Cancer Research
Institute
• hasBudget: 3,000,000
• hasStartDate: 01/08/2014
• hasEndDate: 01/12/2014
• hasNumberOfEmployees: 40
CR Proj
CR Proj
Sam Cohen
Sarah SmithJohn Stevens
John Stevens
Cancer Research
Institutes
Project can only
have one project managerSame person is manager
and coordinator

22. So what happens when you combine OWL + RDF?
SMART DATA
Mapping
Rules
OWL
Models
RDF
Data

23. Use of Ontologies
• Knowledge representation
• Semantic annotation
• Semantic search
• Back bone of Process Automation
• Knowledge inference

24. An Industrial UseCase for SMART DATA

25. Legal Contract
Legal PersonLegal Document
Legal Person
Legal Entity
Item
Invoice Customer
Bill of Lading
Consignee/Shipperhas invoice
Letter of Credit
Freight
Forwarder
Company
Item
buyer
Trade Transaction
Letter of Credit
Bank
Issuing Bank
Account
holds
Vessel
Vessel ID
Journey
Trade Profile
vessel
profile
CIS systemsTransaction Data
Trade
Documents
Marine traffic Website
Port
Date
Price
Has Price
Total Price
Port of Loading/
Port of Discharge
Posted In
Business
Busines
s Sector
Smart Data forTrade Based Anti Money Laundering

26. Legal Contract
Legal EntityLegal Document
Legal Entity
Company
Item
Cotton shirts
Invoice
#JS54
Customer
ABCCorp
Bill of Lading
BOLLOC453
Consignee/Shipper
has invoice
Letter of Credit
ABCCorpLOC453
Freight
Forwarder
Company
ShippersStarItem
buyer
Trade Transaction
#76873
Letter of Credit
Bank
BankUSA
Issuing Bank
Account
#89222
holds
Vessel
BSLE9
Vessel ID
V245
Journey
Route548
Trade Profile
JSmithProfile45
vessel
profile
CIS systemsTransaction Data
Trade
Documents
Marine traffic Website
Port
Bangladesh-Jaipur-
Amsterdam
Date
7/08/2016
Price
2$
Has Price
Total Price
Port of Loading/
Port of Discharge
Posted In
Port
Bangladesh-
Amsterdam
Price
54$
Total Number
27
Business
NAICSCode767
Busines
s Sector

27. Brief Answers
• Why go semantic ?
• To present knowledge about your data.
• To allow data integration
• To bring intelligence to your system
• Should I use RDF or OWL ?
• If you just want to link your data or annotate-> USE RDF
• If you want to make your data smart and apply reasoning and
inference -> USE OWL +RDF
• What is the difference , what is the link ?
• RDF is to present data in triple formats and give it some structure
and unique identifiers so that data can be easily linked
• OWL provides a rich vocabulary to add semantics and context and
allow reasoning and inference
• Did you say smart data ?
• Yes! A data that can be understood by the computer and therefore
allows for intelligent automation

28. THANK YOU
Tara Raafat, PhD
Email:tara.raafat01@mphasis.com