Semantic Web model In the field of disaster management to structurise the data such that any information needed during emergency will be easily available.
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Development of Semantic Web based Disaster Management System
1. Development of Semantic Web
based Disaster Management
System
Sankhadeep Pujaru
Roll No - 12/IT/429
Under the guidance of
Dr. Animesh Dutta
Assistant Professor
NIT Durgapur
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3. Rise of the Semantic Web
• Web 1.0 - Many Web sites consisting of
unstructured, textual content.
• Web 2.0 - Few large Web sites specialized
with specific content types.
• Web 3.0 - Many Web sites containing and
semantically syndicating arbitrary structured content.
• Goal - To represent Web content in a form that is more
easily machine-accessible.
• “The Semantic Web is an extension of the current web
in which information is given well-defined meaning,
better enabling computers and people to work in co-
operation.“ - [Berners-Lee et al., 2001] 3
4. Can we ask these questions ?
Search answers for the following queries in the
current search engines.
- Researchers actively working on semantic
technology related topics in India.
- Apartments near Bengali dominated area in
Bangalore.
- Guided tour providers with offices in Jaipur,
Delhi and Bangalore.
• The required information to answer the above
queries is available on the Web, but the current
Web search engines are not yet smart enough to
understand and answer the queries.
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9. RDF Schema
• Defines vocabulary for RDF
• Organizes this vocabulary in a typed hierarchy
- Class, subClassOf, type.
- Property, subPropertyOf.
- domain, range .
‘ ... /twain/mark’ ‘ ... /ISBN0001047582’
ex:hasWritten
FamousWriter
Writer Book
rdfs:subClassOf
rdf:type
rdf:type
rdfs:domain rdfs:range
SCHEMA
DATA
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ex:hasWritten
10. Ontology
An ontology formally represents knowledge as a hierarchy of concepts
within a domain, using a shared vocabulary to denote the types,
properties and interrelationships of those concepts.
• OWL – a formal ontology language, and it provides standard labels for
describing terms.
- Classes (owl:class, owl:unionOf etc.)
- Properties (owl:ObjectProperty, owl:DatatypeProperty, rdfs:domain,
rdfs:range etc.)
-Relations (owl:equivalentClass, rdfs:subClassOf, owl:equivalentProperty
etc.)
Querying and reasoning using an ontology can help reveal implicit
concept.
Inference = Ontologies + Rules .
If <Durgapur> <isPartOf> <WestBengal> and
<WestBengal> <isPartOf> <India>,
Then <Durgapur> <isPartOf> <India>. 10
12. Scope of Work
• “Which relief organizations can provide how
many tents for the earthquake-affected region
Gujrat in India ? ”
• In the field of disaster management to
structurise the data such that any information
needed during emergency will be easily
available.
• Different structure of websites.
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15. My Proposed Work
• This work emphasises on categorising of the
data.
• The data is organised semi-automatically and
an universal document structure is formed.
• This structure serves globally to all web
developers and accessors to simplify the task of
website development and website navigation.
• Website development is made easier through
RDF and Website navigation is made easier
through SPARQL.
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23. Future Work
• How to make global Ontology from a set of
websites within a domain .
• Mapping from Natural Language Query to
SPARQL.
• Publishing Linked Data on the World Wide
Web.
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24. References
1. Grigoris Antoniou and Frank Van Harmelen. A semantic web primer.
MIT press, 2004.
2. Dave Beckett and Brian McBride. Rdf/xml syntax specification
(revised). W3C recommendation, 10, 2004.
3. Chen-Huei Chou, Fatemeh Zahedi, and Huimin Zhao. Ontology for
developing web sites for natural disaster management: methodology
and implementation. Systems, Man and Cybernetics,
Part A: Systems and Humans, IEEE Transactions on, 41(1):50–62, 2011.
4. World Wide Web Consortium et al. Sparql 1.1 overview. 2013.
5. Blaz Fortuna, Marko Grobelnik, and Dunja Mladenic. OntoGen:semi-
automatic ontology editor. Springer, 2007.
6. Jennifer Golbeck and Matthew Rothstein. Linking social networks on
the web with foaf:A semantic web case study. In AAAI, 8, pages 1138–
1143, 2008.
7. Renato Iannella. An idiot’s guide to the resource description
framework. New Review of Information Networking, 4(1):181–188,
1998.
8. Natalya F Noy, Deborah L McGuinness, et al. Ontology development
101: A guide to creating your first ontology, 2001.
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25. 9. Tim Berners-Lee, James Hendler, Ora Lassila, et al. The semantic
web. Scientific american, 284(5):28–37, 2001.
10. Dan Brickley and Ramanathan V Guha. Resource description
framework (rdf) schema specification 1.0: W3c candidate
recommendation 27 march 2000.
11. Zhifeng Bao, Jiaheng Lu, Tok Wang Ling, and Bo Chen. Towards
an effective xml keyword search. Knowledge and Data
Engineering, IEEE Transactions on, 22(8):1077–1092, 2010.
12. Tom Heath and Christian Bizer. Linked data: Evolving the web
into a global data space. Synthesis lectures on the semantic
web: theory and technology, 1(1):1–136, 2011.
13. Lucas Zamboulis. Xml data integration by graph restructuring.
In Key Technologies for Data Management, pages 57–71.
Springer, 2004.
14. Michael Sintek and Stefan Decker. Triplea query, inference, and
transformation language for the semantic web. In The Semantic
WebISWC 2002, pages 364–378. Springer, 2002.
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