Development of Semantic Web based Disaster Management System
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Development of Semantic Web based Disaster Management System



Semantic Web model In the field of disaster management to structurise the data such that any information needed during emergency will be easily available.

Semantic Web model In the field of disaster management to structurise the data such that any information needed during emergency will be easily available.



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Development of Semantic Web based Disaster Management System Development of Semantic Web based Disaster Management System Presentation Transcript

  • 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 1
  • Contents • Introduction • Layer Cake Architecture • Ontology • RDF • RDF Schema • Disaster Management domain • Proposed architecture • Work done • Ontograph formation • RDF serialisation • SPARQL query • Future Work 2
  • 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
  • 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. 4
  • Semantic Web Vision Layer Cake Architecture 5
  • RDF subject – predicate - object triple, P ( S, O ) [S] P [O] http:// (‘’, "Mark Twain") http:// (‘’, ‘’) http:// (‘’, "The Adventures of Tom Sawyer“) 6
  • “Mark Twain” ‘’ ‘’ "The Adventures of Tom Sawyer" ex:hasName ex:hasWritten dc:title Contd... 7 RDF Graph
  • <rdf:RDF xmlns:rdf="" xmlns:dc="" xmlns:ex="" > <rdf:Description rdf:about=""> <ex:hasWritten rdf:resource=""/> <ex:hasName>Mark Twain</ex:hasName> </rdf:Description> <rdf:Description rdf:about=""> <dc:title>The Adventures of Tom Sawyer</dc:title> </rdf:Description> </rdf:RDF> Contd... 8 RDF Serialisation
  • 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 9 ex:hasWritten
  • 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
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  • 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. 12
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  • Architecture 14
  • 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. 15
  • Ontogen Input.txt Ontograph Supervised manner Jena RDF Form triplet and adding standard , domain specific vocabulary SPARQL ARQ Processor Result Query 16Implemented Architecture
  • 17 Concept Query
  • 18 Concept’s Documents
  • 19 Ontology Visualization
  • 20 RDF of that Ontology
  • 21 Examples of SPARQL Query
  • 22 Contd…
  • 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. 23
  • 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. 24
  • 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. 25
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