On October 23rd, 2014, we updated our
By continuing to use LinkedIn’s SlideShare service, you agree to the revised terms, so please take a few minutes to review them.
Developing Ontology-basedSemantic Web Applicationfor Biological DomainAuthor : Kashif Iqbal
Semantic Web for biological sciences 2Agenda Introduction Problem Statement Motivation Literature Review Methodology & Procedures Implementation & Benefits
Introduction The current Web represents informationusing natural language, graphics andmultimedia (Ivan Herman). Humans can process this information easily They can deduce facts from partial information They can create mental associations. They use to various sensory information.Semantic Web for biological sciences 3
Introduction Tasks often require to combine data on theWeb: Plant flora and Gene sequencing informationmay come from different sites. searches in different digital libraries etc. Again, humans combine these information atedious process. even different terminologys are used!Semantic Web for biological sciences 4
Introduction However: machines are ignorant To make machines intelligent ontologys lie atthe foundation which provide sophisticatedframeworks to model the knowledge of adomain. The Semantic Web provides technologies tomake it possible! For example: RDF ,OWL,SPARQL,OWL-API, User-Interface.Semantic Web for biological sciences 5
Semantic Web for biological sciences 6 In the Life Science domain, a number ofdocuments presents already large on the weband continues to grow at an exponential rate. Current search engines not support forretrieving the information; millions of web documents retrieved also most of the data is not publicallyaccessible due to the concept terminology. The problem is how to provide the betterinformation retrieval support to end users .Problem Statement
The ontologies reviewed are as follows: Vocabularies and Retrieval Tools in Biomedicine:Vanopstal, Robert (2011) The OntoSeed ontology (2007)Creating Ontologies for Content Representation The RiboWeb ontology for Ribosome (2003)Semantic Web for biological sciences 7Literature Review
Semantic Web for biological sciences 8Literature ReviewOntoEdit: Guiding Ontology Development byMethodology and Inferencing. (2009) In: R. Meersman,Z. Tari et al. (eds.) Proceedings of the ConfederatedInternational Conferences, University of California,Methodology for Development and Employment ofOntology Based Knowledge Management Applications:York Sure, (2005) KAON - Towards a large scale Semantic Web. E.Bozsak, M. Ehrig, S. Handschuh et al. Proceedings ofEC-Web (in combination with DEXA2002).
Semantic Web for biological sciences 9Motivation It is an effort to conceptualize a biologicalknowledge base for biologist, scientist, end-users that aim to retrieve biologicalinformation at web scale. Semantic data model give solutions in suchdomain. In general it has a wider applicability thanrelational or object oriented databases.
Developing Semantic WebApplicationSemantic Web for biological sciences 10 “Semantic Web Applications usually make someontological commitments. They need to have hard-coded knowledge aboutdomain ontology obtained from experts whichcontains classes i.e., plants, animals, angiospermgymnosperm along with their relations &associations . The application can also operate on extensions ofthese core concepts e.g., stemming from dynamicextension ontologies about specific types.
Developing Semantic Web ApplicationSemantic Web for biological sciences 11 A Semantic Web Application is still an applicationresearch work, thus it needs to follow good practicefrom Software Engineering. Spiral Model inspired by the famous Boehm spiral isused in this application development.It is an extensible search framework for semantic webapplications.
Semantic Web Application ModelSemantic Web for biological sciences 12
Semantic Web for biological sciences 13Semantic Web Architecture the XML layer, whichrepresents data the RDF layer, whichrepresents the meaning ofdata the Ontology layer, whichrepresents the formal rulescommon agreement aboutmeaning of data. the Logic layer, whichenables intelligent reasoningwith meaningful data.
Semantic Web for biological sciences 14Methodology & Procedures In order to built conceptual data model.There is a need to clearly state the elementsthat are abstracted. These elements are concepts, properties ofconcepts, relations and properties ofrelations. The meaning of each relation between twoconcepts must be established. It allows semantics in applications toautomatically derive information.
Semantic Web for biological sciences 15Methodology & Procedures Table 1. Definitions and Examples of RelationsRelations Definitions ExamplesC is-a C1 Every C at any time is atthe same time a C1Apple is-a FruitLion is-a AnimalC part-of C1 Every C at any time ispart of some C1 at thesame timeHeart part-of BodySeeds part-of Fruit
Semantic Web for biological sciences 16Methodology & Procedures Table 2. Algebraic Properties of RelationsRelations Transitive Symmetric Reflexiveis-a + - +part-of + - +
Semantic Web for biological sciences 17Methodology & Procedures Semantic Web Application Using Jena a java framework To access and manipulate RDF data model The object model offers methods to retrieve concepts object-properties subject-properties ,etc the rest is conventional programming…
Ontology Development ProcessSemantic Web for biological sciences 18
Semantic Web for biological sciences 19 Domain Ontology Screen Shot
Semantic Web for biological sciences 20 Domain Ontology Screen Shot
Semantic Web for biological sciences 21 Domain Ontology Screen Shot
Semantic Web for biological sciences 22Thank you