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Developing Ontology-based
Semantic Web Application
for Biological Domain
Author : Kashif Iqbal

Semantic Web for biological sciences 2
Agenda
 Introduction
 Problem Statement
 Motivation
 Literature Review
 Methodology & Procedures
 Implementation & Benefits

Introduction
 The current Web represents information
using natural language, graphics and
multimedia (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.

Introduction
 Tasks often require to combine data on the
Web:
 Plant flora and Gene sequencing information
may come from different sites.
 searches in different digital libraries etc.
 Again, humans combine these information a
tedious process.
 even different terminology's are used!

Introduction
 However: machines are ignorant
 To make machines intelligent ontology's lie at
the foundation which provide sophisticated
frameworks to model the knowledge of a
domain.
 The Semantic Web provides technologies to
make it possible! For example:
 RDF ,OWL,SPARQL,OWL-API, User-Interface.

 In the Life Science domain, a number of
documents presents already large on the web
and continues to grow at an exponential rate.
 Current search engines not support for
retrieving the information;
 millions of web documents retrieved
 also most of the data is not publically
accessible due to the concept terminology.
 The problem is how to provide the better
information 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)
Literature Review

Literature Review
OntoEdit: Guiding Ontology Development by
Methodology and Inferencing. (2009) In: R. Meersman,
Z. Tari et al. (eds.) Proceedings of the Confederated
International Conferences, University of California,
Methodology for Development and Employment of
Ontology Based Knowledge Management Applications:
York Sure, (2005)
 KAON - Towards a large scale Semantic Web. E.
Bozsak, M. Ehrig, S. Handschuh et al. Proceedings of
EC-Web (in combination with DEXA2002).

Motivation
 It is an effort to conceptualize a biological
knowledge base for biologist, scientist, end-
users that aim to retrieve biological
information at web scale.
 Semantic data model give solutions in such
domain.
 In general it has a wider applicability than
relational or object oriented databases.

Developing Semantic Web
Application
 “Semantic Web Applications usually make some
ontological commitments.
 They need to have hard-coded knowledge about
domain ontology obtained from experts which
contains classes i.e., plants, animals, angiosperm
gymnosperm along with their relations &
associations .
 The application can also operate on extensions of
these core concepts e.g., stemming from dynamic
extension ontologies about specific types.

Developing Semantic Web Application
 A Semantic Web Application is still an application
research work, thus it needs to follow good practice
from Software Engineering.
 Spiral Model inspired by the famous Boehm spiral is
used in this application development.
It is an extensible search framework for semantic web
applications.

Semantic Web Application Model

Semantic Web Architecture
 the XML layer, which
represents data
 the RDF layer, which
represents the meaning of
data
 the Ontology layer, which
represents the formal rules
common agreement about
meaning of data.
 the Logic layer, which
enables intelligent reasoning
with meaningful data.

Methodology & Procedures
 In order to built conceptual data model.
There is a need to clearly state the elements
that are abstracted.
 These elements are concepts, properties of
concepts, relations and properties of
relations.
 The meaning of each relation between two
concepts must be established.
 It allows semantics in applications to
automatically derive information.

 Table 1. Definitions and Examples of Relations
Relations Definitions Examples
C is-a C1 Every C at any time is at
the same time a C1
Apple is-a Fruit
Lion is-a Animal
C part-of C1 Every C at any time is
part of some C1 at the
same time
Heart part-of Body
Seeds part-of Fruit

 Table 2. Algebraic Properties of Relations
Relations Transitive Symmetric Reflexive
is-a + - +
part-of + - +

 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 Process

 Domain Ontology Screen Shot

Thank you

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