Analyzing Design Methodologies For Semantic Web Applications Computer Science Essay

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This paper examines and compares several of most common design methods of semantic web applications. These methodologies are WSDM, HERA, SHDM, OntoWeaver, OntoWebber, Seal and S-FrameWeb. The methods are compared using various parameters. Finally some comparison results are given and discussed.

Keywords: Semantic Web, Software Engineering, annotation, design methodologies

WebML, WSDM, OOHDM, OO-H, UWE, WUML, W2000, etc

Introduction

The current web is a hypertext system which is a collection of interconnected documents that are understandable to the human beings. With current web, the meaning or semantic of information is only understandable to the human beings. It means that meaning of the information is can only be interpreted by human beings. The computer only serves the purpose of delivering documents to the people. The need of semantic web was realized so that machines can understand the meanings or semantic of information. It allows faster processing than human beings.

The semantic web is an extension of current web which defines the meaning of information in such a way so that it can be understandable by the machines and machines can process the information. The major difference between current web and semantic web is that the current web is a huge distributed hypertext system whereas semantic web is a huge distributed knowledge base system. The main focus of semantic web is to share information instead of documents.

Various design methodologies have been developed for the analysis and design of semantic web applications. These methodologies differ from the design methods of web-based application because they focus on addition of semantics to web applications so that they can be processed and understand by machines. Most of the design methods for semantic web applications are extension of traditional methods for web-based applications. Methods are no guarantee that all software development problems will be solved. But they attempt to structure the analysis & development of semantic web application applying design techniques and rules.

In this paper, Section 2 briefly explains some of the design methodologies of semantic web application; Section 3 compares these methodologies using various parameters, Section 4 provides results and discussion and finally Section 5 provides conclusion.

Explanation of design methodologies of semantic web application

WSDM (Web Site Design Method)

WSDM was one of the first web design method developed in 1998 by De Troyer and Leune. It is an audience driven design methodology for semantic web applications. This methodology is aimed at creating different versions of web site for different localities. This methodology supports localization of web sites as different communities or localities may have different languages and different culture.

This methodology has five phases: 1) Mission statement specification 2) Audience modeling 3) Conceptual design 4) Implementation design and finally implementation phase.

For more detail, see the comparison table 1.

HERA

SHDM (Semantic Hypermedia Design Method)

SHDM is a model-driven methodology. It is an extension of OOHDM (Object-oriented design method) and uses ontologies to add annotation (semantic content) to the web. It has five different phases: Requirement gathering, conceptual design, navigational design, abstract interface design and implementation. Although the phases in both approaches are same but technologies are different. In WSDM, object chunk are used to define the conceptual design whereas SHDM is based on OOHDM therefore it uses UML/Class diagram to define the conceptual design. As compared to Hera methodology, it starts from the traditional UML-like object model and then extends it to RDF and DAML+OIL ontology language whereas Hera starts directly from RDF and RDFS. SHDM method considers different types of users but it does not specify how to describe or distinguish different types of users. This issue has been resolved in WSDM methodology.

For more detail, see the comparison table 1.

OntoWeaver

OntoWeaver is an ontology-driven design methodology for creating and maintaining customized web applications. It is a model-driven methodology to explicitly specify customization at high level and uses JESS inference engine o perform reasoning upon site specification to create web site in desired format according to the preferences of users. The declarative nature of site specification enables designer to manage and maintain web application at conceptual level. This methodology allows designer to handle different aspect of site by using different types of ontologies. There are two major activities involved with OntoWeaver: 1) specification of general web site 2) specification of customized web site for different users.

This method is provided with set of tools to enable designer to design and manage web application.

The major strength of this method is that it supports dynamic customization which was not present in other methods such as OntoWeaver, OOHDM and WebML.

For more detail, see the comparison table 1.

OntoWebber

OntoWebber is a model-driven ontology based design methodology for building data-intensive web site and web portal. In most of the previous method, design was hard-coded in HTML, ASP, JSP, etc but this method uses re-usable components such as ontologies to design web site making the integration and maintenance of heterogeneous data sources more manageable than other methods.

OntoWebber uses layered architecture consisting of 4 layers. The integration layer integrates data from heterogeneous data sources and mapped all the data from heterogeneous data sources to unified data format by converting into RDF format. The articulation layer map the incoming data (semantic data) from heterogeneous sources to reference ontology of OntoWebber system as different data sources may use different domain ontology. The composition layer defines site- view specification for different types of user. The last layer 'Generation layer' uses query engine to query site view specification for the specific site view and generates web pages in desired format.

For more detail, see the comparison table 1.

SEAL

SEAL is a framework for developing semantic web portals using ontologies and information retrieval concepts such as semantic browsing and semantic ranking for semantic sharing of knowledge on the web portal between human and software agents. The architecture of SEAL consists of various modules such as knowledge warehouse, OntoBroker, RDF generator, Template module, Navigation module, Query module, Semantic personalization module, semantic ranking and Web server. It supports three types of agents: software agents, community users and general users. The software agents process information on the web portal using RDG Crawler. The RDF crawler is provided with information stored in warehouse via RDF generator and then via web server. The community users serves two activities: 1) The community users provides data to knowledge warehouse via HTML forms then that data is stored into knowledge warehouse via Template module. 2) The community user access information by navigating through web portal via navigation module and by posting query then OntoBroker performs inferencing on knowledge warehouse which retrieved the ranked documents then semantic ranking is done by semantic ranking module. The RDF crawler is a tool that crawls on web to generate external warehouse by downloading inter-connected RDF.

S-FrameWeb

Comparison of design Methodologies

These design methodologies have been compared using various attributes. These are

Table 1.

Parameters

Methodologies

WSDM

HERA

SHDM

OntoWeaver

OntoWebber

Seal

S-FrameWeb

1

Phases/Components/

Modules/ Steps

5

2

5

4

5

9

6

2

Approach

Web-engineering

Web-engineering

Web-engineering

Web-engineering

Web-engineering

Web-engineering

Web-engineering

3

Extension

Extension of object-oriented hypermedia approach

Ontology-based approach

Ontology-based approach

Ontology based approach

Extension of FrameWeb

4

Layered Architecture

Ã-

√

√

Ã-

√

-

-

5

Layers supported

Ã-

3

4

Ã-

4

-

-

6

Methodology

Audience driven

Model-driven

Model-driven

Model-driven

Model-driven

Framework based approach

7

Suitable for web application

Localized websites

Semantic WIS

(Web information system)/ Customized web applications

Semantic WIS

Customized data-intensive web applications

Customized web applications/ data intensive applications/ semantic web community portals

Semantic web portals, Information Retrieval system

Semantic WIS and semantic web services

8

Supports different version of websites based on their locality

√

Ã-

Ã-

Ã-

Ã-

Ã-

Ã-

9

Follows SE principles

√

√

√

√

√

√

√

10

Supports specification of semantic annotation

At design level (conceptual level)

At design level

At conceptual level

At design level (conceptual level)

At design level

At design level

At design level

11

Generation of semantic annotation

During implementation

During implementation

During implementation

During implementation

During implementation

During implementation

During implementation

12

Supports annotation for static pages

√

√

√

√

√

√

√

13

Supports annotation for dynamic pages

√

√

√

√

√

√

√

14

Localization of web site

√

Ã-

Ã-

Ã-

Ã-

Ã-

Ã-

15

Implementation independent annotation

√

√

√

√

√

√

√

16

Uniform process of annotation for both static and dynamic pages

√

√

√

√

√

√

√

17

Re-use of existing ontologies/RDF

√

√

√

√

√

√

√

18

Data retrieval query language

-

RQL

RQL

-

-

-

-

19

Improves the design process

√

-

-

-

-

-

-

20

Annotation starts from

Object chunk (a data model which models the necessary information that are needed to fulfill the requirement of that elementary task)

RDF

UML like class diagram which are later mapped to RDF/XML format

RDF

RDF

RDF generator which generates RDF statements from the internal knowledge warehouse

UML like class diagram represented using ODM which is later mapped to OWL

Annotation starts from

Task modeling phase

21

Semantic web languages

OWL

RDF, RDF(S)

DAML+OIL, OWL, RDF, RDFS

RDF

RDF, DAML+OIL

RDF

ODM, OWL

22

Supports different types of user

√

Ã-

√

√

√

Ã-

Ã-

23

Classification of users

√

Ã-

Ã-

Ã-

Ã-

Ã-

Ã-

24

Suitable for 'One size fits all' and localized web sites

√

Ã-

Ã-

Ã-

Ã-

Ã-

Ã-

25

Automatic generation of semantic annotation

√

√

√

√

√

√

26

Use of Semantic web technology at

Design level

Design level

Design level

Design level

Design level

Design level

Design level

27

Systematic approach for designing web site

√

√

√

√

√

√

√

28

Consistency of annotation

√

-

-

-

-

-

-

29

Supports specification of different data sources and presentation format at design level

Ã-

√

-

√

√

√

Ã-

30

Considers preferences of different users while designing

Ã-

√

Ã-

√

√

√

Ã-

31

Set of tools

-

XSTL

Ontology Editor

Ontology Editor, Site Designer, Site Customizer, Site Builder, Online Page Builder, OntoWeaver Server, JESS, RDF-to-Jess compiler

-

RDF Generator, RDF Crawler

-

32

Supports personalization of presentation based on user preferences a design level

Ã-

√

Ã-

√

√

√

Ã-

33

Support the management and maintenance of web application at conceptual level

√

√

√

√

√

√

√

34

Different views for different types of devices

-

√

Ã-

√

√

Ã-

35

Support dynamic customization

-

Ã-

Ã-

√

Ã-

-

Ã-

36

Support pre-defined customization or static customization

-

√

√

Ã-

√

-

-

37

Supports integration of heterogeneous data sources

-

-

-

√

√

-

-

Handles each aspect of the site design

-

-

Ã-

√

√

-

Ã-

39

Implementation independent approach

√

√

√

√

√

√

√

40

Automatic personalization system

-

-

Ã-

-

√

-

-

41

Inference engine

-

BOR

JESS

-

OntoBroker

-

42

Supports semantic ranking of query results

-

-

Ã-

-

-

√

-

43

Supports complex inferencing for query answering

-

-

Ã-

-

-

√

-

44

Implementation Architecture

-

-

Sesame

-

-

-

-

45

Provides an infrastructure for identifying human request or software agent request

-

-

Ã-

-

-

-

√

46

Strength(s)

i) Implementation independent annotation

ii) Uniform annotation process for both static and dynamic pages

iii) It reduces the work load as compared to previous approaches as annotation is done at design level

iv) Re-use of existing annotation and change in one annotation does not require change in all annotation, all annotation will be updated automatically

v) It gives higher usability and better user satisfaction

vi) Supports for semantic annotation of both static and dynamic pages

vii) Change in implementation do not invalidate annotation

viii) Support annotation for visually impaired users

i) It supports dynamic customization specification which allows specification of customization at run time

ii) It is provided with the set of tools to enable designer to design and manage web application using graphical user interface

iii) Provides different views for different types of devices

i) Models different aspects of web site

ii) Supports knowledge management and dynamic personalization

iii) Re-usability of models enable designers to use specific model (such as favorite presentation style) with other site view

iv) The declarative specification of models make it easier to change any aspect of site by simply defining re-writing rules for models using DAML|+OIL

v) Deals with heterogeneous data sources

vi) Uses unified data model (RDF) to map incoming data from different sources to unified data format

vii) Support pre-generation of HTML pages at compile time (Full compilation), partial compilation and full interpretation

i) Based on rich ontology to semantically rank retrieved documents

ii) It supports complex inferencing for query answering

47

Weaknesses

i) As this approach support pre-generation of HTML pages at compile time if the load of web site is high and designer has adopted full compilation then any change to source data may require large number of site views to be re-instantiated which is inflexible solution so designer must use appropriate option based on his experience

ii) It does not support dynamic customization specification

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