Dewey Decimal Classification Scheme

Research Article A S c i T e c h n o l J o u r n a l
Dar and Razzaq, J Comput Eng Inf Technol 2018, 7:1
DOI:
10.4172/2324-9307.1000194 Journal of Computer
Engineering & Information
Technology
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Technology and Medicine
Building Ontology for Library
Management System Using
Dewey Decimal Classification
Scheme
Amil Rohani Dar*1 and Sheeba Razza2
Abstract
The internet is playing a very important role in communication
and sharing knowledge today. Users of the Internet use web for
different kinds of tasks. The current web mostly restricts processing
of information to manual keyword searching and becomes the
reason for irrelevant information retrieval. This problem can be
overcome by using semantic web. Semantic web is intelligent and
meaningful web. It describes the things in a way that the computer
can understand. Ontology plays a vital role in achieving goal of
semantic web i.e. how to use and reuse knowledge that can be
communicated across applications systems. For the development of
ontology, the most important thing is classes and the resulting class
and subclass relationships. Classification schemes have been used
persistently to represent various kinds of human knowledge. Dewey
Decimal Classification (DDC) scheme provides list of classes for
all kind of books. It was invented by Aristotle in the 4th century BC.
Currently, this scheme is used by most of libraries in the world. In our
work we are extracting the classes from DDC scheme for building
ontology and converting the classes into ontology. We developed a
hierarchical structure comprised of a class-subclass relationship as
well as relation among hierarchy levels and properties. This paper
presents the potential of ontologies applicable to semantic web. The
proposed ontology has been used to develop a library management
system (LMS) and produce excellent results in terms of efficiency
and ease of use.
Keywords
Ontology; Protege; Classification scheme; Database; Library
management system; Semantic web; Web 3.0
*Corresponding author: Amil Rohani Dar, University of Kotli Azad Jammu and
Kashmir, Pakistan, Tel: +92 3328389183; E-mail: [email protected]
Received: December 26, 2017 Accepted: February 28, 2018 Published: March
03, 2018
In web 1.0 the user can only view and read the information on web
pages, and hence it is called the static web. In web 2.0 the user can
view and can interact with the information on web pages, allows both
read and write operations and hence called dynamic web. Web 2.0
brought a big change in the field of www in short time. Web 3.0 is
called semantic web which is read, write and execute web. This web is
not new or separate web but an extension to web 2.0 [1]. Today, people
use keyword search for finding their required material at WWW and
use different search engines for this. However, the web 2.0 restricts
the information processing. The information retrieval becomes
difficult and very time consuming and user must be patient until the
exact information is found. In the current system, it is very hard to
understand the meaning of information as information on the web
is not organized [2]. This is contrary to the requirement of libraries
which need some classification scheme to organize the data in such
a manner that users can search the material easily. The classification
schemes named Library of Congress Classification (LCC) [3] and
DDC [4] almost cover all fields of knowledge. The DDC divides the
books into different classes which is important from ontology building
point of view. The DDC is the most favorite method used by librarians
to classify the books [5]. The ontologies have potential for modeling
the classification scheme. Ontologies use concepts, individuals,
properties and restrictions that help semantic search engine [6].
Ontology can be written in different languages [7] such as XML,
XMLS, RDF, RDFS, and OWL. The paper is organized as follows.
Section 2 briefs the related research and development work. A use case
scenario is presented in section 3. A quick view on semantic web is
given in section 4. Section 5 describes the problem statement. Section
6 is on rules for creating the ontology. Section 7 describes research
methology. Section 8 encompasses system implementation. Section
9 describes ontology exploitation. Section 10 gives protégé ontology
visualization. Section 11 describes SPARQL queries results. Section 12
sums up this effort and includes some futuristic ideas.
Related Work
For the organization of digital resources or physical material, the
librarians use classification schemes in libraries. These schemes consist
of hierarchies of topics which define the controlled vocabularies to
explore collections [8]. The most common classification schemes are
Universal Decimal Classification (UDC) [9], LCC [3] and DDC [4]
among which DDC is widely used in most of libraries. There are some
issues found in classification schemes when expressing them in Simple
Knowledge Organization System. Zeng et.al suggested that these issues
can be solved and implemented in Protégé editor and ontology can
be developed [10]. The literature lacks research in classification based
semantic web ontology and very few researchers have actually tried
to design and analyses such mechanisms. Nevertheless some authors
like Medina MA et.al have put efforts in establishing the basis of this
methodology. Some instances are as follows. The use of classification
schemes to model ontologies is presented [11]. Classifications are also
used for web pages and other kind of electronic media. Giunchiglia et
al. proposes a Formal classification to develop some sort of light weight
ontologies [12]. Classification based ontologies can be very helpful for
practical implementation of semantic web. This fact was proved by
Giunchiglia et al. where the author converts the generic classification
schemes to OWL ontology [13]. Library classification schemes have the
Introduction
A classification scheme is a method used by librarians to organize
the digital or electronic material in librarirs. “The classification system
is used in 200,000 libraries in at least 135 countries”. For the creation
of LMS ontology, DDC scheme helps implement all knowledge fields
and provides the classes which are basic requirement for creation of
ontology. Semantic web is used to implement intelligent search and
relies heavily on ontologies as it provides controlled vocabulary and
machine process able data. Once a suitable ontology is created for
LMS, it can be used to achieve an excellent book searching experience.
According to Tim Berners-Lee [1] there are three kinds of web.

Citation: Dar AR, Razzaq S (2018) Building Ontology for Library Management System Using Dewey Decimal Classification Scheme. J Comput Eng Inf
Technol 7:1.
doi: 10.4172/2324-9307.1000194
Volume 7 • Issue 1 • 1000194 Page 2 of 8
potential to manage electronic data of web organization knowledge.
Library professionals have been applying the classification schemes
in many internet based projects and getting the benefits from this.
Vizine-Goetz D concluded that DDC based browsing is very effective
in the internet world because the classification schemes can cover
all the topics of internet schemes [14]. The main focus of authors is
to analyze the most common properties between internet and DDC
schemes. Classification schemes are mostly used in libraries. For
libraries there are LMS based on relational databases. Such databases
can be easily converted into ontologies [15]. Also there is an example
ontology LMSO [16] is available which uses the concepts, properties &
restrictions of ontology. Ontology for LMS has been developed in this
research work which uses a novel approach based on DDC scheme.
The main focus of this paper is to use DDC scheme classes as concepts.
We use some rules to derive the library ontology. A simple seven step
algorithm is presented that shows the working and interactions of
the proposed system. We also present the system implementation
architecture which describes ontology in semantic web application for
LMS. Then we test the ontology with reasoning service provided by
protégé editor. At the end, results are generated with SPARQL queries
in protégé using its facility of querying ontology.
Use case Scenario
The ontology base library system keeps record of books in such
a way that the library administrator manages the book record and
the users of library can search books. Therefore, we have two use
case scenarios here with respect to administrator and user of library
ontology. The administrator enters the book record into ontology. A
book has several parameters. These are author, book title, description,
pages, copyright year, call number, publisher, publication date, price,
ISBN, shipping weight, volume id, etc. The administrator first adds
the book title in the ontology; if this book is already present in the
ontology then a message will pop up. If the book is not into the
ontology, then the administrator checks which class in the library
ontology is the class of new book. The administrator will then add
this book into the corresponding class and enriched the book with
metadata? Meaning of enriching data not clear to me?. At the other
end, the user of the library ontology system can search the book by
author name, title of the book or by ISBN number. The user can enter
the title of the book in the search bar and SPARQL query will take
this title and check in the library ontology. If this title is present in the
ontology, it will return the results to the user. The user can also search
with any string from the book title instead of using the full title. The
system returns the results very accurately to the user. If the record
does not exist in the library ontology, then it will display a message to
the user accordingly.
Semantic Web
Defining semantic web is very difficult as it consists of a mesh of
information. “Semantic web is a framework for expressing information
in machine understandable form”. Semantic web converts the current
web into a “web of data”. According to the W3C, “The semantic web
provides a common framework that allows data to be shared and
reused across applications, enterprises, and community boundaries”
[17].
Why to Use Semantic Web?
The current web is a global database where, among other
operations, the user searches the required piece of information. This
web cannot search more precise data for user because there is a huge
amount of data. This global database consists of a huge number of
documents and this number keeps on increasing. Also, the mechanism
of storing documents on current web is either unstructured or semistructured. In case of semantic web, the documents can be stored in a
structured way where machines can better understand the documents
and required information can be accessed very easily. Suppose one has
to purchase a book with a certain criteria such as the book author is of
a certain country, price is less than 500 rupees, paper quality is good,
cover page color is black as well as minimum shipping rate and fast
delivery time. In the current web, one has to visit different web pages
for finding books. Then, one has to compare the prices one by one,
and then check shipping and delivery times. Hence, most of the time
is consumed in checking all these parameters one by one. But with
semantic web, one just needs to enter all the preferences for the book
and then a computerized agent would search all the required data
instead of the user. Semantic web searches through metadata which is
machine readable data and gives results very soon. This example gives
a clear picture on usefulness of the semantic web.
Problem Statement
In today’s web manual keyword searching is a problem, which
restricts information processing. While searching in current web this
way, users have to face a lot of irrelevant information. Web 2.0 is an
example of this kind of web where information is stored in different
formats. A user has to search required information by use of keywords
in a search engine. The library systems are also of such kind where
users search the required piece of data by entering keywords or index
terms. The SQL comes up with a lot of information, if it is available,
because it matches the keyword with the database and selects whatever
matches with the keyword. This puts the burden on the user to find
the required piece of information in the search results. It does not
allow defining properties of classes or adding annotations to the data
to perform a more focused search. The whole searching mechanism
becomes manual.
The solution to this kind of problems is provided by semantic web
as it describes the relationship between different things and allows
definition of the properties as well. By using semantic web, we can
make the results in LMS more accurate and efficient. The semantic
web can exploit class, subclass relationships with keyword search at the
same time. Traditional library systems also cannot check consistency
between classes. Ontologies overcome this problem efficiently with
the help of reasoning services. This paper shows that ontology based
library classification schemes are better than relational database LMS.
Rules for Construction of Library Ontology Elements
based on DDC and Book parameters
In this paper, deriving library ontology is based on some rules.
Main concepts are taken from DDC scheme. Additionally, some
classes are taken from book domain. For library ontology, rules for
construction of concepts, rules for ontology properties, rules for
ontology axioms, rules for ontology instances, rules for hierarchy, and
rules for cardinality learning have been defined as follows.
Rules for construction of concepts
Library ontology consists of different classes. Subclasses of class
‘Book’ are directly mapping the classes of the DDC scheme into
library ontology concepts. DDC scheme provides list of classes in a
hierarchical form. That’s why it is easy to pick class names directly
from the DDC official web page and save these classes into ontology.

Citation: Dar AR, Razzaq S (2018) Building Ontology for Library Management System Using Dewey Decimal Classification Scheme. J Comput Eng Inf
Technol 7:1.
doi: 10.4172/2324-9307.1000194
Volume 7 • Issue 1 • 1000194 Page 3 of 8
Classes from DDC (Ci) = LO (Ci) where LO is library ontology, C is
for class and i=1, 2, 3, 4….. Other classes such as ‘Author’, ‘Publisher’
are derived from book domain.
Rules for ontology properties
There are two types of properties. These are object and data type
properties. All the book parameters provide the properties. These
parameters are book title, author, ISBN, publisher, edition, etc. for
example; a book has an author which gives the object property ‘has
author’. Book has publisher which gives object property ‘has publisher’.
The Book has ISBN which gives data type property ‘has ISBN’. The
rule for properties is Book (Ai) = LO (Pi) where A is a book attribute,
P is property and i=1, 2, 3, 4…..
In this way both types of properties can be created.
Rules for ontology individuals
All book parameters consist of values. These values are the
individuals. Suppose book has title ‘Fundamentals of computer
science’. This is the individual for class ‘Book’ which has object
property “has a title”. Book has the author ‘Tom Mitchel’. This is
another individual of object property “has the author”. The Book has
ISBN ‘1230594442’. ISBN is an integer type. Hence, this is data type
property.
Rules for hierarchy of ontology classes
Classes in owl can be organized as class and subclass relationship.
On DDC scheme the classes are arranged in hierarchical form. That’s
why it is easy to integrate the classes in the library ontology in class
and subclass relation.
Rules for construction of learning ontology axioms
The Book has several parameters. Some parameters have unique
value and some have not unique. In this regard, the parameter which
has unique value max_cardinality for this property will be 1. If the
parameter is not unique the min_cardinality for this property will be 1.
Research Methodology
This paper proposes an approach for developing ontology for the
library where each category of DDC scheme is divided into class and
subclass relation. Ontology names these classes as Level-1, Level-2,
and Level-3 until more general to specific class reaches. We used
Protégé Editor [18] for development of ontology. It considers Thing as
the main class of ontology. The ‘Thing’ is a domain which is the superclass of every class, and then it adds our Library Domain class name
Library under Thing as shown below:
Thing
Library
a. Computer Science, Knowledge and Systems
i. Computer science, knowledge and general works
ii. Data processing and computer science
iii. Computer programming, programs and data
b. Philosophy and psychology
i. Philosophy
ii. Metaphysics
iii. Epistemology
iv. Philosophical schools of thought
c. Religion
i. Public worship
ii. Ethics
iii. Sources
iv. Religious experience, life, practice
v. Doctrines
d .….
e .….
f. ….
In this way proposed system creates the classes for ontology. After
this, the proposed system uses the feature of OWL ontology to define
the properties and restrictions between classes and subclasses using
protégé. Each class of ontology is set of individuals [19]. The proposed
system sets the object and data type properties between individuals
and classes. OWL can use different properties. Annotations and other
information can also be added along with properties. Simple 7 step
algorithm shows the implementation methodology of the proposed
system depicted in Figure 1.
We Studied the DDC scheme.
Extract hierarchy of classes from DDC.
Install Protégé and start building ontology using protégé editor.
a. Select directory where ontology is to be stored.
b. Start building ontology under main class “Thing”.
c. Write the names of classes and subclasses under main class.
d. Start adding individuals for each class.
e. Add object properties.
f. Add data type properties.
g. Add annotation properties.
Figure 1: Implementation Methodology.
Citation: Dar AR, Razzaq S (2018) Building Ontology for Library Management System Using Dewey Decimal Classification Scheme. J Comput Eng Inf
Technol 7:1.
doi: 10.4172/2324-9307.1000194
Volume 7 • Issue 1 • 1000194 Page 4 of 8
It provides plug and play environment [19]. Ontologies developed in
protégé are easily exported into different formats [20]. Protégé has
the ability to check the inconsistencies of ontologies with different
reasons in it. Figure 3 shows the class hierarchy of library ontology
which consists of DDC main classes and their subclasses. The Thing
is the main class by default. For representation of domain we created
class Library as subclass of Thing. DDC scheme’s classes are listed
under Books class. The Books class has ten DDC classes. Using this
class and subclass method, a hierarchy is created for library ontology
shown in Figure 3.
Individuals
There is a list of individuals in library ontology. These individuals
are assigned to different classes shown in the ontology in Figure 3.
An Individual can be book name, author, publisher, Uri, country etc.
Figure 4 shows some individuals of ontology.
An example code for adding the individuals in library ontology
is listed below. First individual is the example a book title, second is
the name of the country where the book is published while third is
author’s name. The example is as follows.
<Declaration>
<NamedIndividual IRI=”#Oracle8_server_distributed_
database_systems”/>
</Declaration>
<Declaration>
<NamedIndividual IRI=”#UK”/>
</Declaration>
<Declaration>
<NamedIndividual IRI=”#Raymond_Panko”/> </Declaration>
Object and Data type Properties
The Protégé editor provides two types of properties for individuals.
It also provides a 3rd type of property as well called annotation
Use SPARQL for querying the ontology in protégé.
Design Semantic web application using Eclipse/Net beans etc.
Query the Semantic web application
Show the results to user.
System Implementation
The proposed system is implemented using windows platform.
Figure 2 shows the system diagram and environment framework. The
users on client side browse the system through the World Wide Web.
At client side, a user can search a book using metadata. A user can
use book name, author name, ISBN, call number, etc. For example,
the user can enter the name of book names “Machine Learning” and
send this query to the system over semantic web application. This
application is designed by using Java language in net beans with JenaApi integration. The query here is not a simple SQL query; instead
it is SPARQL query which is handled by SPARQL endpoint on the
remote server side. This query fetches the results from ontology on
server side; the results are sent back to the user on the client side. On
the remote server side, the library administrator manages the library
ontology. The administrator enters the record for books in ontology
using protégé editor. The administrator can make changes in ontology
using a local host or directly on a live server.
Ontology Exploitation
In this work, DDC scheme is used for developing the ontology
for book searching in the library. This ontology covers all the main
classes of DDC. DDC is used for classification in LMS. The proposed
Ontology is listing all ten main classes of this classification scheme.
The following sections show how classes are designed under main class
Thing in protégé, how individuals are added, how object properties
and data properties are listed with examples and how domain and
range works.
Implementation of LMS ontology classes
For the purpose of ontology implementation, protégé 4.2 was
used due to extensibility and flexibility for application development.
Figure 2: System Implementation.
Citation: Dar AR, Razzaq S (2018) Building Ontology for Library Management System Using Dewey Decimal Classification Scheme. J Comput Eng Inf
Technol 7:1.
doi: 10.4172/2324-9307.1000194
Volume 7 • Issue 1 • 1000194 Page 5 of 8
An example for data property from library ontology: A book has ISBN
<DataPropertyAssertion>
<DataProperty IRI=”#hasISBN”/>
<NamedIndividual IRI=”#Dynamic_web_publishing_
unleashed”/> <Literal datatypeIRI=”&xsd;integer”>5438176350516</
Literal>
</DataPropertyAssertion>
Annotation property
For adding expressiveness to ontology, metadata properties are
used. These are not helpful for logical knowledge in the ontology;
however these are adding some additional information about
elements of the ontology. An example of annotation property from
library ontology is given below.
<AnnotationAssertion>
<AnnotationProperty abbreviatedIRI=”rdfs:comment”/>
<IRI>#Beginning_ASP.NET_databases_using_VB.NET</IRI>
<Literal datatypeIRI=”&xsd;string”>
This book is very helpful in learning the ASP .Net
databases and much much more. I used this book and I learnt a lot
from it. This is very simple and easy to understand code using VB.
</Literal>
</AnnotationAssertion>
Protégé Ontology Visualization
Understanding the structure of the ontology is very important
for users. Better understating of classes, individuals and individuals’
properties is important for users to know how the library ontology
is working. Graphical representation of ontology using Owl Viz and
Onto Graf is shown in Figures 6 and 7.
SPARQL Query and Results
In this section some SPARQL queries are made for getting
results of book search from library ontology. For this purpose there
are many possibilities for book search. For example, book can be
searched by book title, author name, ISBN number, call number,
with combination of author and book title etc. We are just using the
book title as searching criteria. The combinations are not used by
property. The Figure 5 below shows both types of properties for
individuals [21,22].
A code example of both types of properties shows usefulness of
these properties. Object properties are used to show the relationship
between two individuals and data type properties add values of
individuals. An example for object property from library ontology: A
book has an Author
<ObjectPropertyAssertion>
<ObjectProperty IRI=”#hasAuthor”/>
<NamedIndividual IRI=”#Design_methods_and_
analysis_of_algorithms”/> <NamedIndividual IRI=”#David_A._
Chappell”/>
</ObjectPropertyAssertion>
Figure 3: Library Ontology.
Figure 4: Individuals.
Figure 5: Object property and Data property.
Citation: Dar AR, Razzaq S (2018) Building Ontology for Library Management System Using Dewey Decimal Classification Scheme. J Comput Eng Inf
Technol 7:1.
doi: 10.4172/2324-9307.1000194
Volume 7 • Issue 1 • 1000194 Page 6 of 8
[Note: Figure shows domain ontology taxonomy for the library which is easy to understand for the human].
Figure 6: Library Ontology Taxonomy using Owl Viz.
Figure 7: OntoGraf is part of the protégé-Owl editor and available as plug-in at the protégé website page.
Citation: Dar AR, Razzaq S (2018) Building Ontology for Library Management System Using Dewey Decimal Classification Scheme. J Comput Eng Inf
Technol 7:1.
doi: 10.4172/2324-9307.1000194
Volume 7 • Issue 1 • 1000194 Page 7 of 8
this system. Users can only write the name of the book title or any
string from within the title. Library ontology will show results to
users which are very relevant and accurate. Below are some queries
and their results using SPARQL inside protégé. Another important
feature of this system is that a user does not have to give full title of
the book. Instead the user just needs to provide a string from the
book title and the system works very fine. A user can also give full
title to the library ontology system. Traditional DBMS shows relevant
and irrelevant results by searching in database when a book search
is made in the library. For example, the user wants to search books
having ‘computer science’ or ‘Cisco network’ or ‘networking academy’
in the title. Traditional DBMS shows too much irrelevant information
about the book title. Figures 8-10 show query examples of the prosed
system which show very relevant and accurate information according
to user search criteria.
Conclusion
There are many library database management systems, practically
used by different organizations, such as insignia software. In such
software, users perform search by entering keywords. These systems
present results to users with a lot of mess in terms of irrelevant
information about book searching. The proposed approach presents
a library ontology development based on five rules. It captures the
semantic information using DDC and book parameters. The proposed
methodology extracts hierarchy of classes from DDC and uses the
classes in protégé for ontology development. Protégé follows the same
class and subclass relation as it is in DDC scheme. Experimental results
in SPARQL protégé show that this approach performs very well and
finds the results semantically. This system shows that ontology based
LMS provides exact and relevant information. In the future, we will
design a semantic web application in Java using Net Beans/Eclipse.
Figure 8: Book title with ‘computer science’.
Figure 9: Book title with ‘Cisco network’.
Citation: Dar AR, Razzaq S (2018) Building Ontology for Library Management System Using Dewey Decimal Classification Scheme. J Comput Eng Inf
Technol 7:1.
doi: 10.4172/2324-9307.1000194
Volume 7 • Issue 1 • 1000194 Page 8 of 8
Figure 10: Book title with ‘networking academy’.
We will integrate our designed ontology with the help of the OWL
API in Net Beans/Eclipse where a user can query the new friendly
interface with easy semantic search.
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Author Affiliation Top
1Lecturer, Department of CS&IT, University of Kotli Azad Jammu & Kashmir,
Pakistan
2Junior Lecturer, Department of CS&IT, University of Kotli Azad Jammu &
Kashmir, Pakistan