READIT - 2009 - Indira Gandhi Centre for Atomic Research

Knowledge Management and Ontology Representation
For Fast Breeder Test Reactor
N.Madurai Meenachi , M.Sai Baba, B.Babu, B.Anandapadmanaban and V.Ramanathan
Indira Gandhi Centre for Atomic Research, FBTR, Kalpakkam
meenachi@igcar.gov.in,msb@igcar.gov.in
ABSTRACT
The Knowledge Management (KM) technology is required to be developed to optimize the
everchanging environment. KM comprises a range of practices used in an organisation to identify, create,
represent, distribute and enable adoption of insights and experiences. Such insights and experiences comprise
knowledge, either embodied in individuals or embedded in organisational processes or practice. It employs the
suitable mechanism for obtaining and integrating the collective wisdom from all members in an organization
leading to enhance the ability of adaptation and innovation. It facilitates in preserving both tacit and explicit
knowledge. It is all about converting the available raw data into a reusable repository for any future service
being offered which needs similar experiences. The Fast Breeder reactor is characterized by information that is
available on a need-to-know basis, with a mix of security structures and protocols to determine who can see
what. Trust in management increases knowledge sharing through reducing fear of losing one's unique value and
improving willingness to document knowledge. These results have important implications at both a managerial
and theoretical level. In this paper the knowledge management system and ontology representation using
Protégé in fast breeder test reactor are discussed. Ontologies are at the heart of semantic web. They define
concepts and relationship that make global interoperability. CDPS (central Data processing system) is taken as
case study and discussed about the representation of knowledge ontology using Protégé 4.0.1.
1. INTRODUCTION
Knowledge Management involves knowledge base to store knowledge inventories
and values among the accessible knowledge items. Knowledge base is the absolute collection
of all expertise, experience and knowledge available within an organization [1]. Knowledge
base development starts with the knowledge acquisition stage, in which knowledge engineers
have to acquire the data and information from domain experts and other sources. Knowledge
is not same as information. Knowledge is dynamic. It can be owned, processed and used can
used only by people. However, Information is static which can also exists without application
and exchange by people.
Knowledge Management is classified as Explicit and Implicit knowledge. Explicit
knowledge includes reports, which can be easily described and codified for storage and
dissemination. Whereas tacit knowledge is highly personal, context specific, and can only be
manifested through its application and practice. This cannot be easily codified. This is vital
knowledge for any organizational growth because it will save time and efforts in solving the
various types of issues and problems. Leonard-Barton and Sensiper [2] state that tacit
knowledge is mainly developed through a process of trial and error encounter in practice.
Tacit and Explicit knowledge interact and interchange with each other in the creative
activities of human beings. Knowledge is created through social interaction of the two types
of knowledge.
A knowledge management activity consists of knowledge creation, acquisition,
representation, disposal, application, estimate and update. Proper utilization of knowledge
asset is the foremost goal of any organization. In any organization, knowledge will be
continually generated and used. KM is not to manage all knowledge, but to manage the
knowledge that is most important to the organization. It involves getting the right information
to the right people at the right time, and helping people create and share knowledge and act in
way that will measurably improve individual and organizational performance [3].