Knowledge Management Basics
Practical Action
In the context of a population survey the above data become meaningful, i.e. – the name of a
village, the number of households below the poverty line and the percentage of adult people
who are illiterate. A local government can use this information when planning a poverty
eradication project or a computer program can produce a summary report based on a
collection of data records. In both cases the data become information (have a meaning) in the
context of a processor (person or machine/computer) that “understands” these data items.
Information is a data item presented in a context that allows inferring from and
about the meaning of the data by a human mind or by the machine.
The analysis of the population data in order to assess the level of poverty and propose
possible solutions to the problem requires knowledge. The first thing one has to know is how
to analyze the data; how the poverty is defined; what the possible ways to alleviate poverty
are; what the people’s reaction to poverty alleviation programs would be; who can help plan
and deliver a program, etc. In dealing with information we have explicit knowledge (facts,
procedures, experiences that can be described in documents and databases, encoded as
computer programs or presented by means of communication) and tacit knowledge
(judgments, insights, skills, beliefs, etc. that cannot be explicitly formulated but are critical
in understanding information and problems).
Information considered/processed/understood in order to solve a problem, take an
action or answer a question together with its broader context of related information
and actions is called knowledge.
We will not dwell any further on the definition of knowledge. There is no consensus on what
knowledge is and the discussion will probably continue as long as people will try to
understand how the human mind works and what the limits to human cognition are. In this
paper we take a very pragmatic approach to defining knowledge in the context of computer-
based systems and practical applications of knowledge management. We concentrate on
methods and tools used to collect, codify, organize, retain, communicate and transfer
knowledge and thus to enhance the ability to use information to solve problems.
The main sources of difficulty with understanding and defining knowledge in the context of
computer-based systems are:
- the long history of associating knowledge with only the human mind (… and there is a
good reason for that since knowledge, in a broad sense, encompasses inferring/thinking ,
beliefs, logic, intuition, cognition, truths, intelligence);
- in practice, computer programs are a form of encoding of some knowledge (e.g.
arithmetic operations, analysis of chemical processes data, text formatting, playing
chess).
Knowledge in the context of a computer system is a representation (text, data structures,
structures of formal knowledge description languages) of facts, objects, phenomena,
abstractions (factual knowledge) and procedures/processes (procedural knowledge including
tacit knowledge). Representations allow automatic operations on knowledge (problem solving,
decision-making support, information retrieval, creating new knowledge, dissemination). We
may say that knowledge is the ability to solve problems and answer questions by retrieving
(possessing) relevant information. Intelligence is the ability to create new knowledge. These
working definitions should suffice for a general discussion.
What it means to manage knowledge?
The need for computer-based knowledge management systems was identified when large
companies realized that making huge databases and document repositories available was
insufficient for solving problems in environments where users’ knowledge of how to use the
data and how to extract relevant knowledge from documents was inadequate. Managing
codified knowledge is only one aspect of knowledge management and relatively easy to
accomplish.
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