Information space: data, information and knowledge. Culture and the evolution

1.

INFORMATION SPACE: DATA, INFORMATION AND
KNOWLEDGE. CULTURE AND THE EVOLUTION OF
THE INFORMATION SPACE: INFORMATION,
INDIVIDUALS, AND ORGANIZATIONS

2.

UNDERSTANDING THE DIFFERENCES BETWEEN DATA,
INFORMATION AND KNOWLEDGE
• The words data, information and knowledge are often thrown
around as substitutes for each other. However, these three terms
technically mean separate things.
• You might ask, “Why bother being pedantic with the terms? What
difference does it make?”
• Well, if we want to manage knowledge, we need to clarify the
terms and understand the different meanings at play.

3.

DATA, INFORMATION AND KNOWLEDGE
• There are three generic things we usually refer to when we use the
words ‘data’, ‘information’ and ‘knowledge’.
1. when we talk about things that we know about: concepts, facts, and
methods that we are familiar with.
2. when we deal with practical know-how: applying our grasp of
concepts, facts, and methods to create action or make things happen.
3. when we refer to a body of knowledge: accumulated knowledge in
books and other forms of documentation.

4.

DATA
• Data are raw facts and figures with no fundamental meaning. Data
plainly reports part of a situation without providing an
interpretation.
• It is an unprocessed form of knowledge that doesn’t convey value or
significance.
• For data to have some useful meaning, it has to be organised,
analysed and interpreted.
• Data can be:
Quantitative: when data can be counted or measured like cost,
weight, and volume.
Qualitative: when data describes things like name, color, and
shape.

5.

INFORMATION
• Information is processed data.
• It is organised, classified, structured and provides meaningful and useful context.
• In contrast to data, information has meaning.
• “Data becomes information when its creator adds meaning. We transform data
into information by adding value in various ways.”
• There are several important processes that convert data to information:
Calculation: data are mathematically or statistically scrutinised
Categorisation: data are sorted into groups or classes
Condensing: summarising data to be more concise
Contextualising: gathering data for a purpose
Correcting: editing errors out from the data

6.

KNOWLEDGE
• Davenport and Prusak proposed a working definition of knowledge framed in
a practical sense of organisational knowledge that it is “broader, deeper and
richer than data or information”.
• Knowledge is a fluid mix of framed experience, values, contextual information,
and expert insight that provides a framework for evaluating and incorporating
new experiences and information.
• This idea of knowledge is an amalgamation of information, that knowledge is a
state of being, exists outside of the ‘knowers’, and has the capacity to effect
action.

7.

EXPLICIT, IMPLICIT, AND TACIT KNOWLEDGE

8.

EXPLICIT KNOWLEDGE
• Explicit knowledge is knowledge that is easily expressed,
communicated and captured in text documents, diagrams,
illustrations, and product specifications among other things.
• Explicit knowledge can be explicitly stated, written down, or
codified as information.
• It is knowledge that can be easily expressed and shared with others,
either through language or other forms of communication.

9.

IMPLICIT KNOWLEDGE
• Implicit knowledge is displayed knowledge that can be captured.
• A simple example would be someone performing a task and how they
execute that task is a display of implicit knowledge.
• Identifying and capturing that implicit knowledge can turn it into
explicit knowledge that can be used across similar tasks.
• Implicit knowledge is knowledge that is not consciously known or
understood but is demonstrated through our actions or behaviour (e.g.,
knowing how to ride a bike).
• Implicit knowledge is often unconscious and automatic and can be
difficult to recognize or change.
• It is inferred or acquired through experience or exposure. It is often
unconscious and automatic and is difficult to articulate.

10.

TACIT KNOWLEDGE
• Tacit knowledge is less tangible and more difficult to articulate and transfer.
• It is knowledge in the form of individual skills, wisdom, experience and ideas.
• Unlike explicit knowledge, tacit knowledge is usually passed on through exhaustive
exposure to and continuous practice with the person of knowledge.
• Everyday life examples include language and intuition – knowledge that is harder to
systematise or automate.
• It is experiential and context-specific, and it is often acquired through practice,
observation, and interaction with others. It includes things that are deeply personal and
unique to an individual, such as skills, habits, and experiences.
• The main difference between tacit and implicit knowledge is that tacit knowledge is
difficult to express or communicate, while implicit knowledge is not consciously known or
understood.

11.

DECLARATIVE AND PROCEDURAL KNOWLEDGE
• Psychologists also classify knowledge into declarative and procedural.
• Declarative knowledge is practically similar to explicit knowledge as it
is knowledge that describes facts, methods and procedures.
• Procedural knowledge leans more towards the knowledge of doing
something.
• Some experts in the field equate this to implicit knowledge while some
view it as tacit knowledge.
• Procedural knowledge is difficult to articulate and document in the form
of text, diagrams and so on.

12.

• "Knowledge is a fluid mix of utilized information leading
to experience, values, contextual information, expert
insight, and grounded intuition that provides an
environment and framework for evaluating and
incorporating new ideals. In organizations it often
becomes embedded not only in documents or
repositories, but also in organizational routines, culture
practices and norms."

13.

14.

WHAT IS THE DIFFERENCE BETWEEN DATA AND
INFORMATION?
• Data and information are closely related, but they are different. Data refers
to raw facts and figures that have not been processed or organized. It is the
raw material from which information is derived.
• Conversely, information refers to data that has been processed, organized,
and presented meaningfully. Information is often more helpful and valuable
than raw data because it has been transformed into a more accessible form
for people to understand and use.
• Information is a broad term that refers to data or facts. This can include news
articles, data sets, reports, instructions, manuals, and more. It can be used to
convey ideas, concepts, or instructions, and it can also be used to support
problem-solving, decision-making, and other efforts.

15.

WHAT IS THE DIFFERENCE BETWEEN INFORMATION AND
KNOWLEDGE?
• Knowledge and information are related but distinct concepts.
• Information refers to data or facts that are presented or communicated. It can be
true or false and can be conveyed through various mediums, such as spoken or
written language, images, or numbers.
• Knowledge is a broad term that refers to the understanding and familiarity with a
particular subject or area. It is a collection of facts, information, and skills that are
acquired through experience or education. It includes the understanding of complex
ideas and concepts and the ability to apply this understanding to new situations.
• Knowledge refers to an understanding or comprehension of a subject or
information. It involves the ability to think about and apply information
meaningfully. In other words, knowledge results from learning, processing, and
applying information.

16.

• A common mistake in understanding knowledge is assuming that
knowledge in our mind is the same as knowledge that has been recorded,
such as on paper or digitally.
• Knowledge only exists within the mind, whether explicit, tacit, or implicit.
Once knowledge is recorded or codified in any way, it becomes
information.
• In other words, we need knowledge to code knowledge into information
and knowledge to decode information into knowledge.
• Thus, another way of looking at things is to say that we have uncodified
knowledge (knowledge that exists in the mind) and codified
knowledge (information).

17.

AN ALTERNATIVE PERSPECTIVE ON DATA,
INFORMATION, AND KNOWLEDGE
• Another perspective on data, information, and knowledge is through the lens of our senses.
• The brain processes sensory data from the environment to create information and
knowledge.
• This process begins with detecting stimuli by specialized sensory receptors.
• These receptors convert physical stimuli, such as light and sound waves, into neural signals
or sensory data that is transmitted to the brain.
• This data is unprocessed and unorganized. However, once it reaches the brain, it is
processed, organized, and given meaning, transforming it into information.
• On reaching the brain, it is first processed in the primary sensory cortex, which is
responsible for identifying the basic features of the stimuli, such as color, shape, and
movement.
• From there, the information is passed to higher-level areas of the brain, where it is
interpreted and integrated with information from other senses and stored knowledge.

18.

• This process of interpretation and integration allows the brain to create
meaning from sensory data and construct a coherent representation of the
world around us.
• It also allows us to predict future events based on past experiences and stored
knowledge.
• In addition, the brain also uses feedback loops to continuously update and
refine its representations of the world by receiving new information and
comparing it to stored knowledge to see if any revisions are needed.
• The brain’s ability to process sensory data is a complex process that involves
the detection of stimuli by specialized receptors, their initial processing in the
primary sensory cortex, and their subsequent interpretation and integration
with stored knowledge in higher-level areas of the brain, which allows us to
create meaning, make predictions and continuously refine our understanding of
the world around us.

19.

WRITTEN LANGUAGE IS NOT INFORMATION
• From this sensory perspective, written text can be viewed as simply a pattern
of squiggles or dots on a surface such as paper or a computer screen. Light
reflects off this pattern, enters the eye, and is encoded and sent to the brain as
a data stream. This data stream is then processed by the brain and turned into
information, such as the words and meaning behind the written text.
• This means that written language has no inherent meaning until the brain
interprets it.
• So from this perspective, data, information, and knowledge reside within the
brain.

20.

THE BRAIN-AS-COMPUTER METAPHOR
• The argument that data, information, and knowledge reside in the brain is
known as the “brain-as-computer” metaphor.
• This metaphor explains how the brain can perceive, process, and understand
the world around it. It is often used as a basis for understanding cognitive
functions such as memory, perception, and decision-making.

21.

SO WHAT DOES THIS MEAN FOR REALITY?
• Reality is the state of things as they exist in the world, independent of our
perception or understanding.
• The brain-as-computer metaphor suggests that the brain takes in “data” from
the world through the senses and uses it to construct a representation of
reality.
• Therefore it can be seen that the reality we perceive and understand is not
the same as the reality that exists independently. So, according to this
perspective, reality exists independently of our understanding of it.

22.

WHAT’S WRONG WITH THIS METAPHOR?
• The “brain-as-computer” metaphor is a valuable tool for understanding certain
aspects of cognitive function, but it has some limitations and potential
drawbacks when applied too broadly, e.g.:
• The brain is much more complex than a computer.
• The brain is not a passive information processor.
• The brain is embodied and embedded.
• The brain is not digital.
• The brain is not rule-based.

23.

• In summary, while the brain-as-computer metaphor can be a helpful
way to understand certain aspects of cognitive function, it is
essential to recognize its limitations and not apply it too broadly.
• The brain is a much more complex and dynamic system than a
computer which we still don’t understand fully.

24.

KNOWLEDGE IS BEST SHARED THROUGH CONVERSATION
• We always know more than we can say, and we will always say more than we can write
down. (Dave Snowden)
• Because of this, knowledge is best shared through conversation.
• In a face-to-face conversation, you can offer information about the issue; you can
probe deeper into the situation; you can gain a sense of what the other already
knows, and so determine at what level to construct your answer; you can ask about
the meaning of a term you are not familiar with; you can seek the reasoning behind
a conclusion if it’s not evident and you can correct false assumptions.
• The speaker and listener repeatedly swap places many times in a short period; the
listener frequently interrupts the speaker, and the roles change. Both parties actively
try to make sense of what the other is attempting to convey.