CHAPTER 2: KNOWLEDGE AS A CONCEPT
2.3 Data, information and knowledge
In the business world employees need data, information and knowledge for problem solving, decision-making processes and to create new knowledge. Access to these concepts comes in a vast number of ways.
Data, information and knowledge are derived from reading, talking to colleagues, databases, and from experiencing and noticing things in the environment. No one method is necessarily more important than the others, but will depend on the context of the scenario. What is important is how organisations create, access, share and use data, information and knowledge. The extent to which the organisation can be said to be efficient is the extent to which it applies available data, information and
knowledge. The final step would be to move from knowledge to wisdom. Wisdom can be thought of knowledge that has been applied.
The task of defining these concepts, especially knowledge, has received attention for many years. Lately, the question of the precise nature of data, information and knowledge has been raised anew, not only in information science but also in organisational environments. Knowledge is also an interdisciplinary field and incorporates many disciplines such as philosophy, economics, management, information technology, human resources and artificial intelligence, to name a few (Nonaka, 1994: 12-13).
The wide variety of perspectives and definitions, which are available illustrate that data, information and knowledge are used quite differently, depending on context and intention of use. A basic problem in connection with these concepts is that they can also be used interchangeably (Wilson, 1996: 2-4). Information and knowledge can be seen as closely related in complementary stages along the same road. As such they perform essential roles in the problem-solving and decision-making processes.
Wilson (1996:1-9) presents a useful explanation of the relationship between
information and knowledge with the “processing hierarchy” in Figure 2.1. He shows that by selecting data information can be produced; by selecting and combining information, knowledge can be generated; from this decisions can be made and action taken.
Action
↑ Decision
↑ Knowledge
↑ Information
↑ Data
Figure 2.1: The processing hierarchy: data, information and knowledge in a hierarchy based on decision-making and problem solving (Wilson, 1996: 4)
According to Debons (1988: 5) data, information, knowledge and wisdom can be viewed as part of a continuum, one leading into another, each the result of actions on the preceding, with no clear boundaries between them. The continuum is illustrated in Figure 2.2.
Event→Symbols→Rules→Formulations
Wisdom Knowledge
Information Cognitively driven segment ---
Data Data-driven segment
Figure 2.2: The knowledge continuum (Debons, 1988: 5)
The event is an occurrence, some condition or change in the state of the world. This state or condition has to be represented if humans have to deal with it. Invented symbols - numbers, letters, glyphs or pictures - become representations of the event.
Rules are used to organise such representations and to generate a datum (singular) or data (plural). Data are perceived when one or more senses are stimulated. When a person is exposed to these stimuli, he/she becomes aware (a state of consciousness) of data about the event.
At this point, information has been acquired. He/she is now informed. Being informed means that he/she is aware of some occurrence, but nothing else. Humans can respond to this information in a number of ways: they can store it in their minds (called memory) or they can record or enter in a computer file. This physical or cognitive representation of data is called information.
When meaning or understanding is applied to awareness, higher cognitive processes are involved. When such processes are applied, a person senses that he/she
understands and can apply what is understood to those things that require resolution.
This understanding enables people to analyse situations and to put things into their proper perspective. Thus when he/she goes beyond awareness (by own intellectual actions), knowledge has been obtained. Knowledge can be given physical
representation by packaging it in books, records or databases. The ultimate step in the knowledge continuum is wisdom, which always involves the inclusion of values in judgement (Debons, 1988: 6-10).
The sequence data → information → knowledge→ wisdom sequence represents an emergent continuum. Although data is a discrete entity, the progression to
information, to knowledge and finally to wisdom does not occur in discrete stages of development. One progresses along the continuum as one’s understanding develops.
Each transformation (e.g. symbols to data, data to information ) represents a step upward in human cognitive functioning (Debons, 1988: 9).
According to Harris (1996: 1): “… the lowest level of known facts is data. Data has no intrinsic meaning. It must be sorted, grouped, analysed and interpreted. When data is processed in this manner, it becomes information. Information has a substance and a purpose. However, information does not have meaning. When information is
combined with context experience, it becomes knowledge”.
Knowledge is the combination of information, context and experience. Context is an individual’s framework for viewing life. This includes influences like values, religion, cultural heritage and gender. Experience is previously acquired knowledge. When knowledge is transferred from one person to another, the knowledge is drawn into the receiver’s context and experience. The knowledge is interpreted according to the receiver’s context and experience (Harris, 1996: 4).
Turban and Frenzel (1992: 10-12) approach data, information and knowledge from a computer science and specifically an artificial intelligence perspective:
• Data refers to numeric or alphanumeric strings that by themselves do not have meaning. These can be facts or figures to be processed.
• Information is data organised so that it is meaningful to the person receiving it.
• According to the two authors knowledge has several definitions:
- Understanding
- A clear and certain perception of something - Learning
- All that can be perceived by the mind - Practical experience or skill
- Cognisance and recognition, and
- Organised information applicable to problem-solving Once again knowledge is internal to the human being and therefore subjective whereas information and data remain external and objective.
According to the above-mentioned authors data, information, knowledge and wisdom can be seen as a continuous whole, each is followed by the other and the degree of human involvement divides the concepts. However, a symbiotic relationship exists between information and knowledge (Snowden, 1999: 11). Evidence of this symbiotic relationship can be found in Nonaka and Takeuchi’s SECI model (see Figure 2.3).
Regardless of whether data, information and knowledge are seen as a continuous whole or as a symbiotic relationship, the following concepts form the foundation of this study:
• Data: Letters, numbers, lines and symbols used to represent events and their state, organised according to formal rules and conventions
• Information: The cognitive state of awareness (as being informed) given representation in physical form (data). This physical representation facilitates the process of knowing
• Knowledge: The cognitive state beyond awareness. Knowledge implies an active involvement and understanding and the ability to extend the level of understanding to meet life’s contingencies. Knowledge can also refer to the organised record of human experience given physical representation (books, reports).