A fundamental corner stone for all information and knowledge literature is the data-information-knowledge-wisdom (DIKW) hierarchy model. A beloved child has many names, thus the hierarchy is also called: information hierarchy, knowledge pyramid and wisdom hierarchy. Essentially this model involves four entities of: data, information, knowledge and wisdom. These are ordered in a hierarchical structure (Figure above) with respect to one another in order to explain the relationship and transformation process between these various entities (Rowley, 2007). The idea with a hierarchical structure is that the higher types of entities “includes the categories that fall below it” (Ackhoff, 1989).
The figure in the beginning of the post is an illustration of the DIKW pyramid, which includes vectors that indicates the characteristics in the aspect of meaning and value (Rowley, 2007).
According to Aven (2012) the origins of the DIKW hierarchy in its current state and form can be traced back to the 80s, however, the first appearance of the model was registered in T.S. Eliot’s poem “The Rock” in 1934 with the following citation:
“Where is the life we have lost in living?
Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in the information?”
The lowest element of the DIKW pyramid is data. Data is in its purest form is plain symbols, such as numbers or letters, and is per definition unorganized or unprocessed and lacks whatsoever any meaning or value (Rowley, 2007). Therefore, data can be seen as observable and measurable properties that are represented in symbols.
Information is defined as data that is given a context or data that have been organized into a structure (Rowley, 2007). The fundamental principle is that a refining process has been applied to the data, which now evolves to information that possesses a meaningful purpose or value.
Knowledge as a concept is far more complex to comprehend than the other lower elements. Aven (2012) defines knowledge as structured and organized information as a result from cognitive processing and validation. Other definitions go into similar abstractions that knowledge is generated as a mix of both data and information, where the human contribution of experiences and rules increases over time. An oversimplified suggestion is that knowledge answers to the “how” questions (Cooper, 2014). Despite the differences, all definitions agree that knowledge can be divided into two categories: tacit and explicit knowledge. Where explicit knowledge can be transferred and documented, while tacit knowledge cannot because it is part of an individual’s human mind (Bocij, Chaffey & Hickie, 2003). All in all, Rowley (2007) summarises this well that all definitions of knowledge combine a mix of information, understanding, capability, experience, skills and values.
Wisdom is arguably the most elusive of all these four elements and concepts. According to Ackoff (1989) wisdom is the only element that concerns with the future, while the other elements deal with the past. A similar view is shared with Awad and Ghaziri (2004) who suggest that “Wisdom is the highest level of abstraction, with vision foresight and the ability to see beyond the horizon”. Rowley (2007) elaborates the definition even further and concludes that wisdom involves moral and ethics, such as human intuition, understanding, interpretation and actions. Cooper (2014) likewise defines wisdom as “an extrapolative process which includes knowledge in an ethical and moral framework”. Another definition by Perwitt (2002) presents wisdom as a double loop of learning in reflection to the three earlier element stages, though an integration of both mind and soul are required in order to obtain wisdom. Therefore, wisdom has a clear element of spirituality embedded to it.
On that note….
Finally, the DIKW pyramid can be well summarised and described by Zeleny’s (2005) appealing metaphor as follow: “know-nothing” (data), “know-what” (information), “know-how” (Knowledge) and “Know-why” (Wisdom).
Ackoff, R.L., 1989. From data to wisdom. Journal of applied systems analysis, 16(1), pp.3-9.
Aven, T., 2013. A conceptual framework for linking risk and the elements of the data information–knowledge–wisdom (DIKW) hierarchy. Reliability Engineering & System Safety, 111, pp.30-36
Awad, E.M. and Ghaziri, H.M., 2004. Knowledge management, 2004. ed: Prentice-Hall, Upper Saddle River, New Jersey.
Cooper, P., 2014. Data, information, knowledge and wisdom. Anaesthesia & Intensive Care Medicine, 15(1), pp.44-45.
Rowley, J.E., 2007. The wisdom hierarchy: representations of the DIKW hierarchy. Journal of information science. 33(2), pp. 163–180
Zeleny, M., 2005. Knowledge-information autopoietic cycle: towards the wisdom systems. International Journal of Management and Decision Making, 7(1), pp.3-18.