DIKW

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DIKW is a proposal of the structuring of data, information, knowledge and wisdom in an information hierarchy where each layer adds certain attributes over and above the previous one. Data is the most basic level; Information adds context; Knowledge adds how to use it; and Wisdom adds when to use it^{[citation needed]}. As such, DIKW is a model that can be useful to understanding analysis and the importance and limits of conceptual works. DIKW intend to be applicable in the fields of Information science and Knowledge Management. Its idea was suggested by Milan Zeleny and Russell L. Ackoff^{[citation needed]}.

1 Description
2 Russell Ackoff's view
3 References
4 External links

[edit] Description

The DIKW model is based on the assumption of the following chain of action^{[citation needed]}.

Data comes in the form of raw observations and measurements.
Information is created by analyzing relationships and connections between the data. It is capable of answering simple "who/what/where/when/why" style questions. Information is a message, there is an (implied) audience and a purpose.
Knowledge is created by using the information for action. Knowledge answers the question "how". Knowledge is a local practice or relationship that works.
Wisdom is created through use of knowledge, through the communication of knowledge users, and through reflection. Wisdom answers the questions "why" and "when" as they relate to actions. Wisdom takes care of the future, it takes implications and lagged effects into account.

Data has commonly been seen as simple facts that can be structured to become information. Information, in turn, becomes knowledge when it is interpreted, put into context, or when meaning is added to it. There are several variations of this widely adopted theme. The common idea is that data is something less than information, and information is less than knowledge. Moreover, it is assumed that we first need to have data before information can be created, and only when we have information, knowledge can emerge. Data are assumed to be simple isolated facts. When such facts are put into a context, and combined within a structure, information emerges. When information is given meaning by interpreting it, information becomes knowledge. At this point, facts exist within a mental structure that consciousness can process, for example, to predict future consequences, or to make inferences. As the human mind uses this knowledge to choose between alternatives, behavior becomes intelligent. Finally, when values and commitment guide intelligent behavior, behavior may be said to be based on wisdom.

Data

Specific local properties^{[citation needed]}:

1: factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation <the data is plentiful and easily available.>

2: information output by a sensing device or organ that includes both useful and irrelevant or redundant information and must be processed to be meaningful.

Information

Specific local properties ^{[citation needed]}:

(1): knowledge obtained from investigation, study, or instruction

(2) : intelligence, news

(3) : facts, data.

Knowledge

Specific local properties ^{[citation needed]}:

(1) the range of one's information.

Wisdom

Specific local definition ^{[citation needed]}:

(1) accumulated philosophic or scientific learning: Knowledge. (2) wise attitude or course of action.

According to these definitions, “data” is the basic unit of “information,” which in turn is the basic unit of “knowledge,” which itself is the basic unit of “wisdom.” So, we have four levels in our understanding and decision-making hierarchy. The whole purpose in collecting data, information, and knowledge is to be able to make wise decisions. However, if the data sources are flawed, then in most cases the decisions will also be flawed.

[edit] Russell Ackoff's view

This is an essay. It is not a policy or guideline. Please update the page as needed, or discuss it on the talk page.

According to Russell Ackoff^{[citation needed]} , a systems theorist and professor of organizational change, the content of the human mind can be classified into five categories: Data, Information, Knowledge, Understanding and Wisdom.

Ackoff adds another level i.e., understanding between knowledge and wisdom. He indicates that the first four categories relate to the past; they deal with what has been or what is known. Only the fifth category, wisdom, deals with the future because it incorporates vision and design. With wisdom, people can create the future rather than just grasp the present and past. But achieving wisdom isn't easy; people must move successively through the other categories.

A further elaboration of Ackoff's definitions follows:

Data... data is raw. It simply exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. It does not have meaning of itself. In computer parlance, a spreadsheet generally starts out by holding data.

Information... information is data that has been given meaning by way of relational connection. This "meaning" can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it.

Knowledge... knowledge is the appropriate collection of information, such that it's intent is to be useful. Knowledge is a deterministic process. When someone "memorizes" information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, an integration such as would infer further knowledge. For example, elementary school children memorize, or amass knowledge of, the "times table". They can tell you that "2 x 2 = 4" because they have amassed that knowledge (it being included in the times table). But when asked what is "1267 x 300", they can not respond correctly because that entry is not in their times table. To correctly answer such a question requires a true cognitive and analytical ability that is only encompassed in the next level... understanding. In computer parlance, most of the applications we use (modeling, simulation, etc.) exercise some type of stored knowledge.

Understanding... understanding is an interpolative and probabilistic process. It is cognitive and analytical. It is the process by which I can take knowledge and synthesize new knowledge from the previously held knowledge. The difference between understanding and knowledge is the difference between "learning" and "memorizing". People who have understanding can undertake useful actions because they can synthesize new knowledge, or in some cases, at least new information, from what is previously known (and understood). That is, understanding can build upon currently held information, knowledge and understanding itself. In computer parlance, AI systems possess understanding in the sense that they are able to synthesize new knowledge from previously stored information and knowledge.

Wisdom... wisdom is an extrapolative and non-deterministic, non-probabilistic process. It calls upon all the previous levels of consciousness, and specifically upon special types of human programming (moral, ethical codes, etc.). It beckons to give us understanding about which there has previously been no understanding, and in doing so, goes far beyond understanding itself. It is the essence of philosophical probing. Unlike the previous four levels, it asks questions to which there is no (easily-achievable) answer, and in some cases, to which there can be no humanly-known answer period. Wisdom is therefore, the process by which we also discern, or judge, between right and wrong, good and bad. I personally believe that computers do not have, and will never have the ability to possess wisdom. Wisdom is a uniquely human state, or as I see it, wisdom requires one to have a soul, for it resides as much in the heart as in the mind. And a soul is something machines will never possess (or perhaps I should reword that to say, a soul is something that, in general, will never possess a machine).

It has been contended that the sequence is a bit less involved than described by Ackoff . It is understanding that support the transition from each stage to the next. Understanding is not a separate level of its own.

[edit] References

Russell L. Ackoff, "From Data to Wisdom," Journal of Applied Systems Analysis 16 (1989): 3-9.
Milan Zeleny, "Management Support Systems: Towards Integrated Knowledge Management," Human Systems Management 7, No 1 (1987): 59-70.