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DIKW

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DIKW is data, information, knowledge, wisdom: 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. As such, DIKW is a model that is useful to understanding analysis and the importance and limits of conceptual works. DIKW is used primarily in the fields of Information science and Knowledge Management.

History

The hierarchy can be traced back to a poem by T.S. Eliot, The Rock, written in 1932. In the opening stanza he wrote: 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 information?. Harlan Cleveland built the hierarchy on this basis in Information as Resource, an article in the magazine The Futurist, December 1982. It was subsequently expanded by Milan Zeleny and Russell L. Ackoff. [link]

Application

The DIKW model is used as an aide to research and analysis by applying the following chain of action. 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

1: factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation 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
(1): knowledge obtained from investigation, study, or instruction (2) : intelligence, news (3) : facts, data.

Knowledge

the range of one's information.
Wisdom 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

Russell Ackoff's view

According to Russell Ackoff, 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.

External links

 


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