DIKW
From Wikipedia, the free encyclopedia
| This article does not cite any references or sources. (February 2007) Please help improve this article by adding citations to reliable sources. Unverifiable material may be challenged and removed. |
| This article or section needs copy editing for grammar, style, cohesion, tone or spelling. You can assist by editing it now. A how-to guide is available. (March 2007) |
| This article may require cleanup to meet Wikipedia's quality standards. Please improve this article if you can. (March 2007) |
| This article or section is in need of attention from an expert on the subject. Please help recruit one or improve this article yourself. See the talk page for details. Please consider using {{Expert-subject}} to associate this request with a WikiProject |
| This article or section may contain original research or unverified claims. Please improve the article by adding references. See the talk page for details. (June 2008) |
DIKW is the proposed 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. The term DIKW is applied in the fields of information science and knowledge management.
Contents |
[edit] Description
The DIKW model assumes the following chain of action:
- Data come 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 deals with the future, as it takes implications and lagged effects into account.[citation needed]
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, can knowledge 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.
- Specific local properties of Data:[citation needed]
- factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation (the data is plentiful and easily available.)
- information output by a sensing device or organ that includes both useful and irrelevant or redundant information and must be processed to be meaningful.
- Specific local properties of Information:[citation needed]
- knowledge obtained from investigation, study, or instruction
- intelligence, news
- facts, data.
- Specific local properties of Knowledge:[citation needed]
- the range of one's information.
- Specific local properties of Wisdom:[citation needed]
- accumulated philosophic or scientific learning: knowledge.
- 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, there are four levels in the 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 resulting decisions will also be flawed.
[edit] Critical comments
The proposed use of data, information, knowledge and wisdom is not congruent with the definitions in Wikipedia. They are described intuitively and their interrelations seem to be not always congruent. In practice, any concrete formal application of the DIKW conceptualization does not exist(see: *). On the other hand, some false information about popularity of this method are included on the private phd student pages of Nikhil Sharma (external link), what is easy to see using Google search for “Knowledge Pyramid” with numerous very different definitions. DIKW is also diffused using pseudo-information pages on the web (see for example *).
[edit] References
- Ackoff, Russell L. (1989). "From Data to Wisdom". Journal of Applied Systems Analysis 16: 3–9.
- Zeleny, Milan (1987). "Management Support Systems: Towards Integrated Knowledge Management". Human Systems Management 7 (1): 59–70.
[edit] External links
- Nikhil Sharma: The Origin of the “Data Information Knowledge Wisdom” Hierarchy
- Data, Information, Knowledge, and Wisdom by Gene Bellinger, Durval Castro, Anthony Mills
- Jennifer Rowley: The wisdom hierarchy: representations of the DIKW hierarchy. In: Journal of Information Science, Vol. 33, No. 2, 163-180 (2007)

