The concept of DIKW hierarchy, (i.e., transforming Data, to Information, to Knowledge, to Wisdom) has been utilized in numerous DSS and by various industries. Stenmark [1] says: "It has often been pointed out that data, information, and knowledge are not the same, but despite efforts to define them, many researchers use the terms very casually. In particular, the terms knowledge and information are often used interchangeably, even though the two entities are far from identical."
How can we define, conceptualize, distiguish, explain and characterize DIKW hierarchy rigorously?
[1] Stenmark, D. (2002). Information vs. Knowledge: The Role of Intranets in Knowledge Management. In Proceedings of HICSS-35, IEEE Press, Hawaii, January 7-10, 2002. [Available at http://w3.informatik.gu.se/~dixi/km/]
Dear Mahmoud,
I would be glad if I were able to characterise merely the knowledge itself as it should be!
Dear Kamal, The Pyramid is very informative. The DIKW hierarchy suggests that one can affect the other and even can be changed into another.
Dear Kamal,
The pyramid you presented is nice. However, one can mention that data and information can be available for many people but only very few can attain the knowledge not to speak on the wisdom.
Dear @Mahmoud, the following article entitled: The data-information-knowledge-wisdom hierarchy and its antithesis by Jay Bernstein discusses this issue
discusses this issue and the author mentioned that data lead to information, which leads to knowledge, which in turnleads to wisdom which was first specified in detail by R. L. Ackoff in 1988. The Data-Information-Knowledge-Wisdom hierarchy is based on filtration, reduction, and transformation. Besides being causal and hierarchical, the scheme is pyramidal, in that data are plentiful while wisdom is almost nonexistent. The following link leads to the full article:
https://www.academia.edu/343239/The_data-information-knowledge-wisdom_hierarchy_and_its_antithesis
Dear Abedallah, Thank you for your answer. I downloaded the paper you mentioned and reading it now. Meanwhile, I copy and paste the abstract of Bernstein's paper to make your point more clear.
Abstract [1]: "The now taken-for-granted notion that data lead to information, which leads to knowledge, which in turn leads to wisdom was first specified in detail by Ackoff in 1988. The DIKW hierarchy is based on filtration, reduction, and transformation. Besides being causal and hierarchical, the scheme is pyramidal, in that data are plentiful while wisdom is almost nonexistent. Ackoff’s formula linking these terms together this way permits us to ask what the opposite of knowledge is and whether analogous principles of hierarchy, process, and pyramiding apply to it. The inversion of the DIKW hierarchy produces a series of opposing terms (including misinformation, error, ignorance, and stupidity) but not exactly a chain or a pyramid. Examining the connections between these phenomena contributes to our understanding of the contours and limits of knowledge."
[1] Bernstein, Jay H. (2009). The Data-Information-Knowledge-Wisdom Hierarchy and its Antithesis. Proceedings North American Symposium on Knowledge Organization Vol 2: PP. 68-75. [Available at: http://dlist.sir.arizona.edu/2633/].
Arranging from DATA to WISDOM along a scale
Russ Ackoff. 1989. From Data to Wisdom, J. App. Sys. Analys. 16:3-9.
Please, have a look in a fine paper, new one that treats this issue and application in military BIG data: “Big data are produced somewhere every day, and volumes of data are characteristic of modern combat operations. Soldiers must become experts with systems that manage, manipulate, transform, and analyze data. In the 21st century, tactically relevant information is produced, monitored, and shared in the digital space; commanders must learn to take advantage of data if they are to exercise mission command effectively."
Our RG colleague Terry Dwain Robertson did a fine paper, link attached! He says: "...However, when examined with any rigor, the distinctions become challenged and the hierarchy (DIKW) appears to fail...."! Good reading!
Article The Data/Information/Knowledge/Wisdom Hierarchy Goes to Seminary
Dear Ljubomir, Thank you for hits and links to the papers by Harry Tunnell (Network-centric warfare and the data-information-knowledge-wisdom hierarchy) and Terry Dwain Robertson (The Data/Information/Knowledge/Wisdom Hierarchy Goes to Seminary). Like always your answers are informative and professional.
This issue should be the main objective in the comming century! There is a lot of information but very few can convert it to knowledge.
I found the follwing definitions by searching Ackoff theory on the net. I am sharing it as I found the definition of these terms can help our understanding for providing answers to "who", "what", "where", "when" , "how" and why" questions. According to him, the content of the human mind can be classified into five categories:
Data: symbols
Information: data that are processed to be useful; provides answers to "who", "what", "where", and "when" questions
Knowledge: application of data and information; answers "how" questions
Understanding: appreciation of "why"
Wisdom: evaluated understanding.
Ackoff 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.
The following diagram represents the transitions from data, to information, to knowledge, and finally to wisdom, and it is understanding that support the transition from each stage to the next (Note: understanding is not a separate level of its own).
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?
T.S. Eliot, "The Rock", Faber & Faber 1934.
A good exposition can be seen in the attached paper links.
https://journals.lib.washington.edu/index.php/nasko/article/viewFile/12806/11288
http://www.dataschemata.com/uploads/7/4/8/7/7487334/dikwchain.pdf
Mahmoud a very interesting question. I am very happy to see contribution for all specially from Kamal and Raoof for teh graphical representation. However I will further retriate the point Andras highlighted. All the data is not information and all the information cannot be considered knowledge. The ability to generate information from the data is the most critical contribution and converting it into knowledge is a challange.
With respect to big data and data science the Knowledge / Information / Data is protected with Wisdom
Yes, it is dear Mahmoud and dear @Krishnan!
http://www.landaile.com/2012/10/15/sap-hana-va-t-il-tuer-sap-bw-1%C3%A8re-partie/
http://www.landaile.com/2012/10/19/sap-hana-va-t-il-tuer-sap-bw-2%C3%A8me-partie/
Data is not information, information is not knowledge, knowledge is not understanding, understanding is not wisdom. -Clifford Stoll
An example of DIKW hierarchy
The following quotation is from the Atlantic Canada Conservation Data Centre:
Individual bits or "bytes" of "raw" biological data (e.g. the number of individual plants of a given species at a given location) do not by themselves inform the human mind. However, drawing various data together within an appropriate context yields information that may be useful (e.g. the distribution and abundance of the plant species at various points in space and time). In turn, this information helps foster the quality of knowing (e.g. whether the plant species is increasing or decreasing in distribution and abundance over space and time). Knowledge and experience blend to become wisdom--the power of applying these attributes critically or practically to make decisions.
http://otec.uoregon.edu/data-wisdom.htm
“Information is not knowledge.
Knowledge is not wisdom.
Wisdom is not truth.
Truth is not beauty.
Beauty is not love.
Love is not music.
Music is THE BEST.” ― Frank Zappa
The Data, Information, Knowledge, Wisdom Chain: The Metaphorical link!
Use of the fluid metaphor for the ‘highest’ element of the chain, tacit knowledge, is
consistent with the physical evolution trends. In addition, with the advent of new technology for
sensing and transmitting both information and data, such as wireless networked sensors, rhetoric is evolving to describe these new systems in new ways. What would it be to speak of “an information field” or to “breathe in the knowledge around us?”....
Although our conceptions of data, information and knowledge have evolved since then it is clear he was able to put his finger on some very real relationships that continue to shape the way we think about the world."
http://inls151f14.web.unc.edu/files/2014/08/hey2004-DIKWchain.pdf
- Badges
- Science topic