What is the DIKW Pyramid?

Evergreen Note

Question :: 這篇文章主要在說什麼?

Answer :: DIKW 金字塔模型是知名的知識架構之ㄧ, 使我們了解到知識的轉化過程. 如諺語 "師父領進門, 修煉在個人", 當師傅講得再多; 給的資料再多, 如果自身沒有想要深入理解的話, 永遠都不會轉化成智慧. 這也有關於自身的態度.

Summary

DIKW 金字塔模型, 是知識管理的著名架構之一. DIKW 為金字塔的四個階段的字首, 分別為 Data、Information、Knowledge、Wisdom, 透過這幾個階段將從資料轉變成自身的智慧.

知識的形成之初都是由 Data 開始的, Data 尚未被賦予意義也未組織的資料源. 文章將到一個範例就是 12012012 是一組數字, 當被賦予了日期這個意義後, 就會變成 12月1號2012年. Data 通常為龐大且短暫的資訊, 如果沒特別感興趣或是去深入了解, 滿容易就忘記了.

當我們對資料做進一步的了解, 去理解資料如何使用的時候就會升為資訊的階段, 通常可以透過 'who', 'what', 'when', 'where' 這些問題來深入了解資料. 在這個階段, 只是知道怎麼使用資訊, 但如果談到 'how' 的時候, 嘗試去理解其原理, 就會再升為下一個階段 "知識".

當達到 "知識" 階段時, 會將這份知識跟其他的部分做連結, 進而深入理解這份知識. 例如談到 TCP 時, 為了理解其運作原理, 就會與 "封包的組成" 和 "OSI model" 做連結, 進而給予 TPC 更多的意義與價值. 當我們可以解釋知識, 並給出觀點與建議時, 就再升為下一個階段 "智慧".

"智慧" 為整個金字塔的最上層, 這階段我們應該要可以侃侃而談, 說明 "為什麼要這樣做" 或者 "給出更好的建議", 在這個階段也可以做出較精準的抉擇跟判斷.

這篇文章的自問 'who', 'what', 'when', 'where', 'how' 可以關聯到另一種分析法 [[5w1h]]. 透過自問的方式來做思考, 這方式也可以很好的收斂問題.

Note

原文 :: What is the Data, Information, Knowledge, Wisdom (DIKW) Pyramid?

The DIKW Pyramid represents the relationships between data, information, knowledge and wisdom. Each building block is a step towards a higher level - first comes data, then is information, next is knowledge and finally comes wisdom. Each step answers different questions about the initial data and adds value to it. The more we enrich our data with meaning and context, the more knowledge and insights we get out of it so we can take better, informed and data-based decisions.

Each step up the pyramid answers questions about the initial data and adds value to it. The more questions we answer, the higher we move up the pyramid. In other words, the more we enrich our data with meaning and context, the more knowledge and insights we get out of it. At the top of the pyramid, we have turned the knowledge and insights into a learning experience that guides our actions.

Data

Data is a collection of facts in a raw or unorganized form such as numbers or characters.

However, without context, data can mean little. For example, 12012012 is just a sequence of numbers without apparent importance. But if we view it in the context of ‘this is a date’, we can easily recognize 12th of January, 2012. By adding context and value to the numbers, they now have more meaning.

In this way, we have transformed the raw sequence of numbers into

Information

Information is the next building block of the DIKW Pyramid. This is data that has been “cleaned” of errors and further processed in a way that makes it easier to measure, visualize and analyze for a specific purpose.

Depending on this purpose, data processing can involve different operations such as combining different sets of data (aggregation), ensuring that the collected data is relevant and accurate (validation), etc. For example, we can organize our data in a way that exposes relationships between various seemingly disparate and disconnected data points. More specifically, we can analyze the Dow Jones index performance by creating a graph of data points for a particular period of time, based on the data at each day’s closing.

By asking relevant questions about ‘who’, ‘what’, ‘when’, ‘where’, etc., we can derive valuable information from the data and make it more useful for us.

But when we get to the question of  ‘how’, this is what makes the leap from information to

Knowledge

“How” is the information, derived from the collected data, relevant to our goals? “How” are the pieces of this information connected to other pieces to add more meaning and value? And, maybe most importantly, “how” can we apply the information to achieve our goal?

When we don’t just view information as a description of collected facts, but also understand how to apply it to achieve our goals, we turn it into knowledge. This knowledge is often the edge that enterprises have over their competitors. As we uncover relationships that are not explicitly stated as information, we get deeper insights that take us higher up the DIKW pyramid.

But only when we use the knowledge and insights gained from the information to take proactive decisions, we can say that we have reached the final – ‘wisdom’ – step of the Knowledge Pyramid.

Wisdom

Wisdom is the top of the DIKW hierarchy and to get there, we must answer questions such as ‘why do something’ and ‘what is best’. In other words, wisdom is knowledge applied in action.

We can also say that, if data and information are like a look back to the past, knowledge and wisdom are associated with what we do now and what we want to achieve in the future.