Progression of Data, from data to information to knowledge to insight to action:
The Data-Information-Knowledge-Wisdom (DIKW) hierarchy, or pyramid, relates data, information, knowledge, and wisdom as four layers in a pyramid. Data is the foundation of the pyramid, information is the next layer, then knowledge, and, finally, wisdom is the apex. DIKW is a model or construct that has been used widely within Information Science and Knowledge Management. Some theoreticians in library and information science have used DIKW to offer an account of logico-conceptual constructions of interest to them, particularly concepts relating to knowledge and epistemology. In a separate realm, managers of information in business process settings have seen the DIKW model as having a role in the task meeting real world practical challenges involving information.
Data is conceived of as symbols or signs, representing stimuli or signals. Information is defined as data that are endowed with meaning and purpose. Knowledge is a fluid mix of framed experience, values, contextual information, expert insight and grounded intuition that provides an environment and framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations it often becomes embedded not only in documents and repositories but also in organizational routines, processes, practices and norms. Wisdom is the ability to increase effectiveness. Wisdom adds value, which requires the mental function that we call judgment. The ethical and aesthetic values that this implies are inherent to the actor and are unique and personal.
Knowledge Pyramid, Wisdom Hierarchy and Information Hierarchy are some of the names referring to the popular representation of the relationships between data, information, knowledge and wisdom in the Data, Information, Knowledge, Wisdom (DIKW) Pyramid.
Like other hierarchy models, the Knowledge Pyramid has rigidly set building blocks – data comes first, information is next, then knowledge follows and finally wisdom is on the top.
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.
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.
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.
Data is conceived of as symbols or signs, representing stimuli or signals. Information is defined as data that are endowed with meaning and purpose. Knowledge is a fluid mix of framed experience, values, contextual information, expert insight and grounded intuition that provides an environment and framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations it often becomes embedded not only in documents and repositories but also in organizational routines, processes, practices and norms. Wisdom is the ability to increase effectiveness. Wisdom adds value, which requires the mental function that we call judgment. The ethical and aesthetic values that this implies are inherent to the actor and are unique and personal.
Knowledge Pyramid, Wisdom Hierarchy and Information Hierarchy are some of the names referring to the popular representation of the relationships between data, information, knowledge and wisdom in the Data, Information, Knowledge, Wisdom (DIKW) Pyramid.
Like other hierarchy models, the Knowledge Pyramid has rigidly set building blocks – data comes first, information is next, then knowledge follows and finally wisdom is on the top.
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.
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.
Data
- information, often in the form of facts or figures obtained from experiments or surveys, used as a basis for making calculations or drawing conclusions
- information, for example, numbers, text, images, and sounds, in a form that is suitable for storage in or processing by a computer
Information
- definite knowledge acquired or supplied about something or somebody
- the collected facts and data about a particular subject
- a telephone service that supplies telephone numbers to the public on request.
- the communication of facts and knowledge
- computer data that has been organized and presented in a systematic fashion to clarify the underlying meaning
- a formal accusation of a crime brought by a prosecutor, as opposed to an indictment brought by a grand jury
Knowledge
- general awareness or possession of information, facts, ideas, truths, or principles
- clear awareness or explicit information, for example, of a situation or fact
- all the information, facts, truths, and principles learned throughout time
- familiarity or understanding gained through experience or study
Wisdom
- the knowledge and experience needed to make sensible decisions and judgments, or the good sense shown by the decisions and judgments made
- accumulated knowledge of life or in a particular sphere of activity that has been gained through experience
- an opinion that almost everyone seems to share or express
- ancient teachings or sayings
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