What are data, information, knowledge and wisdom?

What are data, information, knowledge and wisdom?

Author: Liu Feng

On June 5438+ 10 in 2006, I once wrote an article about data, information, knowledge and wisdom. I saw that Teacher Ni was also discussing this issue on the Science Network, so I sorted out some core contents of the original text and formed this article for discussion.

In knowledge management, there is a classic knowledge hierarchy diagram, and this paper will elaborate on the basis of this diagram.

First, what is data?

We often say that "the temperature of water is 100℃, the weight of the gift is 500g, the length of wood is 2m, and the height of the building is 100th floor". Through the key words of water, temperature, 100℃, gift, weight, 500g, wood, length, 2m, building, height and 100 floor, we have formed an impression of the objective world in our brains. These conventional characters or keywords form the data base of our discussion. The key words we mentioned must be regular. This means different classes and religions. People in different countries will inevitably have different agreements on keywords. From this, we can infer that the data actually has a range of use. People in different fields will present different data when describing the same thing. For example, people in China call the last day of the week "Sunday". Americans call this day "Sunday". Christians call this day "Sunday". The range of data leads to the establishment of information world and knowledge world in different countries. Different religions and different classes will have differences. Recognizing the scope of data can help us to unify the consistency of keywords or data when managing knowledge in a field.

Finally, our definition of data is that data is an abstract representation of the quantity, attribute, location and relationship of objective things with conventional keywords, which is suitable for manual or natural preservation, transmission and processing in this field.

Second, what is information?

As the middle layer in the knowledge hierarchy, one thing can be confirmed, that is, information must come from data and be higher than data. We know that data like 7 degrees, 50 meters, 300 tons, buildings and bridges are irrelevant and isolated. These data can only be called information if they are used to describe the relationship between an objective thing and an objective thing and form a logical data stream. In addition, information actually includes a very important feature-timeliness. For example, the news says that the temperature in Beijing is 9 degrees Celsius. This information means nothing to us. You must add the temperature of 9 degrees Celsius in Beijing today or tomorrow. Another example is the announcement that the meeting will be held on the third floor of the conference room. This information is also meaningless. He must tell us when the meeting will be held on the third floor of the conference room.

Paying attention to the timeliness of information is of great significance for us to use and transmit information. It reminds us that without the timeliness of information, information is incomplete and even becomes a meaningless data stream. Therefore, we believe that information is a timely, meaningful, logical, processed and valuable data stream for decision-making.

Third, what is knowledge?

Although information gives some meaningful things in the data, its value often begins to decline after the time utility fails. Only through people's participation can we summarize, deduce and compare the information, so that its valuable part can be precipitated and combined with the existing human knowledge system, and this valuable information can be transformed into knowledge. For example. Beijing in July 1, the temperature is 30 degrees. 1 February, the temperature is 3 degrees. Generally, this information will become worthless after the timeliness disappears, but when people summarize and compare this information, they will find that the temperature in Beijing will be relatively high in July and relatively low in June, which leads to the conclusion that there are four seasons in a year, so we think that knowledge is valuable information precipitated and structured by human existing knowledge base.

Fourth, what is wisdom?

We often see a person who knows everything, has a lot of knowledge, but is not worldly, and is called a bookworm. You will also see that some people have only read a few books, but their abilities are superior and they can solve difficult problems. We will think that the latter is more intelligent. Therefore, we believe that wisdom is the ability of human beings to analyze, compare and derive solutions to problems arising from the movement of the material world based on existing knowledge. The result of this ability is to dig out the valuable part of information and make it a part of the existing knowledge structure.

According to these definitions, we try to put forward some constructive suggestions for knowledge management:

1。 Pay attention to the unity and integrity of keywords used in data, avoid different information and knowledge systems in the organization, and avoid ambiguity and misunderstanding among members in communication.

2。 Keep the expansibility of keyword set, and prevent new information and knowledge from being generated due to incomplete data.

3。 Pay attention to the timeliness of information, try to dig out its useful value before its timeliness disappears, and let it precipitate in the existing knowledge base.

4。 Pay attention to the reliability and logic of information to prevent information from being added to the knowledge base due to errors or logical confusion, thus reducing the quality of the knowledge base.

5。 Pay attention to the structure of knowledge base, and try to avoid knowledge separation or even knowledge islands. Through the cross-fusion of knowledge in different fields, it is convenient for organization members to locate the required knowledge quickly and accurately when using the knowledge base.

6。 Fully understanding wisdom is an ability to apply knowledge and deal with information problems. When selecting members of an organization, we should consider the balance between their knowledge and their ability to use knowledge.