For more than 30 years, knowledge management has been organized around a hierarchy. According to the data-information-knowledge-wisdom (DIKW) model traced to Russell Ackoff in 1989, data comprises symbols representing the facts. Data becomes useful information as it answers questions. Information becomes knowledge as it is organized into generalizations and can be used to explain answers. Wisdom arises when humans evaluate answers, especially with ethics and aesthetics. In the hierarchy from data to wisdom, there is also a continuum from neutral to non-neutral.
The temperature outside is an example of neutral data that can be created, stored, and transported via networked computers. With no context, that data has little meaning and it can be reported with precision that can be objectively evaluated. Temperature becomes information as it is placed into context. For example, we may judge 65° F to be a warm day or a cool day depending on the season and one’s location. That information can become knowledge of climatic tendencies. A human can evaluate that temperature to make judgments about climate change as she creates and demonstrates wisdom. A computer may be capable of storing data indefinitely and manipulating it to provide answers to our questions, but only a human can decide if the information should be stored or what actions are ethical given the answer.