Concepts related to “wisdom” in relation to “knowledge” are rooted in a hierarchical model often referred to as the “DIKW Pyramid,” which stands for:
- Data: Raw, unorganized facts that need to be processed. For example, individual measurements or observations.
- Information: Data that has been processed to be meaningful. It answers questions like “Who?”, “What?”, “Where?”, and “When?”
- Knowledge: Information that has been organized and processed to be understood. It answers questions like “How?”
- Wisdom: The ability to make sound judgments and decisions based on knowledge. It addresses “Why?” and represents a higher level of insight or understanding.
If someone were to use the term “Wisdom Graph,” it might imply a system that not only understands entities and their relationships (as a Knowledge Graph does) but also provides deeper insights, judgments, or decision-making capabilities based on that knowledge. It would be a step beyond merely presenting facts or connections and might offer more profound analytical insights or recommendations.
In practical applications, implementing a “Wisdom Graph” would require advanced AI and machine learning techniques to ensure the system can provide accurate and insightful judgments based on the available data.