A Level Computer Science OCR Practice Exam

Data stored in a knowledge base often requires inference to be utilized effectively. While the knowledge base itself may contain a wealth of well-structured and defined information, that information does not always present direct answers to questions or problems. Inference involves drawing conclusions based on the available data or rules within the knowledge base, which means users may need to process and interpret the information to extract valuable insights. This drawback highlights the importance of not just having data, but also the necessary mechanisms and understanding to derive actionable intelligence from it.

In contrasting scenarios, quick retrieval of information suggests efficiency, well-defined and structured data indicates clarity, and facilitating decision-making without human intervention points to automation. These aspects are typically viewed as advantages rather than drawbacks, emphasizing the notion that while knowledge bases can be powerful tools, the challenge lies in the need for inference to truly leverage the information contained within them.