necessitating continuous updates to the DIKWP model’s frameworks. 3. Ensuring Robustness and Reliability Consistency : Maintaining consistent and accurate transformations from data to wisdom across diverse datasets and scenarios. Error Handling : Designing mechanisms to handle errors or inconsistencies in the DIKWP layer without compromising the entire system’s integrity. 4. User Adoption and Understanding Educational Barrier : Users may require training to fully understand and utilize the DIKWP model’s transparency features. Usability : Ensuring that the explanations provided by DIKWP are accessible and comprehensible to non-expert users. Future Directions and Research Opportunities To maximize the potential of the DIKWP model and address existing challenges， encapsulating various levels of cognitive abstraction and complexity. Interconnected Components : Each component—Data， S.I. (2017). A Unified Approach to Interpreting Model Predictions. Summary : SHAP assigns each feature an importance value for a particular prediction using game theory.