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A Scenario-Driven Dynamic Assessment Model for Data Credibility
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DOI：10.1016/j.cose.2025.104805.png)
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Abstract
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With the rapid development of information technology, data has become the core element driving decision-making, and the explosive growth of massive data makes data governance face new challenges. The diversity of data sources and the dynamic complexity of application scenarios lead to uneven data quality, so there is an urgent practical need to construct accurate and efficient data credibility assessment methods. Existing researches are mostly limited to a single domain, which leads to fragmentation of assessment standards and makes it difficult to adapt to the needs of multiple scenarios. To address the above problems, this study proposes a dynamic data credibility assessment paradigm with universal applicability. Specifically, firstly, we construct a four-layer data credibility assessment index system based on national standards and domain guidelines through UML modeling technology, which realizes quantifiable disassembly from the target layer to the index layer and ensures cross-scenario compatibility and scalability of the assessment framework. Second, a scenario-driven dynamic fuzzy assessment model is proposed, which consists of a scene adaptation layer, an index optimization layer, a weight dynamic allocation layer and a comprehensive assessment layer. The key assessment indexes are screened by the scene feature analysis and the improved analytical hierarchy process, and the combination of the subjective and objective weights and the modification model are combined to achieve a dynamic balance of the weights, and a fuzzy comprehensive evaluation model is introduced to deal with uncertainties in the assessment process, and finally get the comprehensive assessment grade of data credibility. Finally, this study applies the framework to a vehicle forensics scenario for case analysis and evaluates the method’s accuracy using both simulated and real-world data. The results demonstrate its effectiveness in complex scenarios.
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