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With the significant expansion of civil aviation, particularly in the low-altitude economy, there is a significant gap between the escalating demand for airworthiness certification of novel aircraft designs, such as electric vertical take-off and landing (eVTOL) vehicles, and the inefficiency of the current safety assessment process. This gap is partially attributed to safety assessors' limited exposure to these innovative aircraft models in the safety assessment process, necessitating extensive efforts in identifying precedents and their handling strategies. Complicating matters further, pertinent case studies are scattered across diverse, unstandardized digital formats, obliging assessors to navigate voluminous electronic records while concurrently establishing links among fragmented information scattered across multiple files. This study introduces an advanced information integration methodology, comprising a multi-level path-based architecture and a self-updating algorithm. The proposed method not only furnishes safety assessors with pertinent knowledge featuring explicative interconnectedness automatically, but also dynamically enriches this knowledge corpus through operational usage. Additionally, we devise a suite of evaluative criteria to validate the capacity of our method in processing and consolidating relevant safety datasets. Experimental analyses affirm the efficacy of our proposed approach in streamlining and refreshing safety assessment data. The automation of the retrieval of analogous cases, which relieves the reliance on expert knowledge, enhances the efficiency of the overall safety appraisal procedure. Consequently, this research contributes a solution to enhancing the velocity and accuracy of aircraft certification processes. [ABSTRACT FROM AUTHOR]