This research addresses a critical gap in olfactory analysis: the absence of unified categorization systems that limit cross-disciplinary progress. The project presents a speculative science methodology that bridges personal olfactory experiences with quantitative chemical data through artificial intelligence integration.

The study develops a hybrid analytical framework capable of capturing both the scientific properties of molecular compounds and the emotional, cultural, and sensory responses they evoke in humans. By processing qualitative scent narratives alongside objective chemical databases, the system generates multidimensional analyses visualized through interactive coordinates that reveal previously hidden relationships.

The methodology transforms heterogeneous data into coherent analytical frameworks, connecting subjective perceptual experiences with measurable scientific properties. This approach enables novel cross-disciplinary investigations that span from healthcare diagnostics to cultural heritage studies.

While demonstrated through olfactory analysis, this framework offers broader applications for any research domain requiring the integration of subjective human experiences with objective scientific measurements, providing new pathways for understanding complex phenomena that resist traditional analytical approaches.