Multi-Modal Scientific Data Integration Platform

Create a sophisticated data integration platform capable of harmonizing heterogeneous scientific datasets from multiple experimental modalities. Develop advanced data fusion techniques that can handle disparate data types, including time series, image data, spectroscopic measurements, and numerical simulations. Include machine learning approaches for semantic alignment, uncertainty propagation, and cross-modal feature extraction.