Multidataset
Multidataset is a term used in data science to describe the use of two or more datasets in a combined analysis. The goal is to leverage information from diverse sources to improve statistical power, generalizability, and robustness, while accounting for differences in study design, measurement, and population.
Multidataset work encompasses more than simply stacking data. It may involve formal data integration, joint modeling,
Common approaches include data harmonization to align variables, normalization to reduce technical variation, and batch effect
Applications span genomics and epidemiology, social sciences, ecology, and computer vision, especially when multiple cohorts, sites,
Key challenges include heterogeneity of data collection and quality, missing features, label inconsistency, privacy and licensing
Related concepts include meta-analysis, data integration, data fusion, transfer learning, and multi-task learning.