The Consequences of Data Silos on Data Quality in Biomedical Research In biomedical research, data silos are isolated repositories of information accessible only to specific departments, teams, or organizations. These silos emerge as a natural consequence of the diverse sources and proprietary systems that generate data in the field. Clinical data, genomic sequences, proteomic datasets, and imaging files are often stored separately, each following its own standards, formats, and storage mechanisms. While this setup might suit individual teams, the lack of interconnectedness leads to fragmented data ecosystems that are difficult to integrate and analyze holistically. Source: https://www.elucidata.io/blog/the-consequences-of-data-silos-on-data-quality-in-biomedical-research