1. Introduction Part I: Biomedical data formats and data integration 2. Data structures associated with biomedical research 3. Data mining and predictive analytics for cancer and COVID-19 4. Modular design, image biomarkers, and radiomics Part II: Type theory, graphs, and conceptual spaces 5. Types' internal structure and "non-constructive ("NC4) type theory 6. Using code models to instantiate data models Part III: Conceptual spaces and graph-oriented data-modeling paradigms 7. Multi-aspect modules and image annotation 8. Image annotation as a multi-aspect case study 9. Conceptual spaces and scientific data models