Modern life sciences generate data at a scale and complexity that fundamentally depend on scalable computing infrastructures and rigorous research data management. From assembling individual genomes, exploring complex microbial communities to building graph-based pangenomes, researchers today face both unprecedented opportunities and significant methodological challenges, not only in analysis, but also in how data and workflows are stored, shared, and sustained.