29

Mitchell Shiell1, Jon Eubank1, Justin Richardsson1, Brandon Chan1, Alexis Li1, Ann Catton1, Henrich Feher1, Leonardo Rivera1, Rakesh Mistry1, Samantha Rich1, Yelizar Alturmessov1, Azher Ali1, Patrick Dos Santos1, Edmund Su, Linda Xiang1, Robin Haw1, Lincoln Stein1,2 , Mélanie Courtot1,3

1. Ontario Institute of Cancer Research, Toronto, Canada 2. University of Toronto Department of Molecular Genetics 3. University of Toronto Department of Medical Biophysics, Toronto, Canada.

Overture is used to build platforms that enable researchers to organize and share their data quickly, flexibly and at multiple scales. While Overture successfully powers major international platforms like ICGC-ARGO (100,000+ participants) and VirusSeq (500,000+ genomes), smaller teams generating massive data face prohibitive technical requirements during implementation. How then can we enable teams to build their data platform efficiently and with fewer resources? Prelude addresses this challenge by automating various configuration and deployment processes and breaking platform development into incremental phases, reducing the technical overhead during development and allowing teams to systematically verify requirements through hands-on testing, gaining insights into workflows, data needs, and platform fit. Prelude guides teams through three progressive phases of data platform development each building upon the previous one's foundation: ● Phase one focuses on data exploration and theming, enabling teams to visualize and search their data through a customizable UI; ● Phase two expands capabilities to enable tabular data management and validation with persistent storage; ● Phase three adds file management and object storage. These phases are supported by comprehensive documentation, deployment automations, and utilities that generate key configuration files, reducing unnecessary time spent on tedious manual configurations. Prelude represents a practical step toward making data platform development accessible to all teams of all sizes. By providing a widely accessible platform we hope to encourage community requests and feedback such that we can improve and iterate on the platform making it the best it can be for advancing data sharing and reuse across the scientific community.