In working to achieve the long-term goal of the AnVIL of providing a unified platform for ingestion and organization for a multitude of current and future genomic and genome-related datasets, it is clear that enabling the cross-talk of multiple platforms and datasets is a critical barrier. To overcome this challenge, we propose to improve, adopt, and implement shared standards for DRS and RAS within the Terra platform. To do that, we propose the following aims and subaims: 1. Enhance cross-system interoperability through development and implementation of standards for authentication and for sharing data and applications 1.1 Interoperability standards and technical requirements: Improve interoperability standards, scope technical work needed to support these standards, and develop conventions across systems to facilitate the realization of these use cases 1.2 Terra DRS and RAS support: ? Ensure GA4GH DRS 1.1 support. Data should be accessible over the protocol supporting the systems described in the interoperability use cases. DRS 1.1 is the latest version of the GA4GH standard and includes GUID support ? Include RAS account linking and token management ? Ensure PFB search handoff support improvements as the convention is refined ? Ensure Leonardo accommodates DRS 1.1 and RAS support 1.3 Galaxy and R / Bioconductor DRS and RAS support: ? Ensure GA4GH DRS 1.1 support in Galaxy and R / Bioconductor, so data can be accessed using that standard ? Include RAS token sharing with Galaxy and RStudio instances in Terra, allowing Galaxy and R / Bioconductor to access DRS accessible data using RAS credentials 2. Complete the scoping required to integrate RAS support into the Data Use Oversight System (DUOS) 2.1 Complete scoping to add support to DUOS to enable data access committees to issue visas to researchers
Currently, analyzing data from various datasets, platforms, and ICs is intensely arduous because of time, cost, authentication, and technical expertise limitations. Through the implementation of standards that are focused on making authentication, data harmonization, and search functions interoperable within and external to the AnVIL ecosystem, the researcher burden to find, manage, and compute on large-scale data is greatly reduced. In enabling more timely and targeted analysis, the work in making platforms more interoperable stands to benefit researchers and patients.
