Democratizing genomic data science: exploring the impact of cloud-based platforms on data access and use

The National Human Genome Research Institute awarded the University of Washington $2.347 million under the Human Genome Research program (CFDA 93.172) on April 30, 2026, for a project examining how NIH cloud-based data sharing and analysis platforms democratize genomic data science and enhance uptake by diverse researchers and institutions.

The project investigates the actual uptake and use of genomic and linked health data held by NIH cloud platforms, with particular focus on researchers from underrepresented backgrounds and underserved institutions. The award will support work to describe and critically assess the current impact of NIH cloud-based data sharing and analysis platform availability on patterns of data access and use across the genomic research community, identify opportunities and challenges perceived by underrepresented researchers in accessing these resources, and develop recommendations to improve equity in genomic data science. The research team will work closely with an expert advisory group to advance the goal of broadening the range of researchers and institutions able to access large-scale genomic data through these platforms.

Performance takes place in Washington, with work continuing through March 31, 2030. The University of Washington's Office of Sponsored Programs (Grant & Contracts Division) administers the award as the recipient organization.

Abstract

Identifying and promoting biomedical research practices, including responsible data stewardship and analysis, that advance broad public health benefit and healthcare equity is a societal priority and central ethical concern for researchers and policymakers. For the genomic data science community, new NIH-supported cloud data sharing and analysis platforms promise to `democratize' data use, enabling a more diverse range of researchers to access large-scale genomic and linked health data and, IT is hoped, widen the range of research questions that can be answered using such data. While cloud-based data sharing theoretically promises to widen access to genomic and related biomedical data, because researchers need no longer rely on high- performance computing infrastructure at their local institution, the actual uptake and use of data held by these platforms remains uninvestigated. Nor do we currently understand what investigators from underserved backgrounds and/or underrepresented institutions (whom we refer to collectively here as "underrepresented") perceive as the most important opportunities for, and challenges to, accessing these new resources. Examining how cloud-based data sharing and analysis platforms enhance the uptake and use of genomic data by diverse researchers and institutions will help these new resources better achieve their promise to promote true data science equity. The overall goal of this project is, therefore, to examine the role that NIH cloud-based data sharing and analysis platforms play in promoting a more diverse range of users and research uses, thereby democratizing genomic data science. Specifically, we will work closely with an expert advisory group to address the following aims: aim 1. Describe and critically assess the current impact of NIH cloud-based data sharing and analysis platform availability on patterns of genomic data access and use; aim 2. Compare the perspectives of different categories of underrepresented data scientists on accessing and analyzing genomic and linked health data on cloud-based platforms; and aim 3. Convene expert advisors, platform developers, and other interested parties to discuss findings and propose potential approaches to promote more inclusive and equitable cloud-based genomic data access and use. The proposed in-depth, interdisciplinary, mixed methods investigation will generate novel data about the ways that NIH-supported cloud data sharing and analysis platforms are changing the genomic data sciences landscape and provide essential insights into overcoming challenges which may be interfering with the promise of these new data sharing mechanisms.