RADx Data Hub: Enables 

Capabilities to Find, 

Access, Analyze, and 

Reuse COVID-19 RADx 

Study Data in a Cloudbased Platform

 

MARCH 2024
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Table of Contents

Executive Summary .................................................................................................2

Program Overview and Structure..........................................................................3

Program Accomplishments.....................................................................................4

Community Engagement.........................................................................................4

Impact and the Path Moving Forward ..................................................................5

Conclusion.................................................................................................................6
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Executive Summary

The RADx Data Hub was established to support researchers in accessing curated and deidentified COVID-19 data, allowing them to find, aggregate, and perform data analyses in a 

cloud-enabled platform. The centralized cloud resources offered by the Data Hub provide study

data and analytic capacities for researchers to better understand diagnostic COVID-19 testing 

tools, technologies, and future pandemics, especially for underserved populations and those who 

are disproportionately impacted by COVID-19. Additionally, these resources support rapid 

review of data requests from authorized users through the NIH RADx Data Access Committee to 

ensure proposed research purposes are consistent with participant protections and the data use 

agreement. Access to the Data Hub allows users to query a wide range of health data including 

clinical, behavioral, social determinants of health, survey, interview, diagnostic and testing 

results, viral sequences, output from smart sensors, self-reported symptoms, and imaging data.

The RADx Data Hub was built as a modernized, cloud-based data repository by curating 

collected data elements and creating anonymous COVID-19 research data optimized for cost, 

performance, and streamlined data access. This platform acts as a centralized data and metadata 

collection point across the four RADx programs that collect and submit the data (RADx-Digital 

Health Technologies, RADx-rad, RADx Tech, RADx-UP). Once the data is collected, it is 

systematically mapped, standardized, and curated across the various RADx studies to ensure 

consistent data collection and alignment to designated RADx Common Data Elements (CDEs). 

The RADx Data Hub was also designed to optimize engagement with the research community.

The Data Hub website allows users to explore the various data variables and study information 

for each registered RADx study. The RADx Data Hub support team also provides community 

outreach webinars that discuss the RADx data and the Data Hub functionality. 

To date, the RADx Data Hub contains 138 studies from across the four RADx programs that are 

available to researchers. Each study contains data that is harmonized to 12 RADx CDEs and up 

to 133 mapped variables that are study-dependent. The RADx programs continue to deposit data 
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into the Data Hub and approximately 60 additional studies are expected to be included once data 

collection and harmonization is complete.

As a portion of these studies include American Indian/Alaska Native (AI/AN) communities, the

RADx Data Hub team consulted with the Office of Data Science Strategy (ODSS), the National 

Institute of Minority Health and Health Disparities (NIMHD), and Tribal Leadership to hold a 

Tribal Consultation on July 30, 2021. The goal of this consultation was to address the unique 

cultural, governance, sovereignty needs, and expectations to support and share data collected 

from the AI/AN communities. This led to the establishment of the RADx Tribal Data Repository 

(RADx TDR) for responsible data sharing and access of RADx AI/AN research data. This 

repository is the first NIH research repository designed to implement sovereignty-based 

governance to promote tribal scientific values for researchers working with AI/AN data.

Program Overview and Structure

Each of the four RADx programs (RADx-Digital Health Technologies, RADx-rad, RADx Tech, 

RADx-UP) was established to address different aspects of the COVID-19 pandemic, resulting in 

a wide breadth of data types that needed to be consolidated within a centralized data depository. 

The RADx Data Hub was established to collate data from the various programs and to act as a 

cloud-based data repository of COVID-19 research data – including clinical, behavioral, social 

determinants of health, survey, interview, diagnostic and testing results, viral sequences, output 

from smart sensors, self-reported symptoms, and imaging data. The Data Hub provides access to 

anonymous RADx study research data, algorithms, and other analytic capabilities to expand 

testing and identify effective testing implementation strategies, especially for underserved 

populations and those disproportionately impacted by COVD-19.

As each RADx study has a unique scientific perspective and purpose, the data collected can vary 

widely across the individual studies. For the Data Hub to act as a centralized data depository, the 

data must undergo a standardized procedure to 1) ensure that all protected health information 

(PHI) is removed from the data sets and 2) harmonize the data so that it can be queried and 

analyzed across the studies. As study data is submitted to the RADx Data Hub, it first undergoes 
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validation that the 18 identifiers of PHI are removed to protect participant privacy in the research 

data. Once that is verified, the data is analyzed to identify, curate, standardize, and map the 

collected data elements and metadata to ensure user-friendly platform for scientific discovery. 

Within the RADx Data Hub platform, advanced technologies, such as AI and machine learning, 

are applied to ensure that the data/metadata can be findable, accessible, interoperable, and 

reusable across a multidisciplinary research community. This includes performing vertical and 

horizontal mapping variables across various scientific domain areas to enable a public browser 

searchable by variable, study, and file. Additionally, this data collation standardizes the metadata 

schema for data submission from the four RADx Collection and Data Coordination Centers 

(C)DCCs.

Program Accomplishments

Since launching in December 2022, the RADx Data Hub has provided a secure workspace to 

combine authorized data use and analytics tools, enabled researcher collaborations, ensured the 

ability to share analyses results, and created a framework for generating artificial intelligenceready datasets. The RADx Data Hub, as of November 27, 2023, contains 138 studies available to 

researchers. Additionally, the Data Hub includes 1,129 data files and 287 metadata files, 

including data dictionaries, README files, and schema. This accumulates to a total of 45,467

data variables across all studies, including the 12 RADx CDEs and 133 mapped study-specific 

variables. The Data Hub also contains 1,896 viral samples with genomic sequencing data and 

2,519 viral images for researchers to access.

Community Engagement

The RADx Data Hub was formed as a collaborative effort across the RADx programs and 

continues to actively engage with these scientific communities. Nationally, the RADx Data Hub 

has accepted studies from 46 US states and territories, with 24 states conducting research in two 

RADx programs, six states contributing to three RADx programs, and one state contributing to 

all four RADx programs. The RADx Data Hub community, as of November 27, 2023, consists 

of 421 individuals, 25 user-focus groups, and 575 subscribers. The RADx Data Hub leadership 
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team continues to hold regular, bi-weekly touchpoints with each of the four (C)DCCs, as well as 

quarterly, program-wide meetings. They have also hosted five webinars to engage the research 

community and have developed publicly available information for these researcher engagement 

activities (RADx Data Hub Events | RADx (nih.gov)). 

In addition to these engagement activities, the RADx Data Hub has aided in community outreach 

for the multiple funding opportunities for researchers interested in secondary analysis of data in 

the RADx Data Hub. These funding opportunities (NOT-OD-24-026, the renewal of NOT-OD23-040) aims to support advance scientific inquiry related to COVID-19 through the existing

data resources in the RADx Data. NIH also issued a Notice of Special Interest (NOT-OD-23-

041) to enhance the diversity of the data science workforce to address questions and scientific

inquires to COVID-19 through the existing data resources in the RADx Data Hub. Both research 

pathways would utilize the RADx Data Hub to answer relevant, public health-centric scientific 

inquiries. 

One of the RADx Data Hub’s most important community partnerships is the development of the 

RADx Tribal Data Repository (TDR) for sovereignty-based governance of AI/AN RADx data. 

This was done in a partnership with Tribal Leadership and represents the first NIH research 

repository designed to implement sovereignty-based governance to promote Tribal scientific 

values for researchers working with RADx AI/AN data. The RADx TDR addresses the unique 

cultural, governance, sovereignty needs, and expectations to support and share this data and will 

likely be used as a template for future collaborations. 

Impact and the Path Moving Forward 

Through the design, development, and deployment of the RADx Data Hub, the leadership team 

has identified various aspects of the process that could be improved for future, similar, program 

developments. Primarily, it is vital for the data to be as consistent as possible across the 

programs, so implementing CDEs as early as possible will mitigate data 

collection/harmonization complications. Furthermore, early adoption of a complete and 

consistent data dictionary is crucial to collecting data that can be applied across multiple 
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programs. The team found that the program-specific data dictionaries sometimes contained weak 

or missing descriptions for variables when these were merged into a common data dictionary. 

However, a data dictionary browser designed at the onset of data collection could be a significant 

improvement to the data collection and harmonization process. Program teams continue to 

optimize this process, both for uses in the current RADx Data Hub and for the development of 

future data repositories. 

For the process of CDE selection and maintenance, the RADx Data Hub team recommends that 

the CDEs cover a wide range of health data and should be automated, when possible. The 

collected data for the RADx Data Hub often required manual mapping and path review, both of 

which could benefit from automation. If algorithms were to be developed at the onset of data 

collection, it could simplify data collection and could broaden the evaluation of more variables. 

In the case that automation is unattainable, then researchers should consider the scalability and 

the amount of manual data harmonization/curation that will be required in the data collection 

process. If these considerations can be applied early in the process, it can improve the efficiency 

of data processing and can help improve any harmonization algorithms required. 

Lastly, early community outreach is critical to promoting a newly data-rich resources that will be 

adopted and used by researchers. By reaching these communities through webinars, community 

meetings, social media, etc., the RADx Data Hub Team can inform resources, stimulate scientific 

research interest and promote early adoption of the platform.

Conclusion 

The RADx Data Hub represents one of the largest collections of NIH COVID-19 testing data 

available to researchers that allows researchers to explore, access, and analyze COVID-related 

data developed through NIH RADx programs. The Data Hub will provide curated and 

harmonized data across ~ 200 RADx studies and all data/metadata will be findable, accessible, 

interoperable, and reusable. These data will be of interest to researchers focused on testing 

approaches, diagnostic and surveillance testing through wearable sensors and non-traditional 

approaches, and implementation strategies to enable an enhance testing of underserved, under-
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resourced, and/or vulnerable populations. Furthermore, the development of the RADx Tribal 

Data Repository has created a pathway for future collaboration with American Indian/Alaska 

Native communities. Through a close collaboration with the four RADx (C)DCCs, the RADx 

Data Hub capitalized on the speed and flexibility of these programs to streamline the processing 

of complicated data submissions and making those de-identified and harmonized data available 

to the larger research community.