RADx Data Hub: A Cloud Platform for FAIR, Harmonized COVID-19 Data. Martinez-Romero, M., Horridge, M., Mistry, N., Weyhmiller, A., Yu, J. K., Fujimoto, A., Henry, A., O'Connor, M. J., Sier, A., Suber, S., Akdogan, M. U., Cao, Y., Valliappan, S., Mieczkowska, J. O., team , t. R. D. H., Krishnamurthy, A., Keller, M. A., & Musen, M. A. February, 2025. arXiv:2502.00265 [cs]
RADx Data Hub: A Cloud Platform for FAIR, Harmonized COVID-19 Data [link]Paper  doi  abstract   bibtex   
The COVID-19 pandemic highlighted the urgent need for robust systems to enable rapid data collection, integration, and analysis for public health responses. Existing approaches often relied on disparate, non-interoperable systems, creating bottlenecks in comprehensive analyses and timely decision-making. To address these challenges, the U.S. National Institutes of Health (NIH) launched the Rapid Acceleration of Diagnostics (RADx) initiative in 2020, with the RADx Data Hub, a centralized repository for de-identified and curated COVID-19 data, as its cornerstone. The RADx Data Hub hosts diverse study data, including clinical data, testing results, smart sensor outputs, self-reported symptoms, and information on social determinants of health. Built on cloud infrastructure, the RADx Data Hub integrates metadata standards, interoperable formats, and ontology-based tools to adhere to the FAIR (Findable, Accessible, Interoperable, Reusable) principles for data sharing. Initially developed for COVID-19 research, its architecture and processes are adaptable to other scientific disciplines. This paper provides an overview of the data hosted by the RADx Data Hub and describes the platform's capabilities and architecture.
@misc{martinez-romero_radx_2025,
	title = {{RADx} {Data} {Hub}: {A} {Cloud} {Platform} for {FAIR}, {Harmonized} {COVID}-19 {Data}},
	shorttitle = {{RADx} {Data} {Hub}},
	url = {http://arxiv.org/abs/2502.00265},
	doi = {10.48550/arXiv.2502.00265},
	abstract = {The COVID-19 pandemic highlighted the urgent need for robust systems to enable rapid data collection, integration, and analysis for public health responses. Existing approaches often relied on disparate, non-interoperable systems, creating bottlenecks in comprehensive analyses and timely decision-making. To address these challenges, the U.S. National Institutes of Health (NIH) launched the Rapid Acceleration of Diagnostics (RADx) initiative in 2020, with the RADx Data Hub, a centralized repository for de-identified and curated COVID-19 data, as its cornerstone. The RADx Data Hub hosts diverse study data, including clinical data, testing results, smart sensor outputs, self-reported symptoms, and information on social determinants of health. Built on cloud infrastructure, the RADx Data Hub integrates metadata standards, interoperable formats, and ontology-based tools to adhere to the FAIR (Findable, Accessible, Interoperable, Reusable) principles for data sharing. Initially developed for COVID-19 research, its architecture and processes are adaptable to other scientific disciplines. This paper provides an overview of the data hosted by the RADx Data Hub and describes the platform's capabilities and architecture.},
	urldate = {2025-03-04},
	publisher = {arXiv},
	author = {Martinez-Romero, Marcos and Horridge, Matthew and Mistry, Nilesh and Weyhmiller, Aubrie and Yu, Jimmy K. and Fujimoto, Alissa and Henry, Aria and O'Connor, Martin J. and Sier, Ashley and Suber, Stephanie and Akdogan, Mete U. and Cao, Yan and Valliappan, Somu and Mieczkowska, Joanna O. and team, the RADx Data Hub and Krishnamurthy, Ashok and Keller, Michael A. and Musen, Mark A.},
	month = feb,
	year = {2025},
	note = {arXiv:2502.00265 [cs]},
	keywords = {Computer Science - Databases},
}

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