iDASH: integrating data for analysis, anonymization, and sharing

Lucila Ohno‐Machado(University of California San Diego), Vineet Bafna(University of California San Diego), Aziz A. Boxwala(University of California San Diego), Brian E. Chapman(University of California San Diego), Wendy W. Chapman(University of California San Diego), Kamalika Chaudhuri(University of California San Diego), Michele E. Day(San Diego Supercomputer Center), Claudiu Farcas(University of California San Diego), Nathaniel D. Heintzman(University of California San Diego), Xiaoqian Jiang(University of California San Diego), Hyeoneui Kim(University of California San Diego), Jihoon Kim(University of California San Diego), Michael E. Matheny(Vanderbilt University), Frederic S. Resnic(Brigham and Women's Hospital), Staal A. Vinterbo(University of California San Diego), and the iDASH team
Journal of the American Medical Informatics Association
November 11, 2011
Cited by 145Open Access
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Abstract

iDASH (integrating data for analysis, anonymization, and sharing) is the newest National Center for Biomedical Computing funded by the NIH. It focuses on algorithms and tools for sharing data in a privacy-preserving manner. Foundational privacy technology research performed within iDASH is coupled with innovative engineering for collaborative tool development and data-sharing capabilities in a private Health Insurance Portability and Accountability Act (HIPAA)-certified cloud. Driving Biological Projects, which span different biological levels (from molecules to individuals to populations) and focus on various health conditions, help guide research and development within this Center. Furthermore, training and dissemination efforts connect the Center with its stakeholders and educate data owners and data consumers on how to share and use clinical and biological data. Through these various mechanisms, iDASH implements its goal of providing biomedical and behavioral researchers with access to data, software, and a high-performance computing environment, thus enabling them to generate and test new hypotheses.


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