Monday, April1 | Noon to 1 p.m. | Ruffner Hall G006
Join Dr. Stan Ahalt, director of the Renaissance Computing Institute (RENCI) at the University of North Carolina at Chapel Hill, of recent work with the NIH Commons Fund Data Commons project that has yielded novel scientific results which would have been challenging to achieve without the Commons effort.
Dr. Ahalt will also describe the current NHLBI DataSTAGE initiative focused on leveraging the Commons effort to realize new scientific opportunities that take advantage of the flexibility supported by cloud computing, and he will describe aspects of the NCATS Data Translator project which hold promise for realizing the potential of multi-institutional resources.
The DataSTAGE (Storage, Toolspace, Access and analytics for biG data Empowerment) project aims to create a community of practice that is motivated to collaboratively solve technical challenges to enable NHLBI investigators to find, access, share, store, cross-link, and compute on large-scale data sets. Though the primary goal of the DataSTAGE Consortium is to build a data science platform, at its core this is a people-centric endeavor.
The NHLBI's DataSTAGE is working to develop innovative computing solutions that meet the needs of the NHLBI and its research community, building on the cloud-based infrastructure of the NIH Data Commons. NHLBI's DataSTAGE is a cloud-based platform for tools, applications, and workflows. DataSTAGE provides secure workspaces to share, store, cross-link, and compute large sets of data generated from biomedical and behavioral research.
Data STAGE is a critical part of implementing the Data Commons, a virtual shared space where scientists can access and work with the digital objects of biomedical research, such as data and software. Data from NHLBI's Trans-Omics for Precision Medicine (TOPMed) Program is one of three NIH-funded datasets included in the Data Commons. The TOPMed dataset is being used to test and develop the capabilities of the Data Commons. Data STAGE will enhance access to data from TOPMed-affiliated studies and other NHLBI datasets. Data STAGE will also provide access to tools that can be used to analyze various data types, including phenotypic, genomic, other omics, and imaging data.