Crosscutting NIEHS strategic priorities, the Office of Scientific Computing promotes the Environmental Health Sciences by integrating novel research with support for Laboratory and Clinical Information Technology (IT), Scientific Software, Hardware, Scientific Data, and Scientific High-performance Computing (HPC). This is accomplished through partnerships with the NIEHS scientific community, contractors, and external collaborative groups.
David C. Fargo, Ph.D.
Director of Environmental Science Cyberinfrastructure
P.O. Box 12233Mail Drop B3-01Durham, N.C. 27709
The Office of Scientific Computing maintains an individual research program prioritizing development of novel tools and methods to empower knowledge-based enrichment and discovery. Fostering collaborative research efforts, this work addresses unmet or emerging analytical needs. Projects involve the application of deep learning and metadata systems to big data challenges in genomics, epigenomics, and other big data domains.
Laboratory – IT
Biomedical and Environmental Health Science research is increasingly dependent on IT infrastructure and expertise. NIEHS scientists have diverse and growing scientific IT needs, including support for general Laboratory/Clinical IT. These needs include scientific domain-specific support, project-based or ad hoc support, operational and strategic infrastructure modernization supporting increasing data volume and complexity, and systems supporting scientific data and knowledge management.
Scientific software support includes commercial, open source, and internally developed resources enabling data analytics, data visualization, information management, systems support, and other essential scientific functions across the NIEHS Intramural Research Division, the National Toxicology Program, and the Extramural Research and Training Division. Support includes software distribution, version control including support for legacy versions, and applied training.
Scientific hardware support includes computers or other hardware with non-standard systems software; directly attached to or supporting scientific instruments or equipment; supporting legacy or other non-standard scientific software and databases; locally administered and maintained servers or workstations, frequently running Linux, supporting analytics or hosting scientific applications including databases, webservers, and other functions, and others.
FAIR+ management of scientific data requires assurance of data integrity and security; understanding of data provenance, reliability and reusability; metadata management empowering complex query, filtering and retrieval, and data governance including lifecycle management.
Scientific High-performance Computing (HPC)
NIEHS scientists are increasingly empowered to use high-throughput, data-intensive technologies to advance their research programs. Scientific areas of inquiry generating large and complex data include genomics and epigenomics, computational chemistry, molecular modeling and simulations, structural biology, biomedical imaging, proteomics, metabolomics, systems biology and others.
NIEHS scientific HPC designs provide core capabilities that enable the use of custom solutions and can be adapted to fit changing priorities and requirements. Designs balance ongoing needs, support for continuous incremental changes, and punctuated disruptive technological changes.