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Summary
The NIST Open Access to Research (OAR) is a collaborative organizational effort established to support the NIST Plan for Providing Public Access to the Results of Federally Funded Research. In support of the NIST mission, OAR strives to achieve best practice and use of standards and metrology. The OAR research infrastructure is designed for dissemination of high value curated digital products to the NIST stakeholder community. The NIST Associate Director of Laboratory Programs (ADLP) Research Data and Computing Office (RDCO) provides expertise and oversight for the development and implementation.
Description
Major Capabilities:
Data Services and Tools: The OAR systems provide end-to-end workflow to deliver research outputs to the public. NIST Management of Institutional Data Assets (MIDAS) is a comprehensive application suite developed for orchestrating research data and code publication, data management planning, and organization of data files for publication. This is a free resource for NIST staff, supported by scalable services. A new version of the MIDAS system is currently under development to enhance scalability and ensure sustainability of the system, including a consolidation of digital asset publication code base with seamless integration with a file management solution. The redesign uses open-source technology, hosted on the USNISTGOV Github organization, and a streamlined containerized cloud deployment architecture.
Data Dissemination and Public Access: Users may search, explore and download datasets from the NIST Public Data Repository (PDR), accessible through a science portal interface, https://data.nist.gov. This resource includes a multidisciplinary catalog with direct access to NIST research data and code. It is designed and implemented using standards and best practice for research data. The PDR provides authorship and citation through use of ORCIDs and Datacite persistent Digital Object IDs (DOI)s. It also dynamically generates usage metrics for each record. An implementation of Natural Language Processing (NLP) based on a NIST developed Datasets are tagged using the NIST taxonomy and support aggregates of curated data for strategic areas such as Forensics and CHIPS Metrology Exchange to Innovate in Semiconductors data discovery.
Cloud-Based Collaborative Tools Utilization: NIST researchers may collaborate with internal and external partners using a wide range of cloud based tools. These are commonly used tools such as Google, Box, Microsoft Teams, and Github. Specialized data transfer tools, including Globus, are also utilized for supporting active collaboration through data transfer.
Data Management Infrastructure: The NIST research infrastructure extends across a network of multiple campus datacenters. These support on-prem capabilities such as data storage and computational resources, in addition to options for cloud hosting and deployment. High Performance Computing includes connectivity to the TACC computing facility. NIST research infrastructure adheres to cybersecurity FISMA requirements.