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NETWORKING AND INFORMATION TECHNOLOGY RESEARCH AND DEVELOPMENT (NITRD) PROGRAM ANNOUNCES UPDATE TO BIG DATA STRATEGIC PLAN

(November 12, 2024)
BIG DATA / PUBLICATIONS / STRATEGY DOCUMENTS

This document outlines a new vision and strategies to address the evolving big data research and development needs. It updates “The Federal Big Data Research and Development Strategic Plan” to address the notable developments and substantial changes in technologies and data management over the past several years. Additionally, this update considers the ethical and workforce implications of big data capabilities, and incorporates insights from federal agencies, findings from a community workshop, and input from the public. This update is essential to ensuring that the United States remains equipped to tackle the most pressing challenges and to empower the nation to make informed decisions that directly impact every sector.

87-FR-47473

Request for Information on the Federal Big Data Research and Development Strategic Plan Update

(August 3, 2022)
BIG DATA / FEDERAL REGISTER NOTICE / NEWS

The NITRD NCO and NSF, as part of the NITRD Big Data interagency working group (BD IWG), request input from all interested parties as the IWG prepares updates to the Federal Big Data Research and Development Strategic Plan. Through this RFI, the NITRD NCO seeks input from the public, including academia, government, business, and industry groups of all sizes; those directly performing Big Data research and development (R&D); and those directly affected by such R&D, on ways in which the strategic plan should be revised and improved. The public input provided in response to this RFI will assist the NITRD BD IWG in updating the Federal Big Data Research and Development Strategic Plan.

87-FR-39567

Request for Information on the Federal Big Data Research and Development Strategic Plan Update

(July 1, 2022)
BIG DATA / FEDERAL REGISTER NOTICE / NEWS

The NITRD NCO and NSF, as part of the NITRD Big Data interagency working group (BD IWG), request input from all interested parties as the IWG prepares updates to the Federal Big Data Research and Development Strategic Plan. Through this RFI, the NITRD NCO seeks input from the public, including academia, government, business, and industry groups of all sizes; those directly performing Big Data research and development (R&D); and those directly affected by such R&D, on ways in which the strategic plan should be revised and improved. The public input provided in response to this RFI will assist the NITRD BD IWG in updating the Federal Big Data Research and Development Strategic Plan.

Convergence-HPC-BD-ML-JointWSreport-2019-slide

THE CONVERGENCE OF HIGH PERFORMANCE COMPUTING, BIG DATA, AND MACHINE LEARNING

(September 9, 2019)
BIG DATA / HPC / PUBLICATIONS

The high performance computing (HPC) and big data (BD) communities are evolving in response to changing user needs and technological landscapes. Researchers are increasingly using machine learning (ML) not only for data analytics but also for modeling and simulation; science-based simulations are increasingly relying on embedded ML models not only to interpret results from massive data outputs but also to steer computations. Science-based models are being combined with data-driven models to represent complex systems and phenomena. There also is an increasing need for real-time data analytics, which requires large-scale computations to be performed closer to the data and data infrastructures, to adapt to HPC-like modes of operation. These new use cases create a vital need for HPC and BD systems to deal with simulations and data analytics in a more unified fashion.

Open-Knowledge-Network-Workshop-Report-2018-slide

Open Knowledge Network: Summary of the Big Data IWG Workshop

(November 20, 2018)
BIG DATA / PUBLICATIONS

Technology companies develop proprietary knowledge networks as key business technologies today. However, because these networks are proprietary and expensive to construct, government, academia, small businesses, and nonprofits do not have access to them. In contrast, an open knowledge network (OKN) would be available to all stakeholders, including the researchers who will help push this technology further. An OKN requires a nonproprietary, public–private development effort that spans the entire data science community and will result in an open, shared infrastructure.