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FY2020 NITRD Program Component Areas (PCAs)

For general information about NITRD PCAs, see the NITRD PCA main page. The FY2020 PCAs described on this page are used in the NITRD Supplement to the President’s FY2020 Budget.

FY2020 Changes to the NITRD PCAs

  • Added the Artificial Intelligence (AI) PCA, including guidance on what R&D areas fall under the AI PCA versus other PCAs.*
  • Updated the CHuman PCA to remove overlap with the AI PCA and to focus on group/collaborative systems, tools, and studies rather than individuals.
  • Updated the SPSQ PCA to reflect the current state of software research.

FY2020 Supplement IWG-to-PCA Mapping

For each annual NITRD Supplement, Agencies “map” their NITRD Program activities coordinated by Interagency Working Groups (IWGs) into Supplement sections and budgets organized by PCAs. Predominant FY2020 mapping by agencies: Graphic | Text.

FY2020 NITRD PCA List

FY2020 NITRD PCA Definitions

AI – Artificial Intelligence *

AI R&D advances the ability of computer systems to perform tasks that have traditionally required human intelligence; this includes R&D in machine learning, computer vision, natural language processing/understanding, intelligent decision support systems, and autonomous systems, as well as the novel application of these techniques to various domains, where not principally covered by other PCAs.
↑ PCA List

CHuman – Computing-Enabled Human Interaction, Communication, and Augmentation

CHuman R&D advances information technologies that enhance people’s ability to interact with IT systems, other people, and the physical world; this includes R&D in social computing, human-human and human-machine interaction and collaboration, and human and social impacts of IT.
↑ PCA List

CNPS – Computing-Enabled Networked Physical Systems

CNPS R&D advances information technology-enabled systems that integrate the cyber/information, physical, and human worlds; this includes R&D of cyber-physical systems, Internet of Things, and related complex, high-reliability, networked, distributed computing systems.
↑ PCA List

CSP – Cyber Security and Privacy

CSP R&D advances protection of information and information systems from cyber threats and prevention of adverse privacy effects arising from information processing; this includes R&D to deter, detect, prevent, resist, respond to, recover from, and adapt to threats to the availability, integrity, and confidentiality of information and information systems, as well as R&D of privacy-protecting information systems and standards.
↑ PCA List

EdW – Education and Workforce

EdW R&D advances use of information technology to improve education and training; this includes IT to enhance learning, teaching, assessment, and standards, as well as preparation of next-generation cyber-capable citizens and professionals.
↑ PCA List

EHCS – Enabling R&D for High-Capability Computing Systems

EHCS R&D advances high-capability computing and development of fundamentally new approaches in high-capability computing; this includes R&D in hardware and hardware subsystems, software, architectures, system performance, computational algorithms, data analytics, development tools, and software methods for extreme data- and compute-intensive workloads.
↑ PCA List

HCIA – High-Capability Computing Infrastructure and Applications

HCIA investments advance operation and utilization of systems and infrastructure for high-capability computing, including computation- and data-intensive systems and applications; directly associated software, communications, storage, and data management infrastructure; and other resources supporting high-capability computing.
↑ PCA List

IRAS – Intelligent Robotics and Autonomous Systems

IRAS R&D advances intelligent robotic systems; this includes R&D in robotics hardware and software design and application, machine perception, cognition and adaptation, mobility and manipulation, human-robot interaction, distributed and networked robotics, and increasingly autonomous systems.
↑ PCA List

LSDMA – Large-Scale Data Management and Analysis

LSDMA R&D advances extraction of knowledge and insight from data; this includes R&D in the capture, curation, management, access, analysis, and presentation of large, diverse, often multisource, data.
↑ PCA List

LSN – Large-Scale Networking

LSN R&D advances networking technologies and services; this includes R&D in networking architectures, wireless networks, software-defined networks, heterogeneous multimedia networks, testbeds, grid and cloud research and infrastructure, network service and cloud computing middleware, identity management, and end-to-end performance enhancement and performance measurement.
↑ PCA List

SPSQ – Software Productivity, Sustainability, and Quality

SPSQ R&D advances timely and affordable development and sustainment of low-defect, low-vulnerability software; this includes R&D to significantly improve software production processes, productivity, quality, economics, sustainability, measurement, assurance, and adaptability, and to achieve guarantees of essential requirements such as security, privacy, usability, reliability, and autonomy.
↑ PCA List

 

* Please note that we understand R&D in AI will intersect with multiple PCAs. For example:

  • R&D on general methods for machine vision would fall under the AI PCA, while R&D on robots, even if the robots employ machine vision, would fall under IRAS. Note that R&D on intelligent autonomous systems that exist only in cyberspace, with no physical embodiment, would be reported under AI.
  • R&D that is primarily machine learning would fall under the AI PCA, while R&D on the larger data management and analysis ecosystem, even if it contains an element of machine learning, would fall under LSDMA.
  • R&D on algorithms for computational linguistics would fall under AI, while R&D on the broad problem of human-machine interaction, even if it contains an element of natural language processing, would fall under CHuman.
  • R&D on the cybersecurity challenges unique to AI, such as the ability to exploit flaws in an AI system’s goals would fall under AI, whereas AI supporting cybersecurity research would fall under CSP.
  • R&D on special neuromorphic computing architectures or chips optimized for neural nets would fall under AI, whereas general research in neuromorphic computing would fall under EHCS.

Agencies should consider these examples and report a given activity under the PCA that is primary or most specific to that activity.↩