Cockpit data management
The supplement (Volume 2) to NASA CR-178407, Cockpit Data Management, presents the test data for the FAA study to ease data flow problems on air transport flight decks.
Groce, J. L.↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A Data Management System for a Space Base
Computerized data management system for space base
Ledet, J. P.↗
Contribution of the Spacelab data management system to lower cost space research
This paper reviews the design and operation of the Spacelab data management system as it has evolved. Significant improvements and extensions of the original baseline system have been incorporated and will be discussed. They include the capability for the remote control of Spacelab subsystems, improved remote data acquisition units, a high-rate digital data multiplexer, and an improved high-rate digital recorder. Emphasis will be placed on the overall system aspects, including considerations on the use of minicomputers as an adjunct to the basic Spacelab data system. The approach for experiment related software production and integration will be addressed as well. The paper focuses on the contributions of the data management system in reducing the cost of research in Spacelab.
Burger, J. J.↗
Nuclear Data Management and Analysis System Plan
The United States Department of Energy Advanced Reactor Technologies Program was formed in Fiscal Year 2015 and encompasses the Next Generation Nuclear Plant Project and Very High Temperature Reactor (VHTR) Program as they were known previously. The VHTR Program was created to support design and licensing of the first VHTR nuclear plant. Data created for and used by the program must be qualified for use, stored in a readily accessible electronic form, categorized to assure the correct data are used, and controlled to prevent data corruption or inadvertent changes. The Nuclear Data Management and Analysis System was designed to support the data needs of the VHTR Program, at the time and now the Advanced Reactor Technologies Program. Since its inception, use of the Nuclear Data Management and Analysis System has expanded to support additional projects and programs with similar requirements for control, analysis, and availability of large data sets.
99 GENERAL AND MISCELLANEOUS↗
DataHub - Science data management in support of interactive exploratory analysis
DataHub addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactive nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc.) in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis is on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept.
Handley, Thomas H., Jr.↗
DataHub: Science data management in support of interactive exploratory analysis
The DataHub addresses four areas of significant needs: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactives nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc), in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept.
Handley, Thomas H., Jr.↗
A parallel data management system for large-scale NASA datasets
The past decade has experienced a phenomenal growth in the amount of data and resultant information generated by NASA's operations and research projects. A key application is the reprocessing problem which has been identified to require data management capabilities beyond those available today (PRAT93). The Intelligent Information Fusion (IIF) system (ROEL91) is an ongoing NASA project which has similar requirements. Deriving our understanding of NASA's future data management needs based on the above, this paper describes an approach to using parallel computer systems (processor and I/O architectures) to develop an efficient parallel database management system to address the needs. Specifically, we propose to investigate issues in low-level record organizations and management, complex query processing, and query compilation and scheduling.
Srivastava, Jaideep↗
Evaluation of Technology Concepts for Traffic Data Management and Relevant Audio for Datalink in Commercial Airline Flight Decks
Datalink is currently operational for departure clearances and in oceanic environments and is currently being tested in high altitude domestic enroute airspace. Interaction with even simple datalink clearances may create more workload for flight crews than the voice system they replace if not carefully designed. Datalink may also introduce additional complexity for flight crews with hundreds of uplink messages now defined for use. Finally, flight crews may lose airspace awareness and operationally relevant information that they normally pickup from Air Traffic Control (ATC) voice communications with other aircraft (i.e., “party-line” transmissions). Once again, automation may be poised to increase workload on the flight deck for incremental benefit. Datalink implementation to support future air traffic management concepts needs to be carefully considered, understanding human communication norms and especially, the change from voice- to text-based communications modality and its effect on pilot workload and situation awareness. Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues. NASA is conducting research and development of increasingly autonomous systems, utilizing machine-learning algorithms seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. Increasingly autonomous systems offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. Two increasingly autonomous systems concepts - a traffic data manager and a conversational co-pilot - were developed to intelligently address the datalink issues in a complex, future state environment with significant levels of traffic. The system was tested for suitability of datalink usage for terminal airspace. The traffic data manager allowed for automated declutter of the Automatic Dependent Surveillance-Broadcast (ADS-B) display. The system determined relevant traffic for display based on machine learning algorithms trained by experienced human pilot behaviors. The conversational co-pilot provided relevant audio air traffic control messages based on context and proximity to ownship. Both systems made use of the connected aircraft concepts to provide intelligent context to determine relevancy above and beyond proximity to ownship. A human-in-the-loop test was conducted in NASA Langley Research Center’s Integration Flight Deck B-737-800 simulator to evaluate the traffic data manager and the conversational co-pilot. Twelve airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to the procedural events. This paper details the flight crew performance and evaluation during the events.
Etherington, Timothy↗
LSE-61: Rubin Observatory Data Management System (DMS) Requirements
This document contains the top-level requirements for the Data Management subsystem of the LSST, when combined with the Data Management-related requirements in the LSST System Requirements (LSR, LSE-29) and Observatory System Specifications (OSS, LSE-30).
79 ASTRONOMY AND ASTROPHYSICS↗
The Space Station Data Management System - Avionics that integrate
The Space Station Data Management System (DMS) comprises the networked computers, mass storage, workstations, and instrumentation interfaces required to support onboard systems and payload operations. This paper gives an overview of the current DMS architecture and discusses its role as onboard integrator in four of its major functional areas: (1) data communication; (2) data processing; (3) data administration, storage and retrieval; and (4) data presentation at the human-computer interface.
Whitelaw, Virginia↗
SDMS: A scientific data management system
SDMS is a data base management system developed specifically to support scientific programming applications. It consists of a data definition program to define the forms of data bases, and FORTRAN-compatible subroutine calls to create and access data within them. Each SDMS data base contains one or more data sets. A data set has the form of a relation. Each column of a data set is defined to be either a key or data element. Key elements must be scalar. Data elements may also be vectors or matrices. The data elements in each row of the relation form an element set. SDMS permits direct storage and retrieval of an element set by specifying the corresponding key element values. To support the scientific environment, SDMS allows the dynamic creation of data bases via subroutine calls. It also allows intermediate or scratch data to be stored in temporary data bases which vanish at job end.
Massena, W. A.↗
MERIT: A man/computer data management and enhancement system for upper air nowcasting/forecasting in the United States
It is suggested that the very short range forecast problem for aviation is one of data management rather than model development and the possibility of improving the aviation forecast using current technology is underlined. The MERIT concept of modeling technology, and advanced man/computer interactive data management and enhancement techniques to provide a tailored, accurate and timely forecast for aviation is outlined. The MERIT includes utilization of the Langrangian approach, extensive use of the automated aircraft report to complement the present data base and provide the most current observations; and the concept that a 2 to 12 hour forecast provided every 3 hr can meet the domestic needs of aviation instead of the present 18 and 24 hr forecast provided every 12 hr.
Steinberg, R.↗
Overview of the System of Experts for Intelligent Data Management (SEIDAM)
Viewgraphs on the system of experts for intelligent data management (SEIDAM) are presented. Topics covered include: multiple data sources integration; SEIDAM structure; machine learning; user interface; spatial knowledge expert system; digital terrain model (DTM) and segmentation expert systems; system validation; and tasks and plans.
Goodenough, David G.↗
Space Station data management system architecture
Within the Space Station program, the Data Management System (DMS) functions in a dual role. First, it provides the hardware resources and software services which support the data processing, data communications, and data storage functions of the onboard subsystems and payloads. Second, it functions as an integrating entity which provides a common operating environment and human-machine interface for the operation and control of the orbiting Space Station systems and payloads by both the crew and the ground operators. This paper discusses the evolution and derivation of the requirements and issues which have had significant effect on the design of the Space Station DMS, describes the DMS components and services which support system and payload operations, and presents the current architectural view of the system as it exists in October 1986; one-and-a-half years into the Space Station Phase B Definition and Preliminary Design Study.
Mallary, William E.↗
Pilot climate data system: A state-of-the-art capability in scientific data management
The Pilot Climate Data System (PCDS) was developed by the Information Management Branch of NASA's Goddard Space Flight Center to manage a large collection of climate-related data of interest to the research community. The PCDS now provides uniform data catalogs, inventories, access methods, graphical displays and statistical calculations for selected NASA and non-NASA data sets. Data manipulation capabilities were developed to permit researchers to easily combine or compare data. The current capabilities of the PCDS include many tools for the statistical survey of climate data. A climate researcher can examine any data set of interest via flexible utilities to create a variety of two- and three-dimensional displays, including vector plots, scatter diagrams, histograms, contour plots, surface diagrams and pseudo-color images. The graphics and statistics subsystems employ an intermediate data storage format which is data-set independent. Outside of the graphics system there exist other utilities to select, filter, list, compress, and calculate time-averages and variances for any data of interest. The PCDS now fully supports approximately twenty different data sets and is being used on a trial basis by several different in-house research grounds.
Smith, P. H.↗
NDMAS Data Management Capabilities for Metallic Fuels
This poster summarizes the capabilities of the Nuclear Data Management and Analysis System and its applicability to the Metallic Fuels program in the Advanced Fuel Campaign.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
FY 2025 Multidimensional Data Correlation Platform: Unified Software Architecture for Advanced Materials and Manufacturing Technologies Data Management and Processing
The Advanced Materials and Manufacturing Technologies (AMMT) program continues to advance a data-driven approach to demonstrate the utility of additive manufacturing for fabricating components for nuclear applications. A key scientific goal is to leverage data to better understand manufacturing outcomes and thereby improve the performance, reliability, and lifespan of nuclear components. Ultimately, this effort supports the development of standards for certification and qualification of additively manufactured components, enabling broader industry adoption. In support of this objective, the AMMT program is building and deploying a data management platform to record, index, analyze, and make available the manufacturing data generated across the AMMT program. In FY 2023, the team conceptualized the architecture of the platform and, in FY 2024, deployed the first functional version at the Oak Ridge National Laboratory (ORNL) Manufacturing Demonstration Facility (MDF). In FY 2025, the platform was officially opened to all AMMT members. To enable this expansion, core modifications and enhancements were developed, including improvements to the user interface and workflows for data entry and retrieval. Most notably, robust security and access control mechanisms were implemented to protect data and manage information sharing. This effort featured a logging system, protected views, and controlled access mechanisms. This report documents these enhancements and the transition of the platform into program-wide use.
36 MATERIALS SCIENCE↗
Data management at the National Space Science Data Center
Data processing and information transfer at National Space Science Data Center
Karlow, N.↗