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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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At least 19 records

Cloud Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) - Data Management - Data Products Catalog V4.94

The CALIPSO V2.00 Lidar Level 2 Polar Stratospheric Cloud data product is an updated version of an already order-able dat set. The changes were signed off by the CALIPSO Configuration Control Board, versioned, and the code uploaded to a code repository. There is no ITAR/SBU data or code associated with this product. Data will be publicly order-able at the NASA LaRC Atmospheric Sciences Data Center (ASDC). All documentation and web sites will be made public once the data product is released. The data is in HDF4 format and will be generated for majority of the mission (June 2006 - March 2021). The attached Data Products Catalog (v4.94) describes this new product in section 2.14, pp 115- 119.

Mark Vaughan↗

Project Management, Including Data Management Best Practices Framework (Best Management Practice; Work Product 12.3.b)

The Project Management documentation includes: (1) background on the RCSP Initiative and its best practices development process; (2) a historical perspective of best practices for project management; (3) a comparison of the roles of project managers, functional managers, and operations managers; (4) an overview of project management practices for field activities; and discussions of (5) managing change, (6) managing data, and (7) managing knowledge and information.

01 COAL, LIGNITE, AND PEAT↗

Editorial: Sorption processes in nuclear waste management: data knowledge management and new methodologies for data acquisition/prediction

A fundamental approach to Nuclear Waste Repository research involves the collection of experimental data in a laboratory setting, development of empirical and/or mechanistic numerical models representing those observations, and application of these models (or Reduced Order Models) into reactive transport and performance assessment models as predictive tools for informing society of impacts and risks associated with nuclear waste repository scenarios (Stevens et al., 2020). Therefore, the assimilation and interpretation of experimental data must take advantage of both new data and the rich historical data available in the literature and apply novel modeling approaches to improve predictive tools, particularly from the standpoint of uncertainty quantification, for nuclear waste repository performance assessment (Zavarin et al., 2022).

sorption↗

The ABC's required for establishing a practical computerized plant engineering management data base system

A system's approach is outlined in the paper to assist facility and Plant Engineers improve their organization's data management system. The six basic steps identified may appear somewhat simple; however, adequate planning, proper resources, and the involvement of management will determine the success of a computerized facility management data base. Helpful suggestions are noted throughout the paper to insure the development of a practical computerized data management system.

Maiocco, F. R.↗

Global‐view coefficients: a data management solution for parallel quantum Monte Carlo applications

Summary Quantum Monte Carlo (QMC) applications perform simulation with respect to an initial state of the quantum mechanical system, which is often captured by using a cubic B‐spline basis. This representation is stored as a read‐only table of coefficients and accesses to the table are generated at random as part of the Monte Carlo simulation. Current QMC applications, such as QWalk and QMCPACK, replicate this table at every process or node, which limits scalability because increasing the number of processors does not enable larger systems to be run. We present a partitioned global address space approach to transparently managing this data using Global Arrays in a manner that allows the memory of multiple nodes to be aggregated. We develop an automated data management system that significantly reduces communication overheads, enabling new capabilities for QMC codes. Experimental results with QWalk and QMCPACK demonstrate the effectiveness of the data management system. Copyright © 2016 John Wiley & Sons, Ltd.

Niu, Qingpeng↗

Flight design system-1 system design. Volume 5: Data management and data base documentation support system

Application software intended to reduce the man-hours required per flight design cycle by producing major flight design documents with little or no manual typing is described. The documentation support software is divided into two separately executable processors. However, since both processors support the same overall functions, and most of the software contained in one is also contained in the other, both are collectively presented.

Source record↗

Cloud - Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO) - Data Management System: Data Products Catalog V4.95

The CALIPSO V4.51 Lidar Level 1 and Level 2 data product is an updated version of an already order-able dataset. The changes were signed off by the CALIPSO Configuration Control Board, versioned, and the code uploaded to a code repository. There is no ITAR/SBU data or code associated with this product. Data will be publicly order-able at the NASA LaRC Atmospheric Sciences Data Center (ASDC). All documentation and web sites will be made public once the data product is released. The data is in HDF4 format and will be generated for majority of the mission (June 2006 - August 2023). The attached Data Products Catalog (v4.95) describes the content of these new data products.

Mark Vaughan↗

MaDaTS: Managing Data on Tiered Storage for Scientific Workflows

Scientific workflows are processing large amounts of data through complex simulation and analysis tasks. Meanwhile, the need to minimize I/O costs on next generation systems and the evolution of new technologies (NVRAMs, SSDs etc.) is resulting in deeper storage hierarchies on High Performance Computing (HPC) systems. A multi-tiered storage hierarchy introduces complexities in workflow and data management. There is need for simple and flexible data abstractions that can allow users to seamlessly manage workflow data and tasks on HPC systems with multiple storage tiers. MaDaTS (Managing Data on Tiered Storage for Scientific Workflows) provides an API and a command-line tool that allows users to manage their workflows and data on tiered storage (Ghoshal & Ramakrishnan (2017)).

97 MATHEMATICS AND COMPUTING↗

Satellite data management for effective data access

The management of data generated from satellite missions has not always led to effective access of that data by the scientific community. NASA has tried to alleviate this problem for ocean scientists, by initiating a program, the NASA Ocean Data System (NODS). The menu-based user interface that NODS employs allows a user to make request and receive answers within a short time of accessing the system. A catalog system, which holds information about oceanographic data sets may be queried to determine the suitability of a particular data set. Once a candidate data set is found, the user is directed to the person or place which actually holds the data. NODS also has an archive system that holds data from ocean-observing satellites. The archive may be queried to obtain a manageable data subset that can be delivered in a useful form.

Hogan, Patrick D.↗

PANSOPHY, a JLAB SRF engineering data management system, supporting data collection, retrieval and analysis utilized by LCLS-II

Pansophy is an Engineering Data Management System that provides a comprehensive solution for managing information in the production and testing of cryomodules. It is especially suited to supporting the Data & Quality Management Systems for large projects like LCLS-II. With extensive amounts of data collected for an individual project, data retrieval to facilitate feedback and enhancement of production and processing activities is a high priority. The priority shares importance with the needs of managing the project, including production status, NCR, and Quality Management reports. Recent Pansophy enhancements have been to Data and Quality management reports and statistical analysis. Such enhancements include a database driven menu system, extended MSWord macro and preprocessing of travelers, and an extensive reporting system. The reporting system allows managers and group leaders to quickly respond to the needs of the project in areas of cavity and cryomodule production, data collection, NCR, Quality Management and schedule. Extensions include integration with the SRF inventory system PRIMeS, allowing traceability from receiving of manufactured parts to final cryomodule product.

Bookwalter, Valerie D.↗

An Approach to Data Management Planning for Protected Data Projects

This report describes what is required in a data management plan for data that needs to be protected in some fashion. Here we provide an overview of what a data manager should consider, including the data ingestion and various extract-transform-load processes, metadata considerations and documentation, to what might need to be accounted for in the event of data loss. In addition, this report includes two appendices: forms that, when filled out, make the user compliant with DOE data management requirements as well as additional requirements for handling protected data at ORNL.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Intelligent data management

Intelligent data management is the concept of interfacing a user to a database management system with a value added service that will allow a full range of data management operations at a high level of abstraction using human written language. The development of such a system will be based on expert systems and related artificial intelligence technologies, and will allow the capturing of procedural and relational knowledge about data management operations and the support of a user with such knowledge in an on-line, interactive manner. Such a system will have the following capabilities: (1) the ability to construct a model of the users view of the database, based on the query syntax; (2) the ability to transform English queries and commands into database instructions and processes; (3) the ability to use heuristic knowledge to rapidly prune the data space in search processes; and (4) the ability to use an on-line explanation system to allow the user to understand what the system is doing and why it is doing it. Additional information is given in outline form.

Campbell, William J.↗

DataHub--Knowledge-Based Science Data Management for Exploratory Data Analysis

It is our belief that new modes of research and new tools will be required to handle the massive amount of diverse data that is to be stored, organized, accessed, distributed, visualized, and analyzed. The fundamental innovation required is the integration of three automation technologies, videlicet knowledge-based expert systems, science visualization and science data management. This integration is based on a concept caled the DataHub, which we describe here.

DataHub↗

Data management for interdisciplinary field experiments: OTTER project support

The ability of investigators of an interdisciplinary science project to properly manage the data that are collected during the experiment is critical to the effective conduct of science. When the project becomes large, possibly including several scenes of large-format remotely sensed imagery shared by many investigators requiring several services, the data management effort can involve extensive staff and computerized data inventories. The OTTER (Oregon Transect Ecosystem Research) project was supported by the PLDS (Pilot Land Data System) with several data management services, such as data inventory, certification, and publication. After a brief description of these services, experiences in providing them are compared with earlier data management efforts and some conclusions regarding data management in support of interdisciplinary science are discussed. In addition to providing these services, a major goal of this data management capability was to adopt characteristics of a pro-active attitude, such as flexibility and responsiveness, believed to be crucial for the effective conduct of active, interdisciplinary science. These are also itemized and compared with previous data management support activities. Identifying and improving these services and characteristics can lead to the design and implementation of optimal data management support capabilities, which can result in higher quality science and data products from future interdisciplinary field experiments.

Angelici, Gary↗

Data management for support of the Oregon Transect Ecosystem Research (OTTER) project

Management of data collected during projects that involve large numbers of scientists is an often overlooked aspect of the experimental plan. Ecosystem science projects like the Oregon Transect Ecosystem Research (OTTER) Project that involve many investigators from many institutions and that run for multiple years, collect and archive large amounts of data. These data range in size from a few kilobytes of information for such measurements as canopy chemistry and meteorological variables, to hundreds of megabytes of information for such items as views from multi-band spectrometers flown on aircraft and scenes from imaging radiometers aboard satellites. Organizing and storing data from the OTTER Project, certifying those data, correcting errors in data sets, validating the data, and distributing those data to other OTTER investigators is a major undertaking. Using the National Aeronautics and Space Administration's (NASA) Pilot Land Data System (PLDS), a Support mechanism was established for the OTTER Project which accomplished all of the above. At the onset of the interaction between PLDS and OTTER, it was not certain that PLDS could accomplish these tasks in a manner that would aid researchers in the OTTER Project. This paper documents the data types that were collected under the auspices of the OTTER Project and the procedures implemented to store, catalog, validate, and certify those data. The issues of the compliance of investigators with data-management requirements, data use and certification, and the ease of retrieving data are discussed. We advance the hypothesis that formal data management is necessary in ecological investigations involving multiple investigators using many data gathering instruments and experimental procedures. The issues and experience gained in this exercise give an indication of the needs for data management systems that must be addressed in the coming decades when other large data-gathering endeavors are undertaken by the ecological science community.

Skiles, J. W.↗