Onboard Checkout and Data Management System /OCDMS/ computer selection criteria
Performance/design criteria for aid in selecting onboard checkout and data management system computers
Stomberg, D. H.↗
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Data Management Standards in Computer-aided Acquisition and Logistic Support (CALS)
Viewgraphs and discussion on data management standards in computer-aided acquisition and logistic support (CALS) are presented. CALS is intended to reduce cost, increase quality, and improve timeliness of weapon system acquisition and support by greatly improving the flow of technical information. The phase 2 standards, industrial environment, are discussed. The information resource dictionary system (IRDS) is described.
Jefferson, David K.↗
Data management at Biosphere 2 center
Throughout the history of Biosphere 2, the collecting and recording of biological data has been sporadic. Currently no active effort to administer and record regular biological surveys is being made. Also, there is no central location, such as an on-site data library, where all records from various studies have been archived. As a research institute, good, complete data records are at the core of all Biosphere 2's scientific endeavors. It is therefore imperative that an effective data management system be implemented within the management and research departments as soon as possible. Establishing this system would require three general phases: (1) Design/implement a new archiving/management program (including storage, cataloging and retrieval systems); (2) Organize and input baseline and intermediate data from existing archives; and (3) Maintain records by inputting new data.
McCreary, Leone F.↗
An integrated data management and informatics framework for continuous drug product manufacturing processes: A case study on two pilot plants
The pharmaceutical industry continuously looks for ways to improve its development and manufacturing efficiency. In recent years, such efforts have been driven by the transition from batch to continuous manufacturing and digitalization in process development. To facilitate this transition, integrated data management and informatics tools need to be developed and implemented within the framework of Industry 4.0 technology. Here, in this regard, the work aims to guide the data integration development of continuous pharmaceutical manufacturing processes under the Industry 4.0 framework, improving digital maturity and enabling the development of digital twins. This paper demonstrates two instances where a data integration framework has been successfully employed in academic continuous pharmaceutical manufacturing pilot plants. Details of the integration structure and information flows are comprehensively showcased. Approaches to mitigate concerns in incorporating complex data streams, including integrating multiple process analytical technology tools and legacy equipment, connecting cloud data and simulation models, and safeguarding cyber-physical security, are discussed. Critical challenges and opportunities for practical considerations are highlighted.
59 BASIC BIOLOGICAL SCIENCES↗
Support system for Onboard Checkout and Data Management System /OCDMS/, Saturn/Apollo application program
Specifications for computer program support system for onboard checkout and data management system
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Advanced data management system analysis techniques study
The state of the art of system analysis is reviewed, emphasizing data management. Analytic, hardware, and software techniques are described.
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Remote sensing data management from a user's viewpoint
The author has identified the following significant results. An experimental data bank in conjunction with the National Marine Fisheries Service's Fisheries Engineering Laboratory's (FEL) participation in the ERTS-1 program was established. The data management system was demonstrated to be effective in the performance of the NMFS-FEL ERTS-1 experiment involving several input sources and varying user requirements. The system is to be further evaluated under similar conditions during FEL participation in the Skylab and ERTS-B experiments.
Stevenson, W. H.↗
Data management system CIU and DIU. Appendix A: CIU and DIU schematics
The Computer Interface Unit (CIU) and the Data Interface Unit (DIU) of the Data Management System (DMS) were described as to their functional location, purpose and function. This describes the CIU and DIU at the unit level illustrating their interface thru the Data Bus (DBUS) and to other DMS units. All unit level interfaces are defined as to function and characteristics. The controls, indicators, test points and connectors are listed and function, location and application are described for each. The mechanical configuration is defined and illustrated to provide card and component location for modification or repair purposes. Unique disassembly and assembly requirements are outlined where applicable. A unit internal functional block diagram level description is provided.
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Development of a data management front-end for use with a LANDSAT-based information system
The development and implementation of a data management front-end system for use with a LANDSAT based information system that facilitates the processsing of both LANDSAT and ancillary data was examined. The final tasks, reported on here, involved; (1) the implementation of the VICAR image processing software system at Penn State and the development of a user-friendly front-end for this system; (2) the implementation of JPL-developed software based on VICAR, for mosaicking LANDSAT scenes; (3) the creation and storage of a mosiac of 1981 summer LANDSAT data for the entire state of Pennsylvania; (4) demonstrations of the defoliation assessment procedure for Perry and Centre Counties, and presentation of the results at the 1982 National Gypsy Moth Review Meeting, and (5) the training of Pennsylvania Bureau of Forestry personnel in the use of the defoliation analysis system.
Turner, B. J.↗
Data management for community research projects: A JGOFS case study
Since the mid 1980s, much of the marine science research effort in the United Kingdom has been focused into large scale collaborative projects involving public sector laboratories and university departments, termed Community Research Projects. Two of these, the Biogeochemical Ocean Flux Study (BOFS) and the North Sea Project incorporated large scale data collection to underpin multidisciplinary modeling efforts. The challenge of providing project data sets to support the science was met by a small team within the British Oceanographic Data Centre (BODC) operating as a topical data center. The role of the data center was to both work up the data from the ship's sensors and to combine these data with sample measurements into online databases. The working up of the data was achieved by a unique symbiosis between data center staff and project scientists. The project management, programming and data processing skills of the data center were combined with the oceanographic experience of the project communities to develop a system which has produced quality controlled, calibrated data sets from 49 research cruises in 3.5 years of operation. The data center resources required to achieve this were modest and far outweighed by the time liberated in the scientific community by the removal of the data processing burden. Two online project databases have been assembled containing a very high proportion of the data collected. As these are under the control of BODC their long term availability as part of the UK national data archive is assured. The success of the topical data center model for UK Community Research Project data management has been founded upon the strong working relationships forged between the data center and project scientists. These can only be established by frequent personal contact and hence the relatively small size of the UK has been a critical factor. However, projects covering a larger, even international scale could be successfully supported by a network of topical data centers managing online databases which are interconnected by object oriented distributed data management systems over wide area networks.
Lowry, Roy K.↗
A computer modeling methodology and tool for assessing design concepts for the Space Station Data Management System
A computer modeling tool is being developed to assess candidate designs for the Space Station Data Management System (DMS). The DMS is to be a complex distributed computer system including the processor, storage devices, local area networks, and software that will support all processing functions onboard the Space Station. The modeling tool will allow a candidate design for the DMS, or for other subsystems that use the DMS, to be evaluated in terms of parameters. The tool and its associated modeling methodology are intended for use by DMS and subsystem designers to perform tradeoff analyses between design concepts using varied architectures and technologies.
Jones, W. R.↗
Advances in building data management for building performance standards using the SEED platform
Reducing energy consumption and greenhouse gas emissions in the built environment is a critical step in achieving emission goals to mitigate climate change impacts. Local, federal, and international jurisdictions are deploying several methods to reduce energy and emissions such as voluntary and mandatory benchmarking and building performance standards, requiring building owners to reach energy and emission targets. Jurisdictions leveraging benchmarking and building performance standards require knowledge of the buildings covered; which is a large task due to staffing constraints, limited information on building characteristics and tax parcel data, and the need for advanced data management techniques to align datasets. This paper describes an open-source platform's recent advances to create consistent taxonomies, identify erroneous data, enable auditability, and track building performance. The paper concludes with two use cases on how the platform has been used by jurisdictions.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
IceVal DatAssistant: An Interactive, Automated Icing Data Management System
As with any scientific endeavor, the foundation of icing research at the NASA Glenn Research Center (GRC) is the data acquired during experimental testing. In the case of the GRC Icing Branch, an important part of this data consists of ice tracings taken following tests carried out in the GRC Icing Research Tunnel (IRT), as well as the associated operational and environmental conditions during those tests. Over the years, the large number of experimental runs completed has served to emphasize the need for a consistent strategy to manage the resulting data. To address this situation, the Icing Branch has recently elected to implement the IceVal DatAssistant automated data management system. With the release of this system, all publicly available IRT-generated experimental ice shapes with complete and verifiable conditions have now been compiled into one electronically-searchable database; and simulation software results for the equivalent conditions, generated using the latest version of the LEWICE ice shape prediction code, are likewise included and linked to the corresponding experimental runs. In addition to this comprehensive database, the IceVal system also includes a graphically-oriented database access utility, which provides reliable and easy access to all data contained in the database. In this paper, the issues surrounding historical icing data management practices are discussed, as well as the anticipated benefits to be achieved as a result of migrating to the new system. A detailed description of the software system features and database content is also provided; and, finally, known issues and plans for future work are presented.
Levinson, Laurie H.↗
Simons Foundation Data Management
The Simons Foundation is a non-profit organization that funds scientific research. Their Autism Research is generating significant amounts of genomic data, which they need to both archive and make available for researchers around the globe. The Foundation already stores data at Fermilab, as per agreement FRA-2015-0006. With this CRADA, the Fermilab Scientific Computing Division has developed a prototype solution for the data management needs of the Foundation, modifying services developed for High Energy Physics. The tools allow researchers to select datasets from a metadata catalogue of Foundation data, transfer selected files or datasets from Fermilab to remote storage, and enable the Foundation to manage access and authorization of the files. The prototypical solutions developed through this CRADA is considered the Phase I of a body of work that can be expanded and transitioned to production quality in a subsequent phase II, to be determined with the Foundation.
97 MATHEMATICS AND COMPUTING↗
Exacution: Enhancing Scientific Data Management for Exascale
As we continue toward exascale, scientific data volume is continuing to scale and becoming more burdensome to manage. In this paper, we lay out opportunities to enhance state of the art data management techniques. We emphasize well-principled data compression, and using it to achieve progressive refinement. This can both accelerate I/O and afford the user increased flexibility when she interacts with the data. The formulation naturally maps onto enabling partitioning of the progressively improving-quality representations of a data quantity into different media-type destinations, to keep the highest priority information as close as possible to the computation, and take advantage of deepening memory/storage hierarchies in ways not previously possible. Careful monitoring is requisite to our vision, not only to verify that compression has not eliminated salient features in the data, but also to better understand the performance of massively parallel scientific applications. Increased mathematical rigor would be ideal,to help bring compression on a better-understood theoretical footing, closer to the relevant scientific theory, more aware of constraints imposed by the science, and more tightly error-controlled. Throughout, we highlight pathfinding research we have begun exploring related these topics, and comment toward future work that will be needed.
97 MATHEMATICS AND COMPUTING↗
eFRMAC Overview: Data Management and Enabling Technologies for Characterization of a Radiological Release A Case Study: The Fukushima Nuclear Power Plant Incident
The eFRMAC enterprise is a suite of technologies and software developed by the United States Department of Energy, National Nuclear Security Administration’s Office of Emergency Response to coordinate the rapid data collection, management, and analysis required during a radiological emergency. This enables the Federal Radiological Monitoring and Assessment Center assets to evaluate a radiological or nuclear incident efficiently to facilitate protective actions to protect public health and the environment. This document identifies and describes eFRMAC methods including (1) data acquisition, (2) data management, (3) data analysis, (4) product creation, (5) quality control, and (6) dissemination.
nuclear accidents, environmental assessment, envir↗
DUNE Data Management: Network Visualization Monitoring Software
Fermilab’s fagship Deep Underground Neutrino Experiment (DUNE) seeks to better understand the nature of neutrinos within the context of Leptogenesis, neutrino oscillations, multi-messenger Astronomy, and other scientifc phenomena. The experiment will send a beam of neutrinos from the Fermilab site in Illinois to the Sanford Underground Neutrino Facility (SURF) in South Dakota, generating petabytes of scientifc data. Given the high volume of data expected when measurements begin at the end of the decade, DUNE computing and the data management group must carefully monitor data transfers across the 15 remote storage sites and, more generally, the 36 global DUNE computing sites. This report will describe both the frontend and backend data monitoring software designed to analyze and visualize these data transfers. Specifc emphasis will be placed on the software’s setup, usage, and methods for future implementations. The full software code can be found under the DUNE/data-mgmt-testing GitHub repository.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Program on Earth Observation Data Management Systems (EODMS)
An assessment was made of the needs of a group of potential users of satellite remotely sensed data (state, regional, and local agencies) involved in natural resources management in five states, and alternative data management systems to satisfy these needs are outlined. Tasks described include: (1) a comprehensive data needs analysis of state and local users; (2) the design of remote sensing-derivable information products that serve priority state and local data needs; (3) a cost and performance analysis of alternative processing centers for producing these products; (4) an assessment of the impacts of policy, regulation and government structure on implementing large-scale use of remote sensing technology in this community of users; and (5) the elaboration of alternative institutional arrangements for operational Earth Observation Data Management Systems (EODMS). It is concluded that an operational EODMS will be of most use to state, regional, and local agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.
Eastwood, L. F., Jr.↗