CCSDS reorganization and status report
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The KidSat Data System provided near real-time access to digital images taken from the Space Shuttle. How these various data sets were assembled and how effectively design and operational goals were met is discussed in detail.
The integration of payload instruments into the Command and Data Management Subsystem (CDMS) of the Space Shuttle Spacelab is discussed. Specific emphasis is on the distributed (self-contained processor) vs centralized (Spacelab Computer) approach to science payload utilization of these control and data handling capabilities. An overview of the Spacelab CDMS is first given. A synopsis of the integration process for Spacelab Missions 1, 2, and 3 is discussed. Three different hardware approaches to payload command and data handling are then categorized from which Spacelab implementations to date are derived. The different types of Spacelab Mission 3 payload CDMS hardware and software being used are discussed, including examples of microprocessors and data acquisition systems. Preliminary costs for Spacelab application software vs other flight software approaches are compared. A standard RAU interface that would permit a range of ECOS services to be provided, yet be implemented as a mass-produceable unit for incorporation into payloads, is proposed, in keeping with the trend toward simplifying the integration effort, standardizing CDMS interfaces, and ultimately lowering cost.
NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASAs premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.
NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASA's premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.
Lightweight deep space probe design for spin stabilization
MULTIPAC, multiple pool processor and computer for deep space probe central data system
The Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) has been operational since October 1, 1993. Its mission is to support the Earth Observing System (EOS) by providing rapid access to EOS data and analysis products, and to test Earth Observing System Data and Information System (EOSDIS) design concepts. One of the challenges is to ensure quick and easy retrieval of any data archived within the DAAC's Data Archive and Distributed System (DADS). Over the 15-year life of EOS project, an estimated several Petabytes (10(exp 15)) of data will be permanently stored. Accessing that amount of information is a formidable task that will require innovative approaches. As a precursor of the full EOS system, the GSFC DAAC with a few Terabits of storage, has implemented a prototype of a constraint-based task and resource scheduler to improve the performance of the DADS. This Honeywell Task and Resource Scheduler (HTRS), developed by Honeywell Technology Center in cooperation the Information Science and Technology Branch/935, the Code X Operations Technology Program, and the GSFC DAAC, makes better use of limited resources, prevents backlog of data, provides information about resources bottlenecks and performance characteristics. The prototype which is developed concurrently with the GSFC Version 0 (V0) DADS, models DADS activities such as ingestion and distribution with priority, precedence, resource requirements (disk and network bandwidth) and temporal constraints. HTRS supports schedule updates, insertions, and retrieval of task information via an Application Program Interface (API). The prototype has demonstrated with a few examples, the substantial advantages of using HTRS over scheduling algorithms such as a First In First Out (FIFO) queue. The kernel scheduling engine for HTRS, called Kronos, has been successfully applied to several other domains such as space shuttle mission scheduling, demand flow manufacturing, and avionics communications scheduling.
Ninety day manned test of regenerative life support system in space station simulator, presenting operational and maintenance data
The National Aeronautics and Space Administration (NASA) Ocean Data System (NODS) archive at the Jet Propulsion Laboratory (JPL) includes satellite data sets for the ocean sciences and global-change research to facilitate multidisciplinary use of satellite ocean data. Parameters include sea-surface height, surface-wind vector, sea-surface temperature, atmospheric liquid water, and surface pigment concentration. NODS will become the Data Archive and Distribution Service of the JPL Distributed Active Archive Center for the Earth Observing System Data and Information System (EOSDIS) and will be the United States distribution site for Ocean Topography Experiment (TOPEX)/POSEIDON data and metadata.
Turnkey Commercial Off The Shelf (COTS) data acquisition systems typically perform well and meet most of the objectives of the manufacturer. The problem is that they seldom meet most of the objectives of the end user. The analysis software, if any, is unlikely to be tailored to the end users specific application; and there is seldom the chance of incorporating preferred algorithms to solve unique problems. Purchasing a customized system allows the end user to get a system tailored to the actual application, but the cost can be prohibitive. Once the system has been accepted, future changes come with a cost and response time that's often not workable. When it came time to replace the primary digital data acquisition system used in the Goddard Space Flight Center's Structural Dynamics Test Section, the decision was made to use a combination of COTS hardware and in-house developed software. The COTS hardware used is the DataMAX II Instrumentation Recorder built by R.C. Electronics Inc. and a desktop Pentium 4 computer system. The in-house software was developed using MATLAF3 from The Mathworks. This paper will describe the design and development of the new data acquisition and analysis system.
Turnkey Commercial Off The Shelf (COTS) data acquisition systems typically perform well and meet most of the objectives of the manufacturer. The problem is that they seldom meet most of the objectives of the end user. The analysis software, if any, is unlikely to be tailored to the end users specific application; and there is seldom the chance of incorporating preferred algorithms to solve unique problems. Purchasing a customized system allows the end user to get a system tailored to the actual application, but the cost can be prohibitive. Once the system has been accepted, future changes come with a cost and response time that's often not workable. When it came time to replace the primary digital data acquisition system used in the Goddard Space Flight Center's Structural Dynamics Test Section, the decision was made to use a combination of COTS hardware and in-house developed software. The COTS hardware used is the DataMAX II Instrumentation Recorder built by R.C. Electronics Inc. and a desktop Pentium 4 computer system. The in-house software was developed using MATLAB from The MathWorks. This paper will describe the design and development of the new data acquisition and analysis system.
Spacecraft central data system for deep space solar probe data management
Multiprocessor computer systems and implementation in space station data management system
Marshall Space Flight Center computer and data processing system workload analysis
Hardware and software products and technologies that are available for implementation in the early space station data management system (DMS) design are expected to have limited capabilities in such areas as system performance, capacity, and throughput. With the anticipated growth in operations and payload user requirements during the space station's operational phase, a knowledge base of technological advancements and their possible incorporation into the DMS design will be maintained. System growth and technologies insertion issues for DMS design and development are addressed.
Deep space solar probe central data system design concepts for high data sampling rates, data processing, data storage and efficient transmission format