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The Software Engineering Laboratory was monitoring software development at NASA Goddard Space Flight Center since 1976. The data collection activities of the Laboratory and some of the difficulties of obtaining reliable data are described. In addition, the application of this data collection process to a current prototyping experiment is reviewed.
A primary goal of the NASA Tropospheric Chemistry Program (TCP) is to "contribute substantially to scientific understanding of human impacts on the global troposphere". In order to analyze global or regional trends and factors of the troposphere chemistry, for example, its oxidation capacity or composition, a continuous global/regional data coverage as well as model simulations are needed. The Global Tropospheric Experiment (GTE), a major component of the TCP, provides data vital to these questions via aircraft measurement of key trace chemical species in various remote regions of the world. Another component in NASA's effort are satellite projects for exploration of tropospheric chemistry and dynamics. A unique data product is the Tropospheric Ozone Residual (TOR) utilizing global tropospheric ozone data. Another key research tool are simulation studies of atmospheric chemistry and dynamics for the theoretical understanding of the atmosphere, the extrapolation of observed trends, and for sensitivity studies assessing a changing anthropogenic impact to air chemistry and climate. In the context with model simulations, field data derived from satellites or (airborne) field missions are needed for two purposes: 1. To initialize and validate model simulations, and 2., to interpret field data by comparison to model simulation results in order to analyze global or regional trends and deviations from standard tropospheric chemistry and transport conditions as defined by the simulations. Currently, there is neither a sufficient global data coverage available nor are existing well established global circulation models. The NASA LARC CTM model is currently not yet in a state to accomplish a sufficient tropospheric chemistry simulation, so that the current research under this cooperative agreement focuses on utilizing field data products for direct interpretation. They will be also available for model testing and a later interpretation with a finally utilized model.
An Information Architecture facilitates the understanding and, hence, harnessing of the human system risk-related data supply chain which enhances the ability to securely collect, integrate, and share data assets that improve human system research and operations. By mapping the risk-related data flow from raw data to useable information and knowledge (think of it as a data supply chain), the Human Research Program (HRP) and Space Life Science Directorate (SLSD) are building an information architecture plan to leverage their existing, and often shared, IT infrastructure.
The objective of this investigation was to establish whether crystallographic texture played a role in variable ST ductility in 2219-T87 thick plate. The EBSD study involved data collection at NASA Glenn Research Center and ODF analysis of the imported data at NASA Langley Research Center. The most significant result was that through-thickness variations in microtextural characteristics were asymmetrical about the mid-plane of the plate. However, the overall texture intensity was low, such that cross-sectional variations were classified as a second order effect on ST ductility.
Wind tunnel tests to determine noise data from scale model research aircraft are discussed. Comparisons are made between data obtained in wind tunnels and results of full scale flight tests. The acoustic measurements for the XV-5B V/STOL fan research aircraft are presented.
This report presents DSN progress in flight project support, tracking and data acquisition (TDA) research and technology, network engineering, hardware and software implementation, and operations. Each issue presents material in some, but not all, of the following categories in the order indicated. - Description of the DSN - Mission Support Ongoing Planetary/Interplanetary Flight Projects Advanced Flight Projects - Radio Science - Special Projects - Supporting Research and Technology Tracking and Ground-Based Navigation Communications--Spacecraft/Ground Station Control and Operations Technology Network Control and Data Processing - Network and Facility Engineering and Implementation Network Network Operations Control Center Ground Communications Deep Space Stations - Operations Network Operations Network Operations Control Center Ground Communications Deep Space Stations - Program Planning TDA Planning Quality Assurance In each issue, the part entitled "Description of the DSN" describes the functions and facilities of the DSN and may report the current configuration of one of the five DSN systems (Tracking, Telemetry, Command, Monitor & Control, and Test & Training). The work described in this report series is either performed or managed by the Tracking and Data Acquisition organization of JPL for NASA.
The objective of the Hyper-X program was to flight demonstrate an airframe-integrated hypersonic vehicle. On March 27, 2004, the Hyper-X program team successfully conducted flight 2 and achieved all of the research objectives. The Hyper-X research vehicle successfully separated from the Hyper-X launch vehicle and achieved the desired engine test conditions before the experiment began. The research vehicle rejected the disturbances caused by the cowl door opening and the fuel turning on and off and maintained the engine test conditions throughout the experiment. After the engine test was complete, the vehicle recovered and descended along a trajectory while performing research maneuvers. The last data acquired showed that the vehicle maintained control to the water. This report will provide an overview of the research vehicle guidance and control systems and the performance of the vehicle during the separation event and engine test. The research maneuvers were performed to collect data for aerodynamics and flight controls research. This report also will provide an overview of the flight controls related research and results.
These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). This data release is a combined, multi-sector transit search only. The underlying data products from individual observing sectors have been previously released. The data products included in this data release are the Data Validation (DV) reports, time series, and associated xml les for the threshold crossing events (TCEs) found by searching a combined data set including data from multiple observing sectors. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD)1. The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2017)2. The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018)3 contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.
These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel les, light curve les, collateral pixel les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD)1. The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2017).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.
These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel fi les, light curve fi les, collateral pixel fi les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml fi les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD). The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2019).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.
These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). This data release is a combined, multi-sector transit search only. The underlying data products from individual observing sectors have been previously released. The data products included in this data release are the Data Validation (DV) reports, time series, and associated xml files for the threshold crossing events (TCEs) found by searching a combined data set including data from multiple observing sectors. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD)1. The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2020)2. The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.
Research being undertaken to develop expert systems for reducing telemetry data from spacecraft is described. The use of the Hubble Space Telescope Electrical Power System as a testbed is examined. The Nickel Cadmium Battery Expert System is briefly addressed, and the I-DARE (Intelligent Data Reduction) prototype system is discussed.
In a cooperative program with Pratt & Whitney, researchers obtained fundamental separated flow unsteady aerodynamic data in the NASA Lewis Research Center's Oscillating Cascade. These data fill a void that has hindered the understanding and prediction of subsonic and transonic stall flutter. For small-amplitude torsional oscillations, unsteady pressure distributions were measured on airfoils with cross sections representative of an advanced, low-aspect-ratio fan blade. Data were obtained for two mean incidence angles with a subsonic inflow. At high mean incidence angles (alpha = 10 deg), the mean flow separated at the leading edge and reattached at about 40 percent of the chord. For comparison purposes, data were also obtained for a low incidence angle (a = 0 deg) attached flow.
Introduction: For small communities in diverse fields such as astrobiology, publishing and sharing data can be a difficult challenge. While large, homogenous fields often have repositories and existing data standards, small groups of independent researchers have few options for publishing standards and data that can be utilized within their community. In conjunction with teams at NASA Ames and the University of Arizona, the Open Data Repository's (ODR) Data Publisher has been conducting ongoing pilots to assess the needs of diverse research groups and to develop software to allow them to publish and share their data collaboratively. Objectives: The ODR's Data Publisher aims to provide an easy-to-use and implement software tool that will allow researchers to create and publish database templates and related data. The end product will facilitate both human-readable interfaces (web-based with embedded images, files, and charts) and machine-readable interfaces utilizing semantic standards. Characteristics: The Data Publisher software runs on the standard LAMP (Linux, Apache, MySQL, PHP) stack to provide the widest server base available. The software is based on Symfony (www.symfony.com) which provides a robust framework for creating extensible, object-oriented software in PHP. The software interface consists of a template designer where individual or master database templates can be created. A master database template can be shared by many researchers to provide a common metadata standard that will set a compatibility standard for all derivative databases. Individual researchers can then extend their instance of the template with custom fields, file storage, or visualizations that may be unique to their studies. This allows groups to create compatible databases for data discovery and sharing purposes while still providing the flexibility needed to meet the needs of scientists in rapidly evolving areas of research. Research: As part of this effort, a number of ongoing pilot and test projects are currently in progress. The Astrobiology Habitable Environments Database Working Group is developing a shared database standard using the ODR's Data Publisher and has a number of example databases where astrobiology data are shared. Soon these databases will be integrated via the template-based standard. Work with this group helps determine what data researchers in these diverse fields need to share and archive. Additionally, this pilot helps determine what standards are viable for sharing these types of data from internally developed standards to existing open standards such as the Dublin Core (http://dublincore.org) and Darwin Core (http://rs.twdg.org) metadata standards. Further studies are ongoing with the University of Arizona Department of Geosciences where a number of mineralogy databases are being constructed within the ODR Data Publisher system. Conclusions: Through the ongoing pilots and discussions with individual researchers and small research teams, a definition of the tools desired by these groups is coming into focus. As the software development moves forward, the goal is to meet the publication and collaboration needs of these scientists in an unobtrusive and functional way.
The accomplishments in the following three research areas are summarized: multiwavelength study of active galactic nuclei; magnetic activity of young stellar objects; and statistical methodology for astronomical data analysis. The research is largely based on observations of the ROSAT and ASCA X-ray observatories, complemented by ground-based optical and radio studies. Major findings include: discovery of inverse Compton X-ray emission from radio galaxy lobes; creation of the largest and least biased available sample of BL Lac objects; characterization of X-ray and nonthermal radio emission from T Tauri stars; obtaining an improved census of young stars in a star forming region and modeling the star formation history and kinematics; discovery of X-ray emission from protostars; development of linear regression methods and codes for interpreting astronomical data; and organization of the first cross-disciplinary conferences for astronomers and statisticians.
The first project of the World Climate Research Program is the International Satellite Cloud Climatology Project, (ISCCP) whose objective is the collection and analysis of satellite radiance data in order to infer the global distribution of cloud radiative properties and improve the modeling of cloud effects on climate. The operational component of ISCCP takes advantage of the global coverage provided by the current and planned international array of geostationary and polar-orbiting meteorological satellites in the 1980s. It will produce a five-year global radiance and cloud data set. The research component of ISCCP will coordinate studies to validate climatology, improve cloud analysis algorithms, improve cloud effects modelling, and investigate the role of clouds in the atmospheric radiation budget and hydrologic cycle.
Listening to the case studies that were presented it became quite evident that the best data management systems were the ones where data managers and research scientists worked as a team developed in the early stages of project planning. Examples that were given included WOCE Data Assembly Centres e.g., Drifters, the Global Temperature Salinity Pilot Project (GTSPP) collaboration with Joint Analyses Centres in the U.S. and Australia, and JGOFS/BOFS development of Topical Centres. While each of these has some elements unique to the project, each had brought together 'teams' of Principal Investigators (PI's) and data management experts at an early stage of project development. Conversely, projects which had considered data management as a totally separate activity with lower priority often failed to provide the service required to meet scientific objectives. Therefore, the following actions should be brought to the attention of relevant groups within the IOC and other international organizations: (1) Publicize, at the national and international level, underway data/scientist collaborations that may be used as models in planning for the future. (2) Reduce adversarial situations where data managers and scientists appear to be in competition. (3) Colocation and other forms of collaboration often results in very high quality data sets and more timely data submission. Improved timeliness of data submissions was a common theme throughout the workshop and must be considered an important element in all future plans. Improvements in timely submission of data were noted. In order to continue this trend the advantages of timely submission of data must be stressed to those planning new ocean science projects.
Some of the Earth system data products such as those from NASA airborne and field investigations (a.k.a. campaigns), are highly heterogeneous and cross-disciplinary, making the data extremely challenging to manage. For example, airborne and field campaign measurements tend to be sporadic over a period of time, with large gaps. Data products generated are of various processing levels and utilized for a wide range of inter- and cross-disciplinary research and applications. Data and derived products have been historically stored in a variety of domain-specific standard (and some non-standard) formats and in various locations such as NASA Distributed Active Archive Centers (DAACs), NASA airborne science facilities, field archives, or even individual scientists’ computer hard drives. As a result, airborne and field campaign data products have often been managed and represented differently, making it onerous for data users to find, access, and utilize campaign data. Some difficulties in discovering and accessing the campaign data originate from the incomplete data product and contextual metadata that may contain details relevant to the campaign (e.g. campaign acronym and instrument deployment locations), but tend to lack other significant information needed to understand conditions surrounding the data. Such details can be burdensome to locate after the conclusion of a campaign. Utilizing consistent terminology, essential for improved discovery and reuse, is also challenging due to the variety of involved disciplines. To help address the aforementioned challenges faced by many repositories and data managers handling airborne and field data, this presentation will describe stewardship practices developed by the Airborne Data Management Group (ADMG) within the Interagency Implementation and Advanced Concepts Team (IMPACT) under the NASA’s Earth Science Data systems (ESDS) Program.