Mission to Planet Earth: Past Progress and Future Prospects
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TESS Data Release Notes: Sectors 1 – 13, Multi-Sector Search, DR20
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.
Burke, Christopher J.↗
TESS Data Release Notes: Sector 21 DR 29
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.
Michael M. Fausnaugh↗
TESS Data Release Notes: Sector 24, DR35
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.
TESS↗
An interoperable data architecture for data exchange in a biomedical research network
This paper discusses the approach taken to develop a prototype data architecture for the discovery and validation of disease biomarkers within a biomedical research network.
data↗
TESS Data Release Notes: Sectors 1 – 36, Multi-sector Search, DR53
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.
TESS↗
Life Sciences Data Archives (LSDA) in the Post-Shuttle Era
Now, more than ever before, NASA is realizing the value and importance of their intellectual assets. Principles of knowledge management-the systematic use and reuse of information, experience, and expertise to achieve a specific goal-are being applied throughout the agency. LSDA is also applying these solutions, which rely on a combination of content and collaboration technologies, to enable research teams to create, capture, share, and harness knowledge to do the things they do well, even better. In the early days of spaceflight, space life sciences data were collected and stored in numerous databases, formats, media-types and geographical locations. These data were largely unknown/unavailable to the research community. The Biomedical Informatics and Health Care Systems Branch of the Space Life Sciences Directorate at JSC and the Data Archive Project at ARC, with funding from the Human Research Program through the Exploration Medical Capability Element, are fulfilling these requirements through the systematic population of the Life Sciences Data Archive. This project constitutes a formal system for the acquisition, archival and distribution of data for HRP-related experiments and investigations. The general goal of the archive is to acquire, preserve, and distribute these data and be responsive to inquiries for the science communities. Information about experiments and data, as well as non-attributable human data and data from other species' are available on our public Web site http://lsda.jsc.nasa.gov. The Web site also includes a repository for biospecimens, and a utilization process. NASA has undertaken an initiative to develop a Shuttle Data Archive repository. The Shuttle program is nearing its end in 2010 and it is critical that the medical and research data related to the Shuttle program be captured, retained, and usable for research, lessons learned, and future mission planning. Communities of practice are groups of people who share a concern or a passion for something they do, and learn how to do it better as they interact regularly. LSDA works with the HRP community of practice to ensure that we are preserving the relevant research and data they need in the LSDA repository. An evidence-based approach to risk management is required in space life sciences. Evidence changes over time. LSDA has a pilot project with Collexis, a new type of Web-based search engine. Collexis differentiates itself from full-text search engines by making use of thesauri for information retrieval. The high-quality search is based on semantics that have been defined in a life sciences ontology. Additionally, Collexis' matching technology is unique, allowing discovery of partially matching dicuments. Users do not have to construct a complicated (Boolean) search query, but can simply enter a free text search without the risk of getting "no results". Collexis may address these issues by virtue of its retrieval and discovery capabilities across multiple repositories.
Fitts, Mary A.↗
Inter-agency Working Group for Airborne Data and Telemetry Systems (IWGADTS)
The Interagency Coordinating Committee for Airborne Geosciences Research and Applications (ICCAGRA) was established to improve cooperation and communication among agencies sponsoring airborne platforms and instruments for research and applications, and to serve as a resource for senior level management on airborne geosciences issues. The Interagency Working Group for Airborne Data and Telecommunications Systems (IWGADTS) is a subgroup to ICCAGRA for the purpose of developing recommendations leading to increased interoperability among airborne platforms and instrument payloads, producing increased synergy among research programs with similar goals, and enabling the suborbital layer of the Global Earth Observing System of Systems.
Webster, Chris↗
End-user Assessment of the NASA SPoRT GLM Stoplight Product
National Weather Service (NWS) offices monitor and forecast the threat for lightning within their County Warning Areas for various impact-based decision support services (IDSS). These forecasts are provided routinely for aviation operations, but irregularly for large-scale, outdoor events, which typically have varying safety requirements with regards to lightning. Lightning monitoring and forecasting can require synthesizing a plethora of data, so products that make this process more efficient and effective are sought by the operational community. The NASA Short-term Prediction Research and Transition (SPoRT) Center has begun to develop several products to address these operational challenges during the lifecycle of lightning activity, and conduct evaluations in concentrated (Research-to-Operations/Operations-to-Research) efforts. The product evaluated for this study is the Geostationary Lightning Mapper (GLM) Stoplight product, which addresses lightning safety specifically with regards to lightning recency and cessation. The GLM Stoplight product displays the spatial extent of lightning and uses color-coded pixels to show the recency of lightning in 10-minute increments. This presentation highlights results from an assessment of the GLM Stoplight product by select NWS offices, as well as emergency managers, that took place over a 5-week period from May 1st to June 2nd. Feedback was collected on the GLM Stoplight product and on a new and interactive lightning viewer, which allowed participants to tailor visualization of the product based on their location and desired application. Results will help NASA SPoRT gain a better understanding of how forecasters and emergency managers use lightning data for safety applications. In addition, the assessment will inform research on any necessary modifications to this and future lightning products to assist end users.
Kelley Murphy↗
Using Remotely Sensed Data for Climate Change Mitigation and Adaptation: A Collaborative Effort Between the Climate Change Adaptation Science Investigators Workgroup (CASI), NASA Johnson Space Center, and Jacobs Technology
With ever changing landscapes and environmental conditions due to human induced climate change, adaptability is imperative for the long-term success of facilities and Federal agency missions. To mitigate the effects of climate change, indicators such as above-ground biomass change must be identified to establish a comprehensive monitoring effort. Researching the varying effects of climate change on ecosystems can provide a scientific framework that will help produce informative, strategic and tactical policies for environmental adaptation. As a proactive approach to climate change mitigation, NASA tasked the Climate Change Adaptation Science Investigators Workgroup (CASI) to provide climate change expertise and data to Center facility managers and planners in order to ensure sustainability based on predictive models and current research. Generation of historical datasets that will be used in an agency-wide effort to establish strategies for climate change mitigation and adaptation at NASA facilities is part of the CASI strategy. Using time series of historical remotely sensed data is well-established means of measuring change over time. CASI investigators have acquired multispectral and hyperspectral optical and LiDAR remotely sensed datasets from NASA Earth Observation Satellites (including the International Space Station), airborne sensors, and astronaut photography using hand held digital cameras to create a historical dataset for the Johnson Space Center, as well as the Houston and Galveston area. The raster imagery within each dataset has been georectified, and the multispectral and hyperspectral imagery has been atmospherically corrected. Using ArcGIS for Server, the CASI-Regional Remote Sensing data has been published as an image service, and can be visualized through a basic web mapping application. Future work will include a customized web mapping application created using a JavaScript Application Programming Interface (API), and inclusion of the CASI data for the NASA Johnson Space Center into a NASA-Wide GIS Institutional Portal.
Jagge, Amy↗
Approach to Managing MeaSURES Data at the GSFC Earth Science Data and Information Services Center (GES DISC)
A major need stated by the NASA Earth science research strategy is to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. (NASA Solicitation for Making Earth System data records for Use in Research Environments (MEaSUREs) 2006-2010) Selected projects create long term records of a given parameter, called Earth Science Data Records (ESDRs), based on mature algorithms that bring together continuous multi-sensor data. ESDRs, associated algorithms, vetted by the appropriate community, are archived at a NASA affiliated data center for archive, stewardship, and distribution. See http://measures-projects.gsfc.nasa.gov/ for more details. This presentation describes the NASA GSFC Earth Science Data and Information Services Center (GES DISC) approach to managing the MEaSUREs ESDR datasets assigned to GES DISC. (Energy/water cycle related and atmospheric composition ESDRs) GES DISC will utilize its experience to integrate existing and proven reusable data management components to accommodate the new ESDRs. Components include a data archive system (S4PA), a data discovery and access system (Mirador), and various web services for data access. In addition, if determined to be useful to the user community, the Giovanni data exploration tool will be made available to ESDRs. The GES DISC data integration methodology to be used for the MEaSUREs datasets is presented. The goals of this presentation are to share an approach to ESDR integration, and initiate discussions amongst the data centers, data managers and data providers for the purpose of gaining efficiencies in data management for MEaSUREs projects.
Vollmer, Bruce↗
Aviation System Analysis Capability Quick Response System Report Server User's Guide
This report is a user's guide for the Aviation System Analysis Capability Quick Response System (ASAC QRS) Report Server. The ASAC QRS is an automated online capability to access selected ASAC models and data repositories. It supports analysis by the aviation community. This system was designed by the Logistics Management Institute for the NASA Ames Research Center. The ASAC QRS Report Server allows users to obtain information stored in the ASAC Data Repositories.
DATA STORAGE SYSTEMS↗
LMI Automated Air Cargo Operations Market Research and Forecast
Air cargo companies and aircraft manufacturers are making significant investments to enable the movement of cargo via various levels of automated aircraft, such as aircraft with simplified operations requiring a pilot, remotely monitored or piloted aircraft, and fully autonomous aircraft. These investments will enable greater utilization of aircraft while unlocking new air markets traditionally served by ground transportation only. Many cargo companies and aerospace experts envision an operating environment where a single pilot can remotely pilot numerous aircraft for significant increases in aircraft utilization. The future operating environment is also expected to include air cargo companies flying smaller aircraft from airports and distribution centers outside of major U.S. cities directly to city centers, avoiding congested roads and increasing the velocity of cargo shipments, particularly those that are high-value, time-sensitive, and security sensitive (e.g., pharmaceuticals). These are just a few benefits and use cases cargo companies and aerospace experts see with the advancement of automated aircraft. To better understand industry’s direction, NASA asked the LMI team to research the forecasted market, timeline, risks, and opportunities for integrating unmanned air cargo vehicles into the National Airspace System (NAS) for the development and prioritization of the NASA Air Traffic Management Exploration’s research portfolio. To begin the market assessment, we gathered data via numerous interviews with key stakeholders and subject matter experts and literature reviews. We then incorporated the data into a custom-developed systems dynamics model and visualization dashboard. The systems dynamics model classifies the size of the market (e.g., overall fleet size of automated aircraft) for four distinct use cases over the next 20 years. The model projects the year in which various types of automated aircraft will enter the commercial cargo market based on our team’s collective research on when the aircraft will become viable due to manufacturing and certification timelines and the lifespan of current, traditional aircraft in service, to name a few factors. While this report defines our team’s estimated timeline of entry and growth, the model is dynamic—it enables NASA users to change variables based on future-year events. If the necessary technology does not mature in accordance with our assumptions, then NASA can change the entry of service point to a future year to evaluate the changes in market size in the out years. This flexibility will be key to deciding when and how NASA should invest in various areas.
air traffic management↗
An object-oriented approach to the management of meteorological and hydrological data
An interface to several meteorological and hydrological databases have been developed that enables researchers efficiently to access and interrelate data through a customized menu system. By extending a relational database system with object-oriented concepts, each user or group of users may have different 'views' of the data to allow user access to data in customized ways without altering the organization of the database. An application to COHMEX and WetNet, two earth science projects within NASA Marshall Space Flight Center's Earth Science and Applications Division, are described.
Graves, S. J.↗
Effects of Modality on Interrupted Flight Deck Performance: Implications for Data Link
Externally-imposed tasks frequently interrupt ongoing task performance in the commercial flight deck. While normally managed without consequence, basic research as well as aviation accident and incident investigations show that interruptions can negatively affect performance and safety. This research investigates the influence of interruption and interrupted task modality on pilot performance in a simulated commercial flight deck. Fourteen current commercial airline pilots performed approach scenarios in a fixed-base flight simulator. Air traffic control instructions, conveyed either aurally or visually (via a data link system) interrupted a visual task (obtaining information from the Flight Management System) and an auditory task (listening to the automated terminal information service recording). Some results confirm the hypothesized performance advantage of cross-modality conditions, more compelling nature of auditory interruptions, and interruption-resistance of auditory ongoing tasks. However, taken together, results suggest the four interaction conditions had different effects on pilot performance. These results have implications for the design of data link systems, and for facilitating interruption management through interface design, aiding, and training programs.
Latorella, Kara A.↗
SPHERES: From Ground Development to Operations on ISS
SPHERES (Synchronized Position Hold Engage and Reorient Experimental Satellites) is an internal International Space Station (ISS) Facility that supports multiple investigations for the development of multi-spacecraft and robotic control algorithms. The SPHERES Facility on ISS is managed and operated by the SPHERES National Lab Facility at NASA Ames Research Center (ARC) at Moffett Field California. The SPHERES Facility on ISS consists of three self-contained eight-inch diameter free-floating satellites which perform the various flight algorithms and serve as a platform to support the integration of experimental hardware. To help make science a reality on the ISS, the SPHERES ARC team supports a Guest Scientist Program (GSP). This program allows anyone with new science the possibility to interface with the SPHERES team and hardware. In addition to highlighting the available SPHERES hardware on ISS and on the ground, this presentation will also highlight ground support, facilities, and resources available to guest researchers. Investigations on the ISS evolve through four main phases: Strategic, Tactical, Operations, and Post Operations. The Strategic Phase encompasses early planning beginning with initial contact by the Principle Investigator (PI) and the SPHERES program who may work with the PI to assess what assistance the PI may need. Once the basic parameters are understood, the investigation moves to the Tactical Phase which involves more detailed planning, development, and testing. Depending on the nature of the investigation, the tactical phase may be split into the Lab Tactical Phase or the ISS Tactical Phase due to the difference in requirements for the two destinations. The Operations Phase is when the actual science is performed; this can be either in the lab, or on the ISS. The Post Operations Phase encompasses data analysis and distribution, and generation of summary status and reports. The SPHERES Operations and Engineering teams at ARC is composed of experts who can guide the Payload Developer (PD) and Principle Investigator (PI) in reaching critical milestones to make their science a reality using the SPHERES platform. From performing integrated safety and verification assessments, to assisting in developing crew procedures and operations products, to organizing, planning, and executing all test sessions, to helping manage data products, the SPHERES team at ARC is available to support microgravity research with the SPEHRES Guest Scientist Program.
ISS Research↗
Management systems research study
The development of a Monte Carlo simulation of procurement activities at the NASA Ames Research Center is described. Data cover: simulation of the procurement cycle, construction of a performance evaluation model, examination of employee development, procedures and review of evaluation criteria for divisional and individual performance evaluation. Determination of the influences and apparent impact of contract type and structure and development of a management control system for planning and controlling manpower requirements.
Bruno, A. V.↗
A unique approach to the development of adaptive sensor systems for future spacecraft
In the Shuttle era, it should be possible to develop adaptive remote sensor systems serving more directly specific researcher and user needs and at the same time alleviating the data management problem via intelligent sensor capabilities. The present paper provides a summary of such an approach, wherein specific capabilities have been developed for future global monitoring applications. A detailed description of FILE-I (Feature Identification and Location Experiment) is included along with a summary of future experiments currently under development.
Schappell, R. T.↗