Human Research Program Data Sharing Process
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As custodians of the unique and irreplaceable collections of human subject research data generated by the Human Research Program and its predecessors throughout the agency’s history, the Life Sciences Data Archive (LSDA) is charged with protecting participants’ privacy and implementing their consent decisions as it provides retrospective data for use in new studies. This active, stewardship-focused approach to data management and preservation shapes the products that LSDA provides to researchers and the responsibilities of researchers in using the data and publishing their results. This presentation reviews how federal and agency mandates shape LSDA’s data management procedures and expectations for researchers. Topics covered will include LSDA’s movement towards implementation of the FAIR (Findable, Accessible, Interoperable, Reusable) principles and the archive’s evolving data management practices; collaboration between LSDA and the Lifetime Surveillance of Astronaut Health (LSAH) project (the repository of astronaut medical data); LSDA’s response to the challenges of performing its stewardship role and maintaining trust given the public profiles of the subjects whose data it preserves; and the ever-increasing challenges to expectations of subject privacy stemming from the growing power and ubiquity of data analysis and aggregation tools.
As custodian of the unique and irreplaceable collections of human subject research data generated by the Human Research Program and its predecessors throughout the agency’s history, the Life Sciences Data Archive (LSDA) is charged with protecting participants’ privacy and implementing their consent decisions as it provides retrospective data for use in new studies. This active, stewardship-focused approach to data management and preservation shapes the products that LSDA provides to researchers and the responsibilities of researchers in using the data and publishing their results. This presentation reviews how federal and agency mandates shape LSDA’s data management procedures and expectations for researchers. Topics covered will include LSDA’s movement towards implementation of the FAIR (Findable, Accessible, Interoperable, Reusable) principles and how the archive’s evolving data management practices support FAIR-ness; collaboration between LSDA and the Lifetime Surveillance of Astronaut Health (LSAH) project (the repository of astronaut medical data); LSDA’s response to the challenges of performing its stewardship role and maintaining trust given the public profiles of the subjects whose data it preserves; and the ever-increasing challenges to expectations of subject privacy stemming from the growing power and ubiquity of of data analysis and aggregation tools.
The FAIR principle (findable, accessible, interoperable, and reusable) governs the storage and sharing of NASA space biology and health data[1]. These guiding principles maximize reuse of data and the reproducibility of scientific findings. The NASA Open Science Data Repository (OSDR; an expansion of NASA GeneLab) was built on the FAIR principles and houses over 500 studies and close to 1000 datasets from decades of space life sciences experiments. OSDR embodies the FAIR principles through data governance that includes mediated, embargoed, and fully open access data. The FAIR data governance principles were recently proposed to be expanded to encompass a FAIREST framework for assessing research data repositories (FAIR + Engagement, Social connections, and Trust)[2]. FAIREST emphasizes the importance of data repositories engaging with the scientific community and gaining the trust of researchers regarding data quality. Trust also refers to the TRUST principles developed for assessment of digital repositories: Transparency, Responsibility, User Focus, Sustainability, Technology[3]. We present the “Open Science for Life in Space” Analysis Working Groups (AWGs) as evidence regarding the power of engagement, social connections, and trust which has enhanced OSDR’s capabilities and productivity. AWG members engage in two main activities. One, members provide feedback on OSDR scientific standards for data ingestion, curation, and reuse (study, subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability). Two, AWG members collaborate to mine-reuse OSDR data to conduct scientific analysis. With nearly 800 active members, the AWGs have resulted in 32 publications re-using OSDR data and contributed many papers in two major special issues in Cell (2020) and Nature (2024). AWGs also serve as networking groups, facilitate social connections between researchers at all levels of experience, and also have a social online ‘Forum’ used to keep members informed on projects and opportunities. This community-centric, productive, and trustworthy data culture has resulted in a broader effect with international space agencies, academics, and the commercial space sector wanting to submit their data to OSDR. Ten studies of Inspiration 4 data were recently publicly released by OSDR, as were some JAXA human data. Coming up soon in OSDR are data submissions from the European Space Agency, Virgin Galactic PIs, and SpaceX Polaris Dawn. A major benefit of OSDR is the array of standardized and uniformly formatted data (which was developed through AWG member consensus), from which visualization tools, analysis tools, and machine learning models can be built or trained. This talk will cover the Multi-Study Visualization Tool, the Environmental Data Application, RadLab, and a UCSF-NSF funded knowledge graph biomedical health discovery tool ‘SPOKE’ currently being integrated with OSDR. OSDR also provides training programs in bioinformatics and machine learning to improve the scientific community’s awareness of data availability and to boost their ability to perform data analysis. The increasing engagement of the scientific community and the public with technologies powered by artificial intelligence (AI) heightens the need for data analysis to be transparent. The AI for Life in Space initiative leverages the data products provided in OSDR to train AI models, with an emphasis on explainable and trustworthy AI, which would not be possible without FAIR data and metadata. Overall, here we will demonstrate the importance for NASA life sciences data repositories to adhere to the FAIREST framework, by providing examples and success stories from different aspects of OSDR.
Research on data diversity is discussed. Data diversity relies on a different form of redundancy from existing approaches to software fault tolerance and is substantially less expensive to implement. Data diversity can also be applied to software testing and greatly facilitates the automation of testing. Up to now it has been explored both theoretically and in a pilot study, and has been shown to be a promising technique. The effectiveness of data diversity as an error detection mechanism and the application of data diversity to differential equation solvers are discussed.
The application of an experimental flight test maneuver autopilot test technique for collecting aerodynamic and structural flight research data on a highly maneuverable aircraft is described in this paper. This technique, which was developed to increase the quality and quantity of data obtained during flight test, was applied to the highly maneuverable aircraft technology (HiMAT) vehicle. A primary flight experiment was to verify the design techniques used to develop the HiMAT aerodynamics and structures. This required the performance of maneuvers for collection of large quantities of high-quality pressure distribution, loads, and wing and canard deflection data. Flight data obtained while executing these research maneuvers are presented to demonstrate the effectiveness of this new technique.
The Combined Loads Test System (COLTS) is a new structures test complex that is being developed at NASA Langley Research Center (LaRC) to test large curved panels and cylindrical shell structures. These structural components are representative of aircraft fuselage sections of subsonic and supersonic transport aircraft and cryogenic tank structures of reusable launch vehicles. Test structures are subjected to combined loading conditions that simulate realistic flight load conditions. The facility consists of two pressure-box test machines and one combined loads test machine. Each test machine possesses a unique set of requirements or research data acquisition and real-time data display. Given the complex nature of the mechanical and thermal loads to be applied to the various research test articles, each data system has been designed with connectivity attributes that support both data acquisition and data management functions. This paper addresses the research driven data acquisition requirements for each test machine and demonstrates how an open architecture data system design not only meets those needs but provides robust data sharing between data systems including the various control systems which apply spectra of mechanical and thermal loading profiles.
Recent NASA Common Research Model (CRM) tests at the Langley National Transonic Facility (NTF) and Ames 11-foot Transonic Wind Tunnel (11-foot TWT) have generated an experimental database for CFD code validation. The database consists of force and moment, surface pressures and wideband wing-root dynamic strain/wing Kulite data from continuous sweep pitch polars. The dynamic data sets, acquired at 12,800 Hz sampling rate, are analyzed in this study to evaluate CRM wing buffet onset and potential CRM wing flow separation.
A NASA, F-106B airplane equipped with a vortex flap is establishing a data base for calibration of design and analysis tools for this vortical flow control concept. Some of the problems in safely and precisely flying to research data points were caused by the modified airplane's low longitudinal stability and low margin of structural strength. These characteristics are, in part, a consequence of the program's low cost approach which utilizes a bolt-on, ground-adjustable flap attached to a minimally modified airplane. Presently, the 40-degree flap deflection flight research is being concluded with a flow visualization phase. A similar pattern of flight envelope expansion, pressure distribution, performance, and flow visualization phases remain to be accomplished for the 30-degree flap setting. To date, good research flight data has followed resolution of the safety and data problems described.
NASA PDS hosts terabytes of valuable data from hundreds of data sources and spans decades of research. Data is stored on flat-file systems regulated through careful meta dictionaries. PDS's data is available to the public through its website which supports data searches through drill-down navigation. While the system returns data quickly, result sets in response to identical input differ depending on the drill-down path a user follows. To correct this Issue, to allow custom searching, and to improve general accessibility, PDS sought to create a new data structure and API, and to use them to build applications that are a joy to use and showcase the value of the data to students, teachers and citizens. PDS engaged TopCoder and Harvard Business School through the NTL to pursue these objectives in a pilot effort. Scope was limited to Small Bodies Node data. NTL analyzed data, proposed a solution, and implemented it through a series of micro-contests. Contest focused on different segments of the problem; conceptualization, architectural design, implementation, testing, etc. To demonstrate the utility of the completed solution, NTL developed web-based and mobile applications that can compare targets, regardless of mission. To further explore the potential of the solution NTL hosted "Mash-up" challenges that integrated the API with other publically available assets, to produce consumer and teaching applications, including an Augmented Reality iPad tool. Two contests were also posted to middle and high school students via the NoNameSite.com platform, and as a result of these contests, PDS/SBN has initiated a Facebook program. These contests defined and implemented a data warehouse with the necessary migration tools to transform legacy data, produced a public web interface for the new search, developed a public API, and produced four mobile applications that we expect to appeal to users both within and, without the academic community.
The application of hyper spectral radiometric data to climate research requires very high absolute radiometric accuracy and stability. We use cloud-free tropical ocean data from the Atmospheric InfraRed Sounder (AIR) Calibration Data Subset (ADCS) to show that the radiometric precision and stability required climate applications has been achieved. The sea surface skin temperatures derived from the AIRS 2616cm-1 super window channel are stable relative to the RTG.SST at the better than 8 mK/year level, and the spectral calibration is stable at the 1 ppm/year level. The excellent stability and accuracy are the result of the implementation of AIRS as a grating array spectrometer, which is cooled and stabilized within 10 mK at 155 K. Analysis of daily measurements of the temperature gradient between the surface and 7 km altitude show that the AIRS Calibration Data Subset has applications which extend its original intent for calibration support to climate research. The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua satellite was launched into polar orbit in May 2002. AIRS covers the spectral region from 640 to 2700 cm-1 with 2378 independent channels and represents the first of a new generation of hyper spectral resolution sounders in support of global sounding data for weather forecasting and climate research.
Research and development data policies of civilian government agencies
There is a rich and long history of thermal infrared (TIR) remote sensing data for multidisciplinary Earth science research. The continuity of TIR data collection, however, is now in jeopardy given there are no planned future Earth observing TIR remote sensing satellite systems with moderately high spatial resolutions to replace those currently in orbit on NASA's Terra suite of sensors. This session will convene researchers who have actively worked in the field of TIR remote sensing to present results that elucidate the importance of thermal remote sensing to the wider Earth science research community. Additionally, this session will also exist as a forum for presenting concepts and ideas for new thermal sensing systems with high spatial resolutions for future Earth science satellite missions, as opposed to planned systems such as the Visible/Infrared Imager/Radiometer (VIIRS) suite of sensors on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) that will collect TIR data at very coarse ~~~iairesolutions.
Food and nutrient databases are populated with data obtained from a variety of sources including USDA Reference Tables, scientific journals, food manufacturers and foreign food tables. The food and nutrient database maintained by the Nutrition Coordinating Center (NCC) at the University of Minnesota is continually updated with current nutrient data and continues to be expanded with additional nutrient fields to meet diverse research endeavors. Data are strictly evaluated for reliability and relevance before incorporation into the database; however, the values are obtained from various sources and food samples rather than from direct chemical analysis of specific foods. Precise nutrient values for specific foods are essential to the nutrition program at the National Aeronautics and Space Administration (NASA). Specific foods to be included in the menus of astronauts are chemically analyzed at the Johnson Space Center for selected nutrients. A request from NASA for a method to enter the chemically analyzed nutrient values for these space flight food items into the Nutrition Data System for Research (NDS-R) software resulted in modification of the database and interview system for use by NASA, with further modification to extend the method for related uses by more typical research studies.
Automatic computer techniques for reduction and analyses of space research data
The Microgravity Research Program Office (MRPO) participated aggressively in Phase I of the International Space Station Program using the Russian Mir Space Station. The Mir Station offered an otherwise unavailable opportunity to explore the advantages and challenges to long duration microgravity space research. Payloads with both NASA and commercial backing were included as well as cooperative research with the Canadian Space Agency (CSA). From this experience, much was learned about dealing with long duration on orbit science utilization and developing new working relationships with our Russian partner to promote efficient planning, operations, and integration to solve complexities associated with a multiple partner program. Microgravity participation in the NASA Mir Program began with the first joint NASA Mir flight to the Mir Space Station. The earliest participation setup acceleration measurement capabilities that were used throughout the Program. Research, conducted by all Microgravity science disciplines, continued on each subsequent increment for the entire three-year duration of the Program. The Phase I Program included the Microgravity participation of over 30 Fluids, Combustion, Materials, and Biotechnology Sciences and numerous commercially sponsored research payloads. In addition to the research gained from Microgravity investigations, long duration operation of facility hardware was tested. Microgravity facilities operated on Mir included the Space Acceleration Measurement System (SAMS), the Microgravity Glovebox (MGBX), the Biotechnology System (BTS) and the Canadian Space Agency sponsored Microgravity Isolation Mount (MIM). The Russian OPTIZONE Furnace was also incorporated into our material science research. All of these efforts yielded significant and useful scientific research data. This paper focuses on the microgravity research conducted onboard the Mir space station. It includes the Program preparation and planning necessary to support this type of cross increment research experience; the payloads which were flown; and summaries of significant microgravity science findings. Most importantly this paper highlights the various disciplines of microgravity research conducted during the International Space Station, Phase 1 Program onboard the Mir Station. A capsulation of significant research and the applicability of our findings are provided. In addition, a brief discussion of how future microgravity science gathering capabilities, hardware development and payload operations techniques have enhanced our ability to conduct long duration microgravity research.