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Automated Metadata Scoring Approaches for Earth Observation Data

The Common Metadata Repository (CMR) contains metadata records describing NASA’s Earth observation data products which are archived across 12 data centers also known as Distributed Active Archive Centers (DAACs). To ensure that NASA’s data is discoverable, accessible, and usable, the Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, assesses the quality of these metadata records. The ARC team currently uses a combination of automated and manual methods to check metadata records for quality dimensions such as completeness, correctness, and consistency. In addition to these quality assessments, the team is currently exploring various metadata scoring methods in order to provide normalized results across the twelve DAACs. This method is conducted by using automated methods to assess metadata fields and then provide a numeric score, or grade, based on the analysis. To implement this process, two different approaches have been theorized and are currently being explored by the ARC team. This presentation will describe ARC's two proposed methodologies in more detail, and the pros and cons to using these metadata scoring methods.

Jenny Wood↗

The New Cloud Absorption Radiometer (CAR) Software: One Model for NASA Remote Sensing Virtual Instruments

The Cloud Absorption Radiometer (CAR) instrument has been the most frequently used airborne instrument built in-house at NASA Goddard Space Flight Center, having flown scientific research missions on-board various aircraft to many locations in the United States, Azores, Brazil, and Kuwait since 1983. The CAR instrument is capable of measuring scattered light by clouds in fourteen spectral bands in UV, visible and near-infrared region. This document describes the control, data acquisition, display, and file storage software for the new version of CAR. This software completely replaces the prior CAR Data System and Control Panel with a compact and robust virtual instrument computer interface. Additionally, the instrument is now usable for the first time for taking data in an off-aircraft mode. The new instrument is controlled via a LabVIEW v5. 1.1-developed software interface that utilizes, (1) serial port writes to write commands to the controller module of the instrument, and (2) serial port reads to acquire data from the controller module of the instrument. Step-by-step operational procedures are provided in this document. A suite of other software programs has been developed to complement the actual CAR virtual instrument. These programs include: (1) a simulator mode that allows pretesting of new features that might be added in the future, as well as demonstrations to CAR customers, and development at times when the instrument/hardware is off-location, and (2) a post-experiment data viewer that can be used to view all segments of individual data cycles and to locate positions where 'start' and stop' byte sequences were incorrectly formulated by the instrument controller. The CAR software described here is expected to be the basis for CAR operation for many missions and many years to come.

Roth, Don J.↗

Results of the 2001 JPL Balloon Flight Solar Cell Calibration Program

The 2001 solar cell calibration balloon flight campaign consisted of two flights, which occurred on June 26, 2001, and July 4, 2001. Fifty-nine modules were carried to an altitude of approximately 120,000 ft (36.6 km). Full I-V curves were measured on nineteen of these modules, and output at a fixed load was measured on thirty-two modules (forty-six cells), with some modules repeated on the second flight. Nine modules were flown for temperature measurement only. The data from the fixed load cells on the first flight was not usable. The temperature dependence of the first-flight data was erratic and we were unable to find a way to extract accurate calibration values. The I-V data from the first flight was good, however, and all data from the second flight was also good. The data was corrected to 28 C and to 1 AU (1.496 x 10(exp 8)km). The calibrated cells have been returned to their owners and can now be used as reference standards in simulator testing of cells and arrays.

Anspaugh, B. E.↗

NASA’s Advance Information Systems Technology (AIST) Program

NASA’s Earth Science Technology Office (ESTO) develops early-stage technologies to enhance scientific understanding. ESTO’s technologies can be reliably and confidently applied to a broad range of science measurements and missions, as well as facilitate practical applications to benefit society at large. As the lead technology office within the Earth Science Division of the NASA Science Mission Directorate, ESTO is focused on the technological challenges inherent to space-based investigations of our planet's dynamic, interrelated systems. Through flexible, science-driven technology strategies and a competitive selection process, ESTO-funded technologies have supported numerous Earth science missions as well as commercial applications. From next generation sensors and instruments to communication and information systems, ESTO technologies enable many NASA missions and data services. The Advanced Information Systems Technology (AIST) Program is one focal area of ESTO. AIST innovates information system technologies that enable the development of new observing systems as well as agile science investigations through data analytics and artificial intelligence tools and algorithms. AIST utilizes an end-to-end development approach with the goal of infusing mature technologies into future missions, measurements, and analysis. One thrust of AIST is data exploitation and analysis using an analytic center framework to make observational data and model output more accessible and usable to scientists conducting specific investigations as well as to extract higher-level science content and information from the data. The framework accelerates scientific discovery by harmonizing the data, tools, and computational resources. NASA’s upcoming Surface, Biology and Geology (SBG) mission is one such mission whose data architecture will leverage many of the technologies developed through the AIST program. This talk will highlight current and future program development goals.

Laura Rogers↗

Identification, Uncertainty Characterization and Robust Control Synthesis Applied to Large Flexible Structures Control

This paper demonstrates an approach to frequency domain identification for the explicit purpose of designing robust H(infinity) controllers. The approach transforms raw experimental data into a plant set estimate directly usable by modern robust control design software(e.g., Matlab Robust Control Toolboxes [11][2]). A key issue in control design from raw data is the question of whether the controller will work when applied to the true system. The main feature fo this approach is that the resulting controller in guaranteed to work as designed(when applied to the true system) to a prescribed statistical confidence. While the overall methodology addresses key theoretical issues, it has at the same time been specifically designed to support practical implementations. A simulation example is included to demonstrate the overall approach.

software↗

A Framework for Assessing Earth Observation Metadata Quality: Implications for Data Discovery and Open Science

The Common Metadata Repository (CMR) contains metadata records describing NASA’s collection of over 8,000 Earth observation data products. The Analysis and Review of CMR (ARC) Team at Marshall Space Flight Center assesses the quality of these metadata records. Metadata, rather than the data itself, is indexed for search in both discipline-specific datacenters and global or aggregated catalogs (such as Earth data Search), making it essential for determining whether a data product is appropriate for a given research question or application need. Since metadata connects users to data, it should be as accurate and complete as possible in addition to meeting minimum database requirements. The ARC team has developed a metadata quality framework by which to assess quality. The framework consists of a set of quality criteria that converge around the dimensions of correctness, completeness, and consistency, with the goal of improving the discoverability, accessibility, and usability of NASA’s Earth Observation data. The application of the framework has resulted in a measurable improvement in NASA’s metadata quality. Key aspects of the framework’s success are the ability to systematically evaluate metadata and provide actionable quality improvement recommendations. Lessons learned from the project will be shared along with implementation details which may be relevant to other science disciplines. By aiming to make data more discoverable and accessible to a broad user community, the ARC metadata quality framework helps contribute to NASA’s commitment to open science.

Jeanne Le Roux↗

Stewardship of NASA's Earth Science Data and Ensuring Long-Term Active Archives

Program, NASA has followed an open data policy, with non-discriminatory access to data with no period of exclusive access. NASA has well-established processes for assigning and or accepting datasets into one of 12 Distributed Active Archive Centers (DAACs) that are parts of EOSDIS. EOSDIS has been evolving through several information technology cycles, adapting to hardware and software changes in the commercial sector. NASA is responsible for maintaining Earth science data as long as users are interested in using them for research and applications, which is well beyond the life of the data gathering missions. For science data to remain useful over long periods of time, steps must be taken to preserve: (1) Data bits with no corruption, (2) Discoverability and access, (3) Readability, (4) Understandability, (5) Usability' and (6). Reproducibility of results. NASAs Earth Science data and Information System (ESDIS) Project, along with the 12 EOSDIS Distributed Active Archive Centers (DAACs), has made significant progress in each of these areas over the last decade, and continues to evolve its active archive capabilities. Particular attention is being paid in recent years to ensure that the datasets are published in an easily accessible and citable manner through a unified metadata model, a common metadata repository (CMR), a coherent view through the earthdata.gov website, and assignment of Digital Object Identifiers (DOI) with well-designed landing product information pages.

Data Management↗

Improving GES Disc Data Search and Discovery Through AI Metadata Augmentation

NASA’s Goddard Earth Science (GES) Data and Information Services Center (DISC) is one of twelve data centers in NASA's Science Mission Directorate (SMD), providing vital earth science data to a diverse user base. To enhance the discoverability of this data, GES DISC employs a keyword search system, which leverages scientific keywords embedded in dataset metadata. However, the evolving nature of scientific applications of our data necessitates regular review and augmentation of these keywords. To address this, we developed a service to automatically predict missing science keywords in the metadata. This service constructs a knowledge graph from the latest GES DISC metadata within NASA’s Common Metadata Repository (CMR). Using an open-source library, we trained a machine learning model to predict absent science keywords in the metadata. Our preliminary results indicate that the model has high levels of accuracy at predicting science keywords in the dataset metadata when exposed to data not included in its training. These predicted keywords were then evaluated by GES DISC data curation scientists and compared against other AI tools for metadata augmentation. We aim to enhance the overall usability and accessibility of NASA’s earth science data by implementing this tool in our data curation processes.

Kendall Gilbert↗

Self-Guided Multimedia Stress Management and Resilience Training for Flight Controllers

Stress and anxiety-related problems are among the most common and costly behavioral health problems in society, and for those working in operational environments (i.e. astronauts, flight controllers, military) this can seriously impact crew performance, safety, and wellbeing. Technology-based interventions are effective for treating behavioral health problems, and can significantly improve the delivery of evidence-based health care. This study is evaluating the effectiveness, usefulness, and usability of a self-guided multimedia stress management and resilience training program in a randomized controlled trial (RCT) with a sample of flight controllers at Johnson Space Center. The intervention, SMART-OP (Stress Management and Resilience Training for Optimal Performance), is a six-session, cognitive behavioral-based computer program that uses self-guided, interactive activities to teach skills that can help individuals build resilience and manage stress. In a prior RCT with a sample of stressed but otherwise healthy individuals, SMART-OP reduced perceived stress and increased perceived control over stress in comparison to an Attention Control (AC) group. SMART-OP was rated as "highly useful" and "excellent" in usability and acceptability. Based on α-amylase data, individuals in SMART-OP recovered quicker and more completely from a social stress test as compared to the AC group [1]. In the current study, flight controllers are randomized either to receive SMART-OP training, or to a 6-week waitlist control period (WLC) before beginning SMART-OP. Eligible participants include JSC flight controllers and instructors without any medical or psychiatric disorder, but who are stressed based on self-report. Flight controllers provide a valid analog sample to astronauts in that they work in an operational setting, use similar terminology to astronauts, are mission-focused, and work under the same broader work culture. The study began in December 2014, and to date 79 flight controllers and instructors have expressed interest in the study, 49 of those were cleared for participation, we have screened 44 for eligibility, and 23 have met inclusion criteria. Recruitment is ongoing and the study will continue until December 2016. Outcome measures include perceived stress, perceived control over stress, resilience, mood, personality, emotion regulation, sleep, health behaviors, and psychophysiological data such as 24-hour heart rate, alpha amylase, and urinary and salivary cortisol. We are also collecting user feedback such as usability, working alliance, usefulness, and treatment credibility.

Rose, R. D.↗

Crop, soil, and geological mapping from digitized multispectral satellite photography.

An experimental study was conducted of digitized multispectral satellite photography to seek answers to the following two questions: what are the data handling problems and requirements of converting photographic density measurements to a usable digital form, and what surface features can be distinguished using multispectral data taken at satellite altitudes. Results include the digitization of three multiband black and white photographs and a color infrared photograph, the conversion of the results of digitization to a useful digital form, and several data analysis experiments. As a whole, they encourage the use of multiband photography as a multispectral data collection instrument.

Anuta, P. E.↗

Cascaded convolutional codes

Due to the hardware design of Galileo's Command and Data Subsystem (CDS), the channel code usable in an S-band (2290-2300 MHz) mission must include the NASA standard (7,1/2) convolutional code. Galileo's hardware encoder for the (15,1/4) code is not usable in S-band mode. However, the need for higher coding gain dictates the use of long constraint length convolutional codes. Theoretical results show how a large subclass of such codes is realizable by using a software encoder in the CDS cascaded with the hardware encoder for the NASA standard code.

Pollara, F.↗

Planetary data analysis and display system: A version of PC-McIDAS

We propose to develop a system for access and analysis of planetary data from past and future space missions based on an existing system, the PC-McIDAS workstation. This system is now in use in the atmospheric science community for access to meteorological satellite and conventional weather data. The proposed system would be usable by not only planetary atmospheric researchers but also by the planetary geologic community. By providing the critical tools of an efficient system architecture, newer applications and customized user interfaces can be added by the end user within such a system.

Limaye, Sanjay S.↗

Planetary data analysis and display system: A version of PC-McIDAS

We propose to develop a system for access and analysis of planetary data from past and future space missions based on an existing system, the PC-McIDAS workstation. This system is now in use in the atmospheric science community for access to meteorological satellite and conventional weather data. The proposed system would be usable not only by planetary atmospheric researchers but also by the planetary geologic community. By providing the critical tools of an efficient system architecture, newer applications and customized user interfaces can be added by the end user within such a system.

Limaye, Sanjay S.↗

Tracking and Data Relay Satellite System (TDRSS) Support of User Spacecraft without TDRSS Transponders

NASA GSFC VNS TSG personnel have proposed the use of TDRSS to obtain telemetry and/or S-band one-way return Doppler tracking data for spacecraft which do not have TDRSS-compatible transponders and therefore were never considered candidates for TDRSS support. For spacecraft with less stable local oscillators (LO), one-way return Doppler tracking data is typically of poor quality. It has been demonstrated using UARS, WIND, and NOAA-J tracking data that the simultaneous use of two TDRSS spacecraft can yield differenced one-way return Doppler data of high quality which is usable for orbit determination by differencing away the effects of oscillator instability.

Jackson, James A.↗

Situational Lightning Climatologies for Central Florida, Phase 2, Part 3

The threat of lightning is a daily concern during the warm season in Florida. The forecasters at the Spaceflight Meteorology Group (SMG) at Johnson Spaceflight Center in Houston, TX consider lightning in their landing forecasts for space shuttles at the Kennedy Space Center (KSC), FL Shuttle Landing Facility (SLF). The forecasters at the National Weather Service in Melbourne, FL (NWS MLB) do the same in their routine Terminal Aerodrome Forecasts (TAFs) for seven airports in the NWS MLB County Warning Area (CWA). The Applied Meteorology Unit created flow regime climatologies of lightning probability in the 5-, 10-, 20-, and 30-n mi circles surrounding the Shuttle Landing Facility (SLF) and all airports in the NWS MLB county warning area in 1-, 3-, and 6-hour increments. The results were presented in tabular and graphical format and incorporated into a web-based graphical user interface so forecasters could easily navigate through the data and to make the GUI usable in any web browser on computers with different operating systems.

Bauman, William H., III↗

Evaluation of Technology Concepts for Energy, Automation, and System State Awareness in Commercial Airline Flight Decks

A pilot-in-the-loop flight simulation study was conducted at NASA Langley Research Center to evaluate flight deck systems that (1) provide guidance for recovery from low energy states and stalls, (2) present the current state and expected future state of automated systems, and/or (3) show the state of flight-critical data systems in use by automated systems and primary flight instruments. The study was conducted using 13 commercial airline crews from multiple airlines, paired by airline to minimize procedural effects. Scenarios spanned a range of complex conditions and several emulated causal and contributing factors found in recent accidents involving loss of state awareness by pilots (e.g., energy state, automation state, and/or system state). Three new technology concepts were evaluated while used in concert with current state-of-the-art flight deck systems and indicators. The technologies include a stall recovery guidance algorithm and display concept, an enhanced airspeed control indicator that shows when automation is no longer actively controlling airspeed, and enhanced synoptic pages designed to work with simplified interactive electronic checklists. An additional synoptic was developed to provide the flight crew with information about the effects of loss of flight critical data. Data was collected via questionnaires administered at the completion of flight scenarios, audio/video recordings, flight data, head and eye tracking data, pilot control inputs, and researcher observations. This paper presents findings derived from the questionnaire responses and subjective data measures including workload, situation awareness, usability, and acceptability as well as analyses of two low-energy flight events that resulted in near-stall conditions.

Kramer, Lynda J.↗

pyQuARC: Open Source Library for Earth Observation Metadata Quality Assessment

Metadata quality is essential to effective data discovery and has become increasingly vital as more Earth Science data sets become available. The Common Metadata Repository (CMR) hosts metadata describing NASA’s Earth Observation data products, which are archived across 12 Distributed Active Archive Centers (DAACs). The Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, conducts metadata quality assessments to ensure that these data products are discoverable, accessible, and usable. To achieve these goals, the ARC team has developed a metadata quality assessment framework to evaluate metadata completeness, correctness, and consistency. ARC uses a combination of manual and automated methods to assess these three components and identify areas of improvement; the team then collaborates with the DAACs to resolve any findings. To streamline this process, ARC is currently developing a host of scripts, known as pyQuARC, to automate metadata quality assessments as much as possible. pyQuARC is an open source library for Earth Observation Metadata Quality Assessment, and the tool utilizes ARC’s metadata quality assessment framework to make basic validation checks, pinpoint inconsistencies between dataset-level (i.e. collection) and file-level (i.e. granule) metadata, and identify opportunities for more descriptive and robust information. Since pyQuARC is also customizable, other users can make modifications as needed, and future metadata standards can also be implemented. Once pyQuARC is fully developed, it will support multiple schema types to serve the broader EOSDIS metadata community. This presentation will provide an overview of pyQuARC and its process of development while showcasing the tool’s valuable features and uses.

Jenny Wood↗