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NASA NTRS2011

The New Web-Based Hera Data Processing System at the HEASARC

The HEASARC at NASA/GSFC has provide an on-line astronomical data processing system called Hera for several years. Hera provides a complete data processing environment, including installed software packages, local data storage, and the CPU resources needed to process the user's data. The original design of Hera, however, has 2 requirements that has limited it's usefulness for some users, namely, that 1) the user must download and install a small helper program on their own computer before using Hera, and 2) Hera requires that several computer ports/sockets be allowed to communicate through any local firewalls on the users machine. Both of these restrictions can be problematic for some users, therefore we are now migrating Hera into a purely Web based environment which only requires a standard Web browser. The first release of Web Hera is now publicly available at http://heasarc.gsfc.nasa.gov/webheara/. It currently provides a standard graphical interface for running hundreds of different data processing programs that are available in the HEASARC's ftools software package. Over the next year we to add more features to Web Hera, including an interactive command line interface, and more display and line capabilities.

Pence, W.↗

NASA NTRS2014

The Fleet Application for Scheduling and Tracking (FAST) Management Website

The FAST application was designed to replace the paper and pen method of checking out and checking in GSA Vehicles at KSC. By innovating from a paper and pen based checkout system to a fully digital one, not only the resources wasted by printing the checkout forms have been reduced, but it also reduces significantly the time that users and fleet managers need to interact with the system as well as improving the record accuracy for each vehicle. The vehicle information is pulled from a centralized database server in the SPSDL. In an attempt to add a new feature to the FAST application, the author of this report (alongside the FAST developers) has been designing and developing the FAST Management Website. The GSA fleet managers had to rely on the FAST developers in order to add new vehicles, edit vehicles and previous transactions, or for generating vehicles reports. By providing an easy-to-use FAST Management Website portal, the GSA fleet managers are now able to easily move vehicles, edit records, and print reports.

Object-Oriented Programming↗

NASA NTRS2014

Proto-Examples of Data Access and Visualization Components of a Potential Cloud-Based GEOSS-AI System

Once a research or application problem has been identified, one logical next step is to search for available relevant data products. Thus, an early component of a potential GEOSS-AI system, in the continuum between observations and end point research, applications, and decision making, would be one that enables transparent data discovery and access by users. Such a component might be effected via the systems data agents. Presumably, some kind of data cataloging has already been implemented, e.g., in the GEOSS Common Infrastructure (GCI). Both the agents and cataloging could also leverage existing resources external to the system. The system would have some means to accept and integrate user-contributed agents. The need or desirability for some data format internal to the system should be evaluated. Another early component would be one that facilitates browsing visualization of the data, as well as some basic analyses.Three ongoing projects at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provide possible proto-examples of potential data access and visualization components of a cloud-based GEOSS-AI system. 1. Reorganizing data archived as time-step arrays to point-time series (data rods), as well as leveraging the NASA Simple Subset Wizard (SSW), to significantly increase the number of data products available, at multiple NASA data centers, for production as on-the-fly (virtual) data rods. SSWs data discovery is based on OpenSearch. Both pre-generated and virtual data rods are accessible via Web services. 2. Developing Web Feature Services to publish the metadata, and expose the locations, of pre-generated and virtual data rods in the GEOSS Portal and enable direct access of the data via Web services. SSW is also leveraged to increase the availability of both NASA and non-NASA data.3.Federating NASA Giovanni (Geospatial Interactive Online Visualization and Analysis Interface), for multi-sensor data exploration, that would allow each cooperating data center, currently the NASA Distributed Active Archive Centers (DAACs), to configure its own Giovanni deployment, while also allowing all the deployments to incorporate each others data. A federated Giovanni comprises Giovanni Virtual Machines, which can be run on local servers or in the cloud.

access↗

NASA NTRS2017

Understanding the International Space Station Crew Perspective following Long-Duration Missions through Data Analytics & Visualization of Crew Feedback

The International Space Station (ISS) first became a home and research laboratory for NASA and International Partner crewmembers over 16 years ago. Each ISS mission lasts approximately 6 months and consists of three to six crewmembers. After returning to Earth, most crewmembers participate in an extensive series of 30+ debriefs intended to further understand life onboard ISS and allow crews to reflect on their experiences. Examples of debrief data collected include ISS crew feedback about sleep, dining, payload science, scheduling and time planning, health & safety, and maintenance. The Flight Crew Integration (FCI) Operational Habitability (OpsHab) team, based at Johnson Space Center (JSC), is a small group of Human Factors engineers and one stenographer that has worked collaboratively with the NASA Astronaut office and ISS Program to collect, maintain, disseminate and analyze this data. The database provides an exceptional and unique resource for understanding the "crew perspective" on long duration space missions. Data is formatted and categorized to allow for ease of search, reporting, and ultimately trending, in order to understand lessons learned, recurring issues and efficiencies gained over time. Recently, the FCI OpsHab team began collaborating with the NASA JSC Knowledge Management team to provide analytical analysis and visualization of these over 75,000 crew comments in order to better ascertain the crew's perspective on long duration spaceflight and gain insight on changes over time. In this initial phase of study, a text mining framework was used to cluster similar comments and develop measures of similarity useful for identifying relevant topics affecting crew health or performance, locating similar comments when a particular issue or item of operational interest is identified, and providing search capabilities to identify information pertinent to future spaceflight systems and processes for things like procedure development and training. In addition, the comments were scored for sentiment using a polarity scoring algorithm to identify both positive and negative comments for particular groups and clusters, allowing the team to make analytically informed decisions regarding future hardware and operating procedures. The use of polarity scoring with time series analysis was used to provide insight into how crew health and habitability is changing throughout various spaceflight increments or the station lifecycle as a whole. Finally, a visualization framework was developed to address the needs of the end users to search for and analyze comments by user, category or mission. This paper will discuss how the use of an analytical framework in conjunction with the current human interface, improved the understanding of crew perspective and shortened the time for analysis allowing for more informed decisions and rapid development of improvements. These methods are significantly optimizing the way that this valuable data can be assessed and applied to current and future spaceflight design and development. This collaboration allows the FCI OpsHab team to effectively analyze and share data in a more automated and timely fashion. Trends are no longer derived manually and can be illustrated effectively and accurately with these evolving techniques to an ever growing group of human spaceflight end users.

Bryant, Cody↗

NASA NTRS2016

High Data Rate Architecture (HiDRA)

One of the greatest challenges in developing new space technology is in navigating the transition from ground based laboratory demonstration at Technology Readiness Level 6 (TRL-6) to conducting a prototype demonstration in space (TRL-7). This challenge is com- pounded by the relatively low availability of new spacecraft missions when compared with aeronautical craft to bridge this gap, leading to the general adoption of a low-risk stance by mission management to accept new, unproven technologies into the system. Also in consideration of risk, the limited selection and availability of proven space-grade components imparts a severe limitation on achieving high performance systems by current terrestrial technology standards. Finally from a space communications point of view the long duration characteristic of most missions imparts a major constraint on the entire space and ground network architecture, since any new technologies introduced into the system would have to be compliant with the duration of the currently deployed operational technologies, and in some cases may be limited by surrounding legacy capabilities. Beyond ensuring that the new technology is verified to function correctly and validated to meet the needs of the end users the formidable challenge then grows to additionally include: carefully timing the maturity path of the new technology to coincide with a feasible and accepting future mission so it flies before its relevancy has passed, utilizing a limited catalog of available components to their maximum potential to create meaningful and unprecedented new capabilities, designing and ensuring interoperability with aging space and ground infrastructures while simultaneously providing a growth path to the future. The International Space Station (ISS) is approaching 20 years of age. To keep the ISS relevant, technology upgrades are continuously taking place. Regarding communications, the state-of-the-art communication system upgrades underway include high-rate laser terminals. These must interface with the existing, aging data infrastructure. The High Data Rate Architecture (HiDRA) project is designed to provide networked store, carry, and forward capability to optimize data flow through both the existing radio frequency (RF) and new laser communications terminal. The networking capability is realized through the Delay Tolerant Networking (DTN) protocol, and is used for scheduling data movement as well as optimizing the performance of existing RF channels. HiDRA is realized as a distributed FPGA memory and interface controller that is itself controlled by a local computer running DTN software. Thus HiDRA is applicable to other arenas seeking to employ next-generation communications technologies, e.g. deep space. In this paper, we describe HiDRA and its far-reaching research implications.

DTN↗

NASA NTRS2017

An Unobtrusive System to Measure, Assess, and Predict Cognitive Workload in Real-World Environments

Across many careers, individuals face alternating periods of high and low attention and cognitive workload, which can result in impaired cognitive functioning and can be detrimental to job performance. For example, some professions (e.g., fire fighters, emergency medical personnel, doctors and nurses working in an emergency room, pilots) require long periods of low workload (boredom), followed by sudden, high-tempo operations during which they may be required to respond to an emergency and perform at peak cognitive levels. Conversely, other professions (e.g., air traffic controllers, market investors in financial industries, analysts) require long periods of high workload and multitasking during which the addition of just one more task results in cognitive overload resulting in mistakes. An unobtrusive system to measure, assess, and predict cognitive workload could warn individuals, their teammates, or their supervisors when steps should be taken to augment cognitive readiness. In this talk I will describe an approach to this problem that we have found to be successful across work domains including: (1) a suite of unobtrusive, field-ready neurophysiological, physiological, and behavioral sensors that are chosen to best suit the target environment; (2) custom algorithms and statistical techniques to process and time-align raw data originating from the sensor suite; (3) probabilistic and statistical models designed to interpret the data into the human state of interest (e.g., cognitive workload, attention, fatigue); (4) and machine-learning techniques to predict upcoming performance based on the current pattern of events, and (5) display of each piece of information depending on the needs of the target user who may or may not want to drill down into the functioning of the system to determine how conclusions about human state and performance are determined. I will then focus in on our experimental results from our custom functional near-infrared spectroscopy sensor, designed to operate in real-world environments to be worn comfortably (e.g., positioned into a baseball cap or a surgeons cap) to measure changes in brain blood oxygenation without adding burden to the individual being assessed.

workload collection↗

NASA NTRS2017

The NASA Wallops Arc-Second Pointer (WASP) System for Precision Pointing of Scientific Balloon Instruments and Telescopes

The National Aeronautics and Space Administrations (NASA) Wallops Flight Facility (WFF), part of the Goddard Space Flight Center (GSFC), has developed a unique pointing control system for instruments aboard scientific balloon gondolas. The ability to point large telescopes and instruments with arc-second accuracy and stability is highly desired by multiple scientific disciplines, such as Planetary, Earth Science, Heliospheric and Astrophysics, and the availability of a standardized system supplied by NASA alleviates the need for the science user to develop and provide their own system. In addition to the pointing control system, a star tracker has been developed with both daytime and nighttime capability to augment the WASP and provide an absolute pointing reference. The WASP Project has successfully completed five test flights and one operational science mission, and is currently supporting an additional test flight in 2017, along with three science missions with flights scheduled between 2018 and 2020. The WASP system has demonstrated precision pointing and high reliability, and is available to support scientific balloon missions.

WASP↗

NASA NTRS2018

Prioritizing Aquatic Science and Applications Needs in the Chesapeake Bay for a Space-Borne Hyperspectral Mission

The Chesapeake Bay is the largest estuary in North America, benefiting a growing population through its ecosystem services, fishing, recreations, and transportation routes. Studies indicate the health of the Bay as seen some improvement in recent years, yet threats to its health persist (e.g. warming, pollution nutrient run-off). Increasing human activities in coastal regions requires constant vigilance by agencies managing water quality, to ensure the safety of the population. Since April 2018, an interagency working group has been meeting monthly and a daylong workshop was convened with science and applications stakeholders around the overall theme of monitoring water quality from space. Current ocean color images indicate bloom locations used to guide in situ sampling efforts, despite limited spatial, spectral and temporal resolution. High resolution hyperspectral remote sensing provides a potential opportunity to measure additional indicators of ecological health and water quality. Assessing the needs of the aquatic user community around the Chesapeake Bay will inform science and applications recommendations during the current architecture study for a Surface Biology and Geology (SBG) Mission, as well as future scoping studies of other coastal and inland water bodies.

Schollaert Uz, Stephanie↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

Dynamic Channel Assignments for Efficient Use of Aviation Spectrum Allocations

The demand for voice and data communications continues to rise with the emergence of new aerial vehicles into the airspace and the continued growth of aviation operations throughout the National Airspace System (NAS). Recent studies have shown that the anticipated growing demand for spectrum resources will exceed the capacity of existing aviation spectrum allocations. Further, airspace configurations, via assignment of fixed channel allocations within standard service volumes, do not allow for the dynamic and efficient distribution of spectrum resources based on airspace demand; as a result, a new approach to aviation spectrum management is needed to support the forecasted needs of new airspace users. The National Aeronautics and Space Administration (NASA) is investigating applications of artificial intelligence (AI), machine learning (ML), and other advanced concepts to solve a dynamic constraint satisfaction problem which is analogous to the frequency assignment problem faced by aviation. Procedures and strategies for dynamic channel allocation can be borrowed from other large-scale mobile services (i.e., 4G/5G applications) and can provide a novel spectrum management approach that allows for the intelligent utilization of aviation spectrum throughout the airspace while maintaining the strict quality of service prescribed by aeronautical standards.

Communications↗

NASA NTRSDate not supplied

Dynamic Channel Assignments for Efficient Use of Aviation Spectrum Allocations

communications↗

NASA NTRSDate not supplied

End-User Engagement to Understand NRT and Low Latency EO Data Needs

Explore the source record for details and available documents.

Rachel Soobitsky↗

NASA NTRSDate not supplied

NASA SPoRT’s Streamflow-AI: Updates and Advancements

The NASA Short-term Prediction Research and Transition Center (SPoRT) has been running a near-real-time deep learning model, Streamflow-AI, that predicts stream heights at over 250 locations across the Eastern United States out to 7 days for several years. This project was born out of a research-to-operations/operation-to-research (R2O/O2R) paradigm within SPoRT through extensive collaboration with National Weather Service (NWS) and River Forecast Center (RFC) forecasters. The original intention of Streamflow-AI was to provide accurate medium range (>2 days) forecasts of river flooding events that are particularly challenging for NWS forecasters, because routine streamflow forecasts may not incorporate quantitative precipitation forecast (QPF) data beyond one or two days. Therefore, Streamflow-AI was designed to help fill the operational gap, producing routine 7 day river level forecasts using a suite of QPFs. Throughout the evolution of the project, research efforts have been tailored to meet the needs of the end users. This presentation will provide a brief overview of NASA SPoRT’s Streamflow-AI product, highlighting O2R/R2O concepts with a focus on recent developments including a 1-hr rapid update model and 15-min burn scar flooding modeling efforts.

Flooding↗

NASA NTRS2016

SIG: Multiple Views on Safety-Critical Automation: Aircraft, Autonomous Vehicles, Air Traffic Management and Satellite Ground Segments Perspectives

This SIG focuses on the engineering of automation in interactive critical systems. Automation has already been studied in a number of (sub-) disciplines and application fields: design, human factors, psychology, (software) engineering, aviation, health care, games. One distinguishing feature of the area we are focusing on is that in the field of interactive critical systems properties such as reliability, dependability, fault tolerance are as important as usability, user experience or overall acceptance issues. The SIG targets at two problem areas: first the engineering of the user interaction with (partly-) autonomous systems: how to design, build and assess autonomous behavior, especially in cases where there is a need to represent on the user interface both autonomous and interactive objects. An example of such integration is the representation of an unmanned aerial vehicle (UAV) (where no direct interaction is possible), together with aircrafts (that have to be instructed by an air traffic controller to avoid the UAV). Second the design and engineering of user interaction in general for autonomous objects/systems (for example a cruise control in a car or an autopilot in an aircraft). The goal of the SIG is to raise interest in the CHI community on the general aspects of automation and to identify a community of researchers and practitioners interested in those increasingly prominent issues of interfaces towards (semi)-autonomous systems. The expected audience should be interested in addressing the issues of integration of mainly unconnected research domains to formulate a new joint research agenda.

human-automation interaction↗

NASA NTRS2016

Multiple Views on Safety-Critical Automation: Aircraft, Autonomous Vehicles, Air Traffic Management and Satellite Ground Segments Perspectives

This SIG focuses on the engineering of automation in interactive critical systems. Automation has already been studied in a number of (sub-) disciplines and application fields: design, human factors, psychology, (software) engineering, aviation, health care, games. One distinguishing feature of the area we are focusing on is that in the field of interactive critical systems properties such as reliability, dependability, fault-tolerance are as important as usability, user experience or overall acceptance issues. The SIG targets at two problem areas: first the engineering of the user interaction with (partly-) autonomous systems: how to design, build and assess autonomous behavior, especially in cases where there is a need to represent on the user interface both autonomous and interactive objects. An example of such integration is the representation of an unmanned aerial vehicle (UAV) (where no direct interaction is possible), together with aircrafts (that have to be instructed by an air traffic controller to avoid the UAV). Second the design and engineering of user interaction in general for autonomous objects systems (for example a cruise control in a car or an autopilot in an aircraft). The goal of the SIG is to raise interest in the CHI community on the general aspects of automation and to identify a community of researchers and practitioners interested in those increasingly prominent issues of interfaces towards (semi)-autonomous systems. The expected audience should be interested in addressing the issues of integration of mainly unconnected research domains to formulate a new joint research agenda.

safety-critical automation↗

NASA NTRS2008

Moving Away from Ones and Zeros, Designing a Ground Data System Based on Higher Levels of Abstraction

Previous JPL ground systems have been designed with the Ground Data System (GDS) engineer in mind. The focus on these systems has been on packaging and delivery of low level information (frames, packets, telemetry values) to the end user. It was not that long ago when project teams would be huddled over a workstation, examining crude displays of telemetry bits organized in various ways, trying to determine the status of a spacecraft. Understanding the data often required additional levels of GDS expertise, or worse, transformation of the raw data into alternative formats followed by ingestion into other tools so that the data became meaningful. The primary focus was often to answer these types of questions: "Why did this particular frame fail Reed-Solomon decode? Why did this packet get marked as invalid? Why am I missing a block of telemetry from my query?" -- which are completely valid questions to ask from a GDS Engineer's point of view, and large families of tools have been designed to help answer these questions. But these are not the questions that most users care about - which are more like: "Why is the battery state of charge trending down? Show me a summary image report for the last traverse to the target. Show me a data accountability summary for the last DSN pass." Answers to these questions, which are what users are looking for, requires a higher level of abstraction and supporting tools than mining through ones and zeros. JPL has created a next generation capability called the Mission Data Processing and Control System (MPCS) which is designed to support this higher level of abstraction by providing customizable views of the ground system combining collections of lower level information into more meaningful ways. Instead of examining frames, packets, and individual telemetry data points -- MPCS is capable of providing comprehensive summary reports, product status, overall flight/ground event status, as well as payload health summaries. Based on these higher level views, end users can make tactical or strategic decisions, or drop into detailed analysis as needed. System designers need to continue building systems that support low level GDS troubleshooting - but the basic design of a GDS should be geared towards what end users actually need to see. This paper will describe the capabilities of MPCS that directly support these higher levels of abstraction, and which are being used today in missions such as the Mars Science Laboratory and other NASA missions.

MPCS↗

NASA NTRS1982

The evolution of a Ku-Band satellite network

The purpose of this study was to undertake the management and development of CTS terminals and time on appropriate Ku-Band satellites was procured. A community of public service users who have readily addressable needs and resources to pay for services on an ad hoc Ku-Band network was developed and a test network for selected users was managed.

Bransford, L. A.↗

NASA NTRS1999

I/O Parallelization for the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center (GSFC) has developed the GEOS DAS, a data assimilation system that provides production support for NASA missions and will support NASA's Earth Observing System (EOS) in the coming years. The DAO's support of the EOS project along with the requirement of producing long-term reanalysis datasets with an unvarying system levy a large I/O burden on the future system. The DAO has been involved in prototyping parallel implementations of the GEOS DAS for a number of years and is now converting the production version from shared-memory parallelism to distributed-memory parallelism using the portable Message-Passing Interface (MPI). If the MPI-based GEOS DAS is to meet these production requirements, we must make I/O from the parallel system efficient. We have designed a scheme that allows efficient I/O processing while retaining portability, reducing the need for post-processing, and producing data formats that are required by our users, both internal and external. The first phase of the GEOS DAS Parallel I/O System (GPIOS) will expand upon the common method of gathering global data to a Single PE for output. Instead of using a PE also tasked with primary computation, a number of PEs will be dedicated to I/O and its related tasks. This allows the data transformations and formatting required prior to output to take place asynchronously with respect to the GEOS DAS assimilation cycle, improving performance and generating output data sets in a format convenient for our users. I/O PEs can be added as needed to handle larger data volumes or to meet user file specifications. We will show I/O performance results from a prototype MPI GCM integrated with GPIOS. Phase two of GPIOS development will examine ways of integrating new software technologies to further improve performance and build scalability into the system. The maturing of MPI-IO implementations and other supporting libraries such as parallel HDF should provide performance gains while retaining portability.

Lucchesi, R.↗