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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Interpretable Deep Learning for the Earth System with Fractal Nets

Focal Area 3: Explainable AI Our confidence in the projections made by Earth System Models (ESMs) depends on understanding them to be, in some important respects, faithful representations of the Earth system. Here we present an “explainable Artificial Intelligence (AI)” method that allows us to uncover the dynamical structure of the observed and modeled Earth system, discover hidden links across wide spatiotemporal scales, target model development efforts at poorly-represented dynamics, and optimize observed or modeled data collection to maximize predictive information. Science Challenge: Dynamical system science for the Earth system poses unique challenges given the large degree of internal climate variability. Thus, tools that help us understand how ESMs succeed and fail at representing these dynamics are crucial, particularly in relation to the observed system. Furthermore, the computational and memory constraints on ESM data output motivate in situ analysis of ESM dynamics, including automatic detection of dynamical shifts. Also, of key importance are procedures that leverage ESMs to optimize observational campaigns for improving process representation, reducing structural uncertainty and improving model skill.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Optimization of knowledge-based systems and expert system building tools

The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

Yasuda, Phyllis↗
NASA NTRS1995

Data handling and visualization for NASA's science programs

Advanced information systems capabilities are essential to conducting NASA's scientific research mission. Access to these capabilities is no longer a luxury for a select few within the science community, but rather an absolute necessity for carrying out scientific investigations. The dependence on high performance computing and networking, as well as ready and expedient access to science data, metadata, and analysis tools is the fundamental underpinning for the entire research endeavor. At the same time, advances in the whole range of information technologies continues on an almost explosive growth path, reaching beyond the research community to affect the population as a whole. Capitalizing on and exploiting these advances are critical to the continued success of space science investigations. NASA must remain abreast of developments in the field and strike an appropriate balance between being a smart buyer and a direct investor in the technology which serves its unique requirements. Another key theme deals with the need for the space and computer science communities to collaborate as partners to more fully realize the potential of information technology in the space science research environment.

Bredekamp, Joseph H.↗
NASA NTRS1987

Animated computer graphics models of space and earth sciences data generated via the massively parallel processor

The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined.

Treinish, Lloyd A.↗
NASA NTRS2002

Key ingredients needed when building large data processing systems for scientists

Why is building a large science software system so painful? Weren't teams of software engineers supposed to make life easier for scientists? Does it sometimes feel as if it would be easier to write the million lines of code in Fortran 77 yourself? The cause of this dissatisfaction is that many of the needs of the science customer remain hidden in discussions with software engineers until after a system has already been built. In fact, many of the hidden needs of the science customer conflict with stated needs and are therefore very difficult to meet unless they are addressed from the outset in a system's architectural requirements. What's missing is the consideration of a small set of key software properties in initial agreements about the requirements, the design and the cost of the system.

Earth Observing System EOS↗
DOE OSTI2018

Toward a Multimodal-Deep Learning Retrieval System for Monitoring Nuclear Proliferation Activities

As the amount of available data increases, the human ability to locate, process, and analyze it is strained and eventually overwhelmed. To address this challenge for nonproliferation analysts, the authors have been creating a large-scale multimodal retrieval system to help analysts triage and search open source science, technology, and news data for indicators of nuclear proliferation capabilities and activities. The system relies on a set of deep neural networks (DNNs) trained to evaluate conceptual similarities across data modalities, such as text, image, and video. These DNNs can be used to search and prioritize data, according to a nuclear fuel cycle (NFC) process template, that are conceptually closest to the seed query items regardless of data modality. The DNNs have been trained to map conceptually related words, sentences, and images to nearby points in a multimodal feature space, enabling intra- and intermodal retrieval via nearest-neighbor calculations to seed query points. The authors evaluate the system’s ability to retrieve NFC-related data that have been purposely hidden in collections of unrelated background data. They demonstrate quantitative and qualitative results for text-to-image, image-to-image, and image-to-video retrievals. This paper discusses data challenges confronting nonproliferation analysts, describes the DNNs designed to retrieve multimodal data that are proximal in the semantic space, and demonstrates their effectiveness by applying the DNNs to nonproliferation-specific multimodal data sets.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

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.↗
NASA NTRS1993

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.↗
NASA NTRSDate not supplied

Examining 18 Years of Journal Publications to Characterize Usage Modes of Giovanni, a Versatile Earth Science Data Web Service

Introduction to Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) Giovanni … is a Web-based visualization and analysis system that provides 22 different visualization and analysis options, operating on thousands of Earth science data variables generated by satellite instrument observations and from related model datasets Giovanni … was originally conceived as a data exploration tool, but its ease-of-use, analytical capabilities (spatial and temporal subsetting, multi-period averaging, data mapping and time-series, and more) have led to its use as a multi-discipline research tool Giovanni … provided unprecedented access to NASA Earth science data for many different disciplines, AND is still providing a simple way to find, analyze, visualize, and utilize such data for a wide spectrum of research topics

James Acker↗
NASA NTRS1980

Nasa Program Plan

Major facts are given for NASA'S planned FY-1981 through FY-1985 programs in aeronautics, space science, space and terrestrial applications, energy technology, space technology, space transportation systems, space tracking and data systems, and construction of facilities. Competition and cooperation, reimbursable launchings, schedules and milestones, supporting research and technology, mission coverage, and required funding are considered. Tables and graphs summarize new initiatives, significant events, estimates of space shuttle flights, and major missions in astrophysics, planetary exploration, life sciences, environmental and resources observation, and solar terrestrial investigations. The growth in tracking and data systems capabilities is also depicted.

Source record↗
NASA NTRS1985

Pilot land data system

The full realization of the potential of satellite remote sensing would require the utilization of information systems which are currently not available. However, technological advances make it now possible to design a data system for meeting the land scientists' most critical information needs. A working group has been assembled to examine the need for a Pilot Data System (PLDS). The pilot program is to establish a limited-scale, distributed information system to explore approaches to satisfy the needs of the land science research community. Aspects and objectives considered by the working group are discussed, taking into account science scenarios, required functions, the characteristics of a land data system, and questions of pilot land data system development.

Estes, J. E.↗
DOE OSTI2022

Observational data from uncrewed systems over Southern Great Plains

Uncrewed Systems (UxS), including uncrewed aerial systems (UAS) and tethered balloon/kite systems (TBS), are significantly expanding observational capabilities in atmospheric science. Rapid adaptation of these platforms and the advancement of miniaturized instruments have resulted in an expanding number of data sets captured under various environmental conditions by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. In 2021, observational data collected using ARM UxS platforms, including seven TigerShark UAS flights and 133 tethered balloon system (TBS) flights, were archived by the ARM Data Center and made publicly available to the user community https://adc.arm.gov/discovery/#/results/s::sgp*U3 and https://adc.arm.gov/discovery/#/results/s::sgp*tbs. These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research. This manuscript describes the DOE UAS/TBS datasets, including information on the acquisition, collection, and quality control processes, and highlights the potential scientific contributions using UAS and TBS platforms.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Relevancy Ranking of Satellite Dataset Search Results

As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

science data management↗
NASA NTRS1996

Development of Secondary Archive System at Goddard Space Flight Center Version 0 Distributed Active Archive Center

The Goddard Space Flight Center (GSFC) version 0 Distributed Active Archive Center (DAAC) has been developed to support existing and pre Earth Observing System (EOS) Earth science datasets, facilitate the scientific research, and test EOS data and information system (EOSDIS) concepts. To ensure that no data is ever lost, each product received at GSFC DAAC is archived on two different media, VHS and digital linear tape (DLT). The first copy is made on VHS tape and is under the control of UniTree. The second and third copies are made to DLT and VHS media under a custom built software package named 'Archer'. While Archer provides only a subset of the functions available with commercial software like UniTree, it supports migration between near-line and off-line media and offers much greater performance and flexibility to satisfy the specific needs of a data center. Archer is specifically designed to maximize total system throughput, rather than focusing on the turn-around time for individual files. The commercial off the shelf software (COTS) hierarchical storage management (HSM) products evaluated were mainly concerned with transparent, interactive, file access to the end-user, rather than a batch-orientated, optimizable (based on known data file characteristics) data archive and retrieval system. This is critical to the distribution requirements of the GSFC DAAC where orders for 5000 or more files at a time are received. Archer has the ability to queue many thousands of file requests and to sort these requests into internal processing schedules that optimize overall throughput. Specifically, mount and dismount, tape load and unload cycles, and tape motion are minimized. This feature did not seem to be available in many COTS pacages. Archer also uses a generic tar tape format that allows tapes to be read by many different systems rather than the proprietary format found in most COTS packages. This paper discusses some of the specific requirements at GSFC DAAC, the motivations for implementing the Archer system, and presents a discussion of the Archer design that resulted.

Sherman, Mark↗
NASA NTRS2006

A Multi-mission Event-Driven Component-Based System for Support of Flight Software Development, ATLO, and Operations first used by the Mars Science Laboratory (MSL) Project

This viewgraph presentation reviews the architectural description of the Mission Data Processing and Control System (MPCS). MPCS is an event-driven, multi-mission ground data processing components providing uplink, downlink, and data management capabilities which will support the Mars Science Laboratory (MSL) project as its first target mission. MPCS is designed with these factors (1) Enabling plug and play architecture (2) MPCS has strong inheritance from GDS components that have been developed for other Flight Projects (MER, MRO, DAWN, MSAP), and are currently being used in operations and ATLO, and (3) MPCS components are Java-based, platform independent, and are designed to consume and produce XML-formatted data

Mission Data Processing and Control System (MPCS)↗
DOE OSTI2020

High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region

In 2019, highway congestion wasted over 3 billion gallons of fuel and caused 8.8 billion hours of lost productivity.1 Research has shown that introducing near-real time traffic controls can significantly reduce congestion. Validated and calibrated traffic simulations enable the modeling of transportation systems and the evaluation of different traffic control actions and schemes given a variety of circumstances that represent likely future scenarios. The developed scenarios can inform the deployment of controls in near real-time to improve freight and passenger vehicle congestion and energy use. In this work, we present simulations used to model the traffic in the Chattanooga, Tennessee, metropolitan area. Simulations were constructed and calibrated using a variety of local, data science enhanced, data sources utilizing open source software including the Simulation of Urban Mobility (SUMO) simulator. High-Performance Computing (HPC) provides a scalable platform with enough computing for the high-fidelity simulation of many scenarios and the application of advance data science especially for large-scale systems. Our simulations include microscopic simulations at a corridor level for traffic signal control, and mesoscopic simulations to evaluate regional operational controls and infrastructure.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Carbon Dioxide Observational Platform System (CO-OPS), feasibility study

The Carbon Dioxide Observational Platform System (CO-OPS) is a near-space, geostationary, multi-user, unmanned microwave powered monitoring platform system. This systems engineering feasibility study addressed identified existing requirements such as: carbon dioxide observational data requirements, communications requirements, and eye-in-the-sky requirements of other groups like the Defense Department, the Forestry Service, and the Coast Guard. In addition, potential applications in: earth system science, space system sciences, and test and verification (satellite sensors and data management techniques) were considered. The eleven month effort is summarized. Past work and methods of gathering the required observational data were assessed and rough-order-of magnitude cost estimates have shown the CO-OPS system to be most cost effective (less than $30 million within a 10 year lifetime). It was also concluded that there are no technical, schedule, or obstacles that would prevent achieving the objectives of the total 5-year CO-OPS program.

Bouquet, D. L.↗