Results for “Data access” — Page 21

NASA NTRS2000

Upgrade of The Thermal Vacuum Data System at NASA/GSFC

The Goddard Space Flight Center's new thermal vacuum data acquisition system is a networked client-sever application that enables lab operations crews to monitor all tests from a central location. The GSFC thermal vacuum lab consists of eleven chambers in Building 7 and one chamber in Building 10. The new data system was implemented for several reasons. These included the need for centralized data collection, more flexible and easier to use operator interface, greater data accessibility, a reduction in testing time and cost, and increased payload and personnel safety. Additionally, a new data system was needed for year-2000 compliance. This paper discusses the incorporation of the Thermal Vacuum Data System (TVDS) within the thermal vacuum lab at GSFC, its features and capabilities and lessons learned in its implementation. Additional topics include off-center (Internet) capability for remote monitoring and the role of TVDS in the efforts to automate thermal vacuum chamber operations.

Palmer, John↗

NASA NTRS2017

Benchmark Shock Tube Experiments for Radiative Heating Relevant to Earth Re-Entry

Detailed spectrally and spatially resolved radiance has been measured in the Electric Arc Shock Tube (EAST) facility for conditions relevant to high speed entry into a variety of atmospheres, including Earth, Venus, Titan, Mars and the Outer Planets. The tests that measured radiation relevant for Earth re-entry are the focus of this work and are taken from campaigns 47, 50, 52 and 57. These tests covered conditions from 8 km/s to 15.5 km/s at initial pressures ranging from 0.05 Torr to 1 Torr, of which shots at 0.1 and 0.2 Torr are analyzed in this paper. These conditions cover a range of points of interest for potential fight missions, including return from Low Earth Orbit, the Moon and Mars. The large volume of testing available from EAST is useful for statistical analysis of radiation data, but is problematic for identifying representative experiments for performing detailed analysis. Therefore, the intent of this paper is to select a subset of benchmark test data that can be considered for further detailed study. These benchmark shots are intended to provide more accessible data sets for future code validation studies and facility-to-facility comparisons. The shots that have been selected as benchmark data are the ones in closest agreement to a line of best fit through all of the EAST results, whilst also showing the best experimental characteristics, such as test time and convergence to equilibrium. The EAST data are presented in different formats for analysis. These data include the spectral radiance at equilibrium, the spatial dependence of radiance over defined wavelength ranges and the mean non-equilibrium spectral radiance (so-called 'spectral non-equilibrium metric'). All the information needed to simulate each experimental trace, including free-stream conditions, shock time of arrival (i.e. x-t) relation, and the spectral and spatial resolution functions, are provided.

Shock Tube↗

NASA NTRS2021

NASA ARMD Wildfire Management Workshop

In response to the increasing severity and cost of wildfires in the United States, the NASA Aeronautics Research Mission Directorate (ARMD) conducted a one-day Wildfire Management Workshop on May 13, 2021. The NASA Aeronautics Research Institute (NARI) at the NASA Ames Research Center organized the event. The goal of the workshop was to provide a forum for representatives from wildfire organizations (government, private, and academic) to raise important issues and discuss solutions. The proceedings consisted of presentations from the U.S. Forest Service, NASA Space Technology Mission Directorate, and NASA Applied Sciences Disasters Program. Also included were two sessions of breakout groups that focused on specific wildfire management issues. Some major themes that emerged from the breakout groups included data access and management, wildfire modeling, improving organizational collaboration, the use of aircraft in fighting fires and collecting data, and providing front line firefighters with the information tools they need to be effective. The output of the workshop will be used by ARMD to consider avenues that NASA might take to help with wildfire management.

Wildfire Management↗

NASA NTRS2021

NASA ARMD Wildfire Management Workshop

In response to the increasing severity and cost of wildfires in the United States, the NASA Aeronautics Research Mission Directorate (ARMD) conducted a one-day Wildfire Management Workshop on May 13, 2021. The NASA Aeronautics Research Institute (NARI) at the NASA Ames Research Center organized the event. The goal of the workshop was to provide a forum for representatives from wildfire organizations (government, private, and academic) to raise important issues and discuss solutions. The proceedings consisted of presentations from the U.S. Forest Service, NASA Space Technology Mission Directorate, and NASA Applied Sciences Disasters Program. Also included were two sessions of breakout groups that focused on specific wildfire management issues. Some major themes that emerged from the breakout groups included data access and management, wildfire modeling, improving organizational collaboration, the use of aircraft in fighting fires and collecting data, and providing front line firefighters with the information tools they need to be effective. The output of the workshop will be used by ARMD to consider avenues that NASA might take to help with wildfire management.

Parimal Kopardekar↗

NASA NTRS2021

NASA ARMD Wildfire Management Workshop

In response to the increasing severity and cost of wildfires in the United States, the NASA Aeronautics Research Mission Directorate (ARMD) conducted a one-day Wildfire Management Workshop on May 13, 2021. The NASA Aeronautics Research Institute (NARI) at the NASA Ames Research Center organized the event. The goal of the workshop was to provide a forum for representatives from wildfire organizations (government, private, and academic) to raise important issues and discuss solutions. The proceedings consisted of presentations from the U.S. Forest Service, NASA Space Technology Mission Directorate, and NASA Applied Sciences Disasters Program. Also included were two sessions of breakout groups that focused on specific wildfire management issues. Some major themes that emerged from the breakout groups included data access and management, wildfire modeling, improving organizational collaboration, the use of aircraft in fighting fires and collecting data, and providing front line firefighters with the information tools they need to be effective. The output of the workshop will be used by ARMD to consider avenues that NASA might take to help with wildfire management.

Wildfire↗

DOE OSTI2023

ASC Data Science Infrastructure Project June 2023 [Slides]

Data Science Infrastructure (DSI) Project offers a standardized but flexible way of storing data and associated metadata to support AI/ML and data intensive scientific workflows: Establish requirements via use case interviews; Develop DSI framework to support flexible, secure, and accessible data stores tailored to researcher needs; Augment existing institutional frameworks for code management, performance testing and file indexing via automated DSI interfaces; Deploy DSI framework to support key use cases in collaboration with domain scientists.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1974

An algorithm for a general class of routing problems derived from Huygens' principle

If a set of N points or nodes with a nonnegative cost associated with each ordered pair is known, it is desired to find a path from one given node to another given node which minimizes the cost sum. An algorithm is presented which yields a global minimum solution after at most N - 1 iterations or on a typical large third-generation computer, after 1 hour of computation time for a 10,000-node problem. The rapid-access data storage capacity demanded by the algorithm is approximately 3N words for costs read in from slow-access storage or 2N words for calculable costs. The time-storage requirements of the algorithm known to the authors. When the problem is viewed as a discretized optimal control problem, after N-1 iterations, an optimal control or node transition is established for each of the N nodes or states; thus, the algorithm can be applied to situations were there may be errors in the control that necessitate a closed loop control that necessitate a closed loop control philosophy.

Avis, L. M.↗

NASA NTRS2008

Provenance in Data Interoperability for Multi-Sensor Intercomparison

As our inventory of Earth science data sets grows, the ability to compare, merge and fuse multiple datasets grows in importance. This requires a deeper data interoperability than we have now. Efforts such as Open Geospatial Consortium and OPeNDAP (Open-source Project for a Network Data Access Protocol) have broken down format barriers to interoperability; the next challenge is the semantic aspects of the data. Consider the issues when satellite data are merged, cross-calibrated, validated, inter-compared and fused. We must match up data sets that are related, yet different in significant ways: the phenomenon being measured, measurement technique, location in space-time or quality of the measurements. If subtle distinctions between similar measurements are not clear to the user, results can be meaningless or lead to an incorrect interpretation of the data. Most of these distinctions trace to how the data came to be: sensors, processing and quality assessment. For example, monthly averages of satellite-based aerosol measurements often show significant discrepancies, which might be due to differences in spatio- temporal aggregation, sampling issues, sensor biases, algorithm differences or calibration issues. Provenance information must be captured in a semantic framework that allows data inter-use tools to incorporate it and aid in the intervention of comparison or merged products. Semantic web technology allows us to encode our knowledge of measurement characteristics, phenomena measured, space-time representation, and data quality attributes in a well-structured, machine-readable ontology and rulesets. An analysis tool can use this knowledge to show users the provenance-related distrintions between two variables, advising on options for further data processing and analysis. An additional problem for workflows distributed across heterogeneous systems is retrieval and transport of provenance. Provenance may be either embedded within the data payload, or transmitted from server to client in an out-of-band mechanism. The out of band mechanism is more flexible in the richness of provenance information that can be accomodated, but it relies on a persistent framework and can be difficult for legacy clients to use. We are prototyping the embedded model, incorporating provenance within metadata objects in the data payload. Thus, it always remains with the data. The downside is a limit to the size of provenance metadata that we can include, an issue that will eventually need resolution to encompass the richness of provenance information required for daata intercomparison and merging.

Lynnes, Chris↗

NASA NTRS2015

Long-Term Global Aerosol Products from NASA Reanalysis MERRA-2 Available at GES DISC

Description of data access methods and showcases of aerosols from volcanic eruption, dust storm and wildfire available from Goddard Earth Science - Data and Information Services Center (GES-DISC).

data service↗

NASA NTRS2015

Managing Large Datasets for Atmospheric Research

Since the mid-1980s, airborne and ground measurements have been widely used to provide comprehensive characterization of atmospheric composition and processes. Field campaigns have generated a wealth of insitu data and have grown considerably over the years in terms of both the number of measured parameters and the data volume. This can largely be attributed to the rapid advances in instrument development and computing power. The users of field data may face a number of challenges spanning data access, understanding, and proper use in scientific analysis. This tutorial is designed to provide an introduction to using data sets, with a focus on airborne measurements, for atmospheric research. The first part of the tutorial provides an overview of airborne measurements and data discovery. This will be followed by a discussion on the understanding of airborne data files. An actual data file will be used to illustrate how data are reported, including the use of data flags to indicate missing data and limits of detection. Retrieving information from the file header will be discussed, which is essential to properly interpreting the data. Field measurements are typically reported as a function of sampling time, but different instruments often have different sampling intervals. To create a combined data set, the data merge process (interpolation of all data to a common time base) will be discussed in terms of the algorithm, data merge products available from airborne studies, and their application in research. Statistical treatment of missing data and data flagged for limit of detection will also be covered in this section. These basic data processing techniques are applicable to both airborne and ground-based observational data sets. Finally, the recently developed Toolsets for Airborne Data (TAD) will be introduced. TAD (tad.larc.nasa.gov) is an airborne data portal offering tools to create user defined merged data products with the capability to provide descriptive statistics and the option to treat measurement uncertainty.

Chen, Gao↗

NASA NTRS2017

NASA Update for Unidata Stratcomm

The NASA representative to the Unidata Strategic Committee presented a semiannual update on NASAs work with and use of Unidata technologies. The talk updated Unidata on the program of cloud computing prototypes underway for the Earth Observing System Data and Information System (EOSDIS). Also discussed was a trade study on the use of the Open source Project for a Network Data Access Protocol (OPeNDAP) with Web Object Storage in the cloud.

data systems↗

NASA NTRS2019

Reusability in NASA's Earth Observation System Data and Information System (EOSDIS)

NASA's Earth Observation System Data and Information System (EOSDIS) has been operational since 1994. The term FAIR is relatively recent compared to the operational life of EOSDIS. However, given the evolutionary nature of EOSDIS in response to both the state of the art and community expectations, it is useful to assess where EOSDIS stands relative to the FAIR data management. In this presentation we evaluate EOSDIS against the Reusability principle, which calls for a clear and accessible data usage license, rich description of data, detailed provenance, and compliance with domain-relevant community standards.Achieving consistent compliance for datasets is particularly challenging with the diverse community of missions and scientists providing data to EOSDIS. To address this, EOSDIS's constituent Distributed Active Archive Centers work with data producers to utilize the applicable standards and conventions. In addition, a guidebook is under development to provide comprehensive and understandable guidance on how to construct compliant, and thus more reusable, data products.

Hampapuram (Rama) Ramapriyan↗

DOE OSTI2022

POSTER: Automatic Differentiation of Parallel Loops with Formal Methods

The accompanying poster to this short paper presents a combination of reverse mode AD and formal methods to enable efficient differentiation of (or backpropagation through) shared-memory parallel code. Compared to the state of the art, our approach can more often avoid the need for atomic updates or private data copies during the parallel derivative computation, even in the presence of unstructured or data-dependent data access patterns. This is achieved by gathering information about the memory access patterns from the input program, which is assumed to be correctly parallelized. This information is then used to build a model of assertions in a theorem prover, which can be used to check the safety of shared memory accesses during the parallel derivative computation

Automatic Differentiation↗

DOE OSTI2022

Bias control for a memory device

Methods, systems, and devices for bias control for a memory device are described. A memory system may store indication of whether data is coherent. In some examples, the indication may be stored as metadata, where a first value indicates that the data is not coherent and a second value or a third value indicate that the data is coherent. When a processing unit or other component of the memory system processes a command to access data, the memory system may operate according to a device bias mode when the indication is the first value, and according to a host bias mode when the indication is the second value or the third value.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Bias control for a memory device

Methods, systems, and devices for bias control for a memory device are described. A memory system may store indication of whether data is coherent. In some examples, the indication may be stored as metadata, where a first value indicates that the data is not coherent and a second value or a third value indicate that the data is coherent. When a processing unit or other component of the memory system processes a command to access data, the memory system may operate according to a device bias mode when the indication is the first value, and according to a host bias mode when the indication is the second value or the third value.

Walker, Dean↗

NASA NTRS1989

A rapid prototyping/artificial intelligence approach to space station-era information management and access

Applications of rapid prototyping and Artificial Intelligence techniques to problems associated with Space Station-era information management systems are described. In particular, the work is centered on issues related to: (1) intelligent man-machine interfaces applied to scientific data user support, and (2) the requirement that intelligent information management systems (IIMS) be able to efficiently process metadata updates concerning types of data handled. The advanced IIMS represents functional capabilities driven almost entirely by the needs of potential users. Space Station-era scientific data projected to be generated is likely to be significantly greater than data currently processed and analyzed. Information about scientific data must be presented clearly, concisely, and with support features to allow users at all levels of expertise efficient and cost-effective data access. Additionally, mechanisms for allowing more efficient IIMS metadata update processes must be addressed. The work reported covers the following IIMS design aspects: IIMS data and metadata modeling, including the automatic updating of IIMS-contained metadata, IIMS user-system interface considerations, including significant problems associated with remote access, user profiles, and on-line tutorial capabilities, and development of an IIMS query and browse facility, including the capability to deal with spatial information. A working prototype has been developed and is being enhanced.

Carnahan, Richard S., Jr.↗

NASA NTRS2018

WebGeocalc and Cosmographia: Modern Tools to Access OPS SPICE Data

For more than two decades navigation and other ancillary data from most US and international planetary science missions have been packaged using "SPICE" (Spacecraft, Planet, Instrument, Camera-matrix, Events) system data files (a.k.a. SPICE kernels) and, in conjunction with SPICE Toolkit software used by scientists and engineers to compute observation geometry in various ground system tools ranging from mission planning and analysis applications to data production pipelines to science analysis tools. The traditional way for accessing SPICE data is by downloading necessary SPICE kernels to a user’s workstation, installing the SPICE Toolkit software available from NAIF, and writing an application calling APIs from the SPICE Toolkit library to compute numeric geometric parameters of interest. While this approach did and still does provide the greatest flexibility in implementing geometric computations of interest, it proved to be complicated for users with little programming abilities, required data to be always copied to the users’ workstations, and lacked any out-of-the-box visualization capabilities. To address these shortcomings NAIF developed the WebGeocalc (WGC) tool and extended the publicly available Cosmographia program to use SPICE. Employing these two new tools in mission operations enables easier access to SPICE computations and SPICE-based visualizations for a wider variety of mission personnel.

Semenov, Boris V.↗

DOE OSTI2023

Python package for machine-readable access to PDG data (PDG Python API) v0.1

This Python package implements a high-level interface to access the data published by the Particle Data Group (PDG) in the Review of Particle Physics (the "Review"). The Particle Data Group is an international collaboration led by the PDG group at LBNL. The PDG summarizes the established knowledge in the field of particle physics in a single publication, the Review of Particle Physics. The Review is published and updated online (see https://pdg.lbl.gov) each year, and published in a scientific journal every other year. It is currently licensed under a CC BY-NC 4.0 license. In 2021 PDG was designated by the Office of Science as a SC PuRe Data Resource. The Review is one of the most highly cited publications in the field of particle physics. The PDG Python API is part of PDG's efforts to make all data provided in the Review available in machine-readable format. This data includes the PDG world averages (or best limits) on particle masses, widths or lifetimes, branching fractions, magnetic moments, form factors, coupling constant ratios, and searches, as well as particle quantum numbers. It also includes detailed information on how PDG arrived at its averages, such as e.g. tables of published measurements with comments and footnotes, information on the consistency of published measurements, and detailed fit information.

Beringer, Juerg↗