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At least 595 records · Page 33

TPSAS-NF1676L-35698-DND

The NASA Langley Atmospheric Science Data Center (ASDC) is using the Esri ArcGIS Platform to improve data discoverability, accessibility and interoperability to meet their diversified userbase. As a NASA Distributed Active Archive Center (DAAC), ASDC is actively working to provide their atmospheric datasets as ArcGIS Image Services by leveraging the ArcGIS multidimensional suite of tools. This presentation will provide a brief overview of the ArcGIS Platform implementation at ASDC, an overview of the ArcGIS collaboration occurring among DAACs, as well as NASA Earth Science data application with partnering projects like the Prediction Of Worldwide Energy Resources (POWER).

Matthew Tisdale↗

Communications among data and science centers

The ability to electronically access and query the contents of remote computer archives is of singular importance in space and earth sciences; the present evaluation of such on-line information networks' development status foresees swift expansion of their data capabilities and complexity, in view of the volumes of data that will continue to be generated by NASA missions. The U.S.'s National Space Science Data Center (NSSDC) manages NASA's largest science computer network, the Space Physics Analysis Network; a comprehensive account is given of the structure of NSSDC international access through BITNET, and of connections to the NSSDC available in the Americas via the International X.25 network.

Green, James L.↗

Laboratory For Atmospheres 1996 Annual Report

A broad and vigorous science program in NASA is vital for the advancement of knowledge through space research.Scientists at NASA in collaboration with outside scientists play a key role in conceiving new space missions, providing mission requirements, and carrying out research oriented towards explaining the behavior of Earth's and other planetary systems. NASA scientists also supply outside scientists with technical assistance and scientific data.The Laboratory for Atmospheres serves as the focal point of a broad theoretical and experimental research program. The goal of the program is to study all aspects of the atmospheres of the Earth and other planets, including their structural, dynamical, radiative, and chemical properties. The Laboratory is one of four science laboratories of the at the Goddard Space Flight Center (GSFC). The Laboratory is located in Greenbelt, MD along with the and the. , located in New York, NY, is the fourth science Laboratory in the Directorate. The Directorate also includes the Global Change Data Center and the Space Data and Computing Division (SDCD). The GSFC is the lead center for science and management of the, which is one of the four NASA enterprises. Earth Sciences Directorate Laboratory for Terrestrial Physics Laboratory for Hydrospheric Processes The Goddard Institute for Space Studies (GISS) Mission to Planet Earth (MTPE)This report is a general statement of the purpose and philosophy of the Laboratory and of its role within NASA. It also includes a broad description of the research areas; information on human resources, scientific interactions, and outreach activities with the outside community; and a selection of the major accomplishments achieved in the Laboratory in calendar year 1996.

Steven E. Platnick↗

Mass storage system experiences and future needs at the National Center for Atmospheric Research

A summary and viewgraphs of a discussion presented at the National Space Science Data Center (NSSDC) Mass Storage Workshop is included. Some of the experiences of the Scientific Computing Division at the National Center for Atmospheric Research (NCAR) dealing the the 'data problem' are discussed. A brief history and a development of some basic mass storage system (MSS) principles are given. An attempt is made to show how these principles apply to the integration of various components into NCAR's MSS. Future MSS needs for future computing environments is discussed.

Olear, Bernard T.↗

RCSB Protein Data Bank: Celebrating 50 years of the PDB with new tools for understanding and visualizing biological macromolecules in 3D

We report the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the US National Science Foundation, National Institutes of Health, and Department of Energy, has served structural biologists and Protein Data Bank (PDB) data consumers worldwide since 1999. RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, is the US data center for the global PDB archive housing biomolecular structure data. RCSB PDB is also responsible for the security of PDB data, as the wwPDB-designated Archive Keeper. Annually, RCSB PDB serves tens of thousands of three-dimensional (3D) macromolecular structure data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) from all inhabited continents. RCSB PDB makes PDB data available from its research-focused RCSB.org web portal at no charge and without usage restrictions to millions of PDB data consumers working in every nation and territory worldwide. In addition, RCSB PDB operates an outreach and education PDB101.RCSB.org web portal that was used by more than 800,000 educators, students, and members of the public during calendar year 2020. This invited Tools Issue contribution describes (i) how the archive is growing and evolving as new experimental methods generate ever larger and more complex biomolecular structures; (ii) the importance of data standards and data remediation in effective management of the archive and facile integration with more than 50 external data resources; and (iii) new tools and features for 3D structure analysis and visualization made available during the past year via the RCSB.org web portal.

59 BASIC BIOLOGICAL SCIENCES↗

VoroClust

SAND2025-11465O VoroClust, also known as Voronoi Clustering, is a fast, density-based unsupervised clustering algorithm applicable to high-resolution and high-dimensional data. It operates as quickly as distance-based clustering methods while effectively capturing complex regional geometries, matching the performance of current density-based methods. VoroClust employs a data-centered sphere cover to reduce computational demands while preserving data topology. It propagates clusters outward from local density peaks. Although supervised machine learning is powerful for applications like image classification and segmentation, it requires comprehensive, consistent datasets, which many applications lack. Unsupervised clustering algorithms analyze the structure of each dataset rather than relying on similarities with other examples, making them well-suited for practical applications with insufficient or inappropriate data for supervised learning. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Ebeida, Mohamed [Sandia National Lab. (SNL-CA), Li↗

Imaging data

The primary, planetary imaging data base includes all images obtained in visible wavelengths by imaging camera systems aboard planetary spacecraft. (Excluded, due to the volume and complexity of the data, are images taken from Lunar or Earth orbital spacecraft). These estimated 145,000 individual images exist on 12,400 magnetic tapes in a digital format primarily as Experiment Data Records (EDRs); and most are accompanied by the Supplementary Experiment Data Records (SEDRs), which render the EDRs useful. Hardcopy pictures and negatives, the designated archive products for imaging experiments, along with color products and mosaics are maintained at the National space Science Data Center (NSSDC). Also included in the discussion of imaging data are two-dimensional data produced by spacecraft instruments other than optical sensors which may be considered images in a broad sense. Examples of these instruments are imaging radar systems, scanning infrared radiometers, and photopolarimeters.

Source record↗

Solar-geophysical data number 499, March 1986, supplement

This supplement contains the description and explanation of the data in the monthly publication Solar-Geophysical Data, compiled by the National Geophysical Data Center (NGDC) in Boulder, Colo., USA. Solar-Geophysical Data is intended to keep research workers informed on a timely schedule of the major events of solar activity and the associated interplanetary, ionospheric, radio propagation and other geophysical effects.

Source record↗

The HEAO A-1 X Ray Source Catalog (Wood Et Al. 1984): Documentation for the Machine-Readable Version

The machine-readable version of the catalog, as it is currently being distributed from the Astronomical Data Center, is described. The catalog is a compilation of data for 842 sources detected with the U.S. Naval Research Laboratory Large Area Sky Survey Experiment flown aboard the HEAO 1 satellite. The data include source identifications, positions, error boxes, mean X-ray intensities, and cross identifications to other source designations.

Warren, Wayne H., Jr.↗

External comparisons of reprocessed SBUV/TOMS ozone data

Ozone Retrievals from the Solar Backscatter Ultraviolet (SBUV) Instrument on-board the Nimbus-7 Satellite have been reprocessed using an improved internal calibration. The resulting data set covering November, 1978 through January, 1987 has been archived at the National Space Science Data Center in Greenbelt, Maryland. The reprocessed SBUV total ozone data as well as recalibrated Total Ozone Mapping Spectrometer (TOMS) data are compared with total ozone measurements from a network of ground based Dobson spectrophotometers. The SBUV also measures the vertical distribution of ozone, and these measurements are compared with external measurements made by SAGE II, Umkehr, and Ozonesondes. Special attention is paid to long-term changes in ozone bias.

Wellemeyer, C. G.↗

Monitoring of MLS Measurements for Ozone Data Assimilation

The ozone data assimilation system at the NASA Goddard Space Flight Center Data Assimilation Office (DAO) has operationally provided near real time global three dimensional analyzed ozone fields since December 1999. Presently, 4 system assimilates both total column ozone and profile measurements from the NOAA - 16 SBUV/2 instrument into an off-line transport model using a physical space statistical analysis scheme (PS AS). Recently, this system was modified to investigate a possible impact from including MLS profile observations. Over a period from December 13, 1991 to March 1, 1992 the system assimilated both NOAA 11 SBUV/2 profile measurements and TOMS total column measurements. Short term ozone forecasts were produced and compared to MLS observations. The resulting observed -minus -forecast (O-F) residuals were studied regionally (by both latitude bands and pressure levels) in order to explore the potential impact of MLS observations on the assimilation and sensitivity to the UARS yaw maneuver and other instrument and algorithm characteristics. In addition, MLS profiles were compared to nearest neighbor SBUV and analysis profiles. In the tropics, analyzed ozone values tend to be too high from 1-3 hPa and too low from 10-20 hPa. MLS measurements in these regions tend be lower and higher (respectively) than forecast ozone values. This indicates that assimilating MLS measurements may improve, analysis results in these areas. Further, nearest neighbor profile comparisons in the southern high latitudes indicate that laminar features present in the analysis but not present in SBUV measurements, are also present in MLS measurements. This, together with the availability of MLS measurements in polar night regions indicates that assimilating MLS measurements in polar night regions indicates that assimilating MLS measurements may improve analyzed ozone values in high latitudes.

Winslow, Nathan↗

Serving Fisheries and Ocean Metadata to Communities Around the World

NASA's Global Change Master Directory (GCMD) assists the oceanographic community in the discovery, access, and sharing of scientific data by serving on-line fisheries and ocean metadata to users around the globe. As of January 2006, the directory holds more than 16,300 Earth Science data descriptions and over 1,300 services descriptions. Of these, nearly 4,000 unique ocean-related metadata records are available to the public, with many having direct links to the data. In 2005, the GCMD averaged over 5 million hits a month, with nearly a half million unique hosts for the year. Through the GCMD portal (http://qcrnd.nasa.qov/), users can search vast and growing quantities of data and services using controlled keywords, free-text searches or a combination of both. Users may now refine a search based on topic, location, instrument, platform, project, data center, spatial and temporal coverage. The directory also offers data holders a means to post and search their data through customized portals, i.e. online customized subset metadata directories. The discovery metadata standard used is the Directory Interchange Format (DIF), adopted in 1994. This format has evolved to accommodate other national and international standards such as FGDC and IS019115. Users can submit metadata through easy-to-use online and offline authoring tools. The directory, which also serves as a coordinating node of the International Directory Network (IDN), has been active at the international, regional and national level for many years through its involvement with the Committee on Earth Observation Satellites (CEOS), federal agencies (such as NASA, NOAA, and USGS), international agencies (such as IOC/IODE, UN, and JAXA) and partnerships (such as ESIP, IOOS/DMAC, GOSIC, GLOBEC, OBIS, and GoMODP), sharing experience, knowledge related to metadata and/or data management and interoperability.

Meaux, Melanie↗

Lunar Data Node: Apollo Data Restoration and Archiving Update

The Lunar Data Node (LDN) of the Planetary Data System (PDS) is responsible for the restoration and archiving of Apollo data. The LDN is located at the National Space Science Data Center (NSSDC), which holds much of the extant Apollo data on microfilm, microfiche, hard-copy documents, and magnetic tapes in older formats. The goal of the restoration effort is to convert the data into user-accessible PDS formats, create a full set of explanatory supporting data (metadata), archive the full data sets through PDS, and post the data online at the PDS Geosciences Node. This will both enable easy use of the data by current researchers and ensure that the data and metadata are securely preserved for future use. We are also attempting to locate and preserve Apollo data which were never archived at NSSDC. We will give a progress report on the data sets we have been restoring and future work.

Williams, David R.↗

Total Ozone Trends from 1979 to 2016 Derived from Five Merged Observational Datasets - The Emergence into Ozone Recovery

We report on updated trends using different merged datasets from satellite and ground-based observations for the period from 1979 to 2016. Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. Merged datasets used here include NASA MOD v8.6 and National Oceanic and Atmospheric Administration (NOAA) merge v8.6, both based on data from the series of Solar Backscatter UltraViolet (SBUV) and SBUV-2 satellite instruments (1978–present) as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone (GTO) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (1995-present), mainly comprising satellite data from GOME, the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and GOME-2A. The fifth dataset consists of the monthly mean zonal mean data from ground-based measurements collected at World Ozone and UV Data Center (WOUDC). The addition of four more years of data since the last World Meteorological Organization (WMO) ozone assessment (2013-2016) shows that for most datasets and regions the trends since the stratospheric halogen reached its maximum (approximately 1996 globally and approximately 2000 in polar regions) are mostly not significantly different from zero. However, for some latitudes, in particular the Southern Hemisphere extratropics and Northern Hemisphere subtropics, several datasets show small positive trends of slightly below +1 percent decade(exp. -1) that are barely statistically significant at the 2 Sigma uncertainty level. In the tropics, only two datasets show significant trends of +0.5 to +0.8 percent(exp.-1), while the others show near-zero trends. Positive trends since 2000 have been observed over Antarctica in September, but near-zero trends are found in October as well as in March over the Arctic. Uncertainties due to possible drifts between the datasets, from the merging procedure used to combine satellite datasets and related to the low sampling of ground-based data, are not accounted for in the trend analysis. Consequently, the retrieved trends can be only considered to be at the brink of becoming significant, but there are indications that we are about to emerge into the expected recovery phase. However, the recent trends are still considerably masked by the observed large year-to-year dynamical variability in total ozone.

column ozone trends↗

Enabling Analysis of Air Quality Data From Tropospheric Emissions: Monitoring of POllution (Tempo) Via Cloud-Based Tools

Launched in April 2023, the Tropospheric Emissions: Monitoring of POllution (TEMPO) instrument provides high-resolution measurements of key atmospheric pollutants, such as ozone, nitrogen dioxide, and formaldehyde. Maximizing the use and utility of this new source of air quality information requires streamlining data access for a wide variety of research, public health, and other interested users. These varied applications often require the data to be structured in different ways, e.g., specific formats, array shapes, or file sizes. To enable access to TEMPO data in different forms, the NASA Atmospheric Science Data Center (ASDC), as part of the NASA Earth Science Data and Information System (ESDIS), provides a variety of cloud-based data transformation and GIS visualization tools. This presentation demonstrates methods of accessing and working with TEMPO data through these services, while highlighting aspects of the software and algorithmic workflows that perform the necessary data transformations. Examples include data subsetting, concatenation, and visualizations accessible via Jupyter notebooks and GIS software.

Daniel Kaufman↗

AXAF user interfaces for heterogeneous analysis environments

The AXAF Science Center (ASC) will develop software to support all facets of data center activities and user research for the AXAF X-ray Observatory, scheduled for launch in 1999. The goal is to provide astronomers with the ability to utilize heterogeneous data analysis packages, that is, to allow astronomers to pick the best packages for doing their scientific analysis. For example, ASC software will be based on IRAF, but non-IRAF programs will be incorporated into the data system where appropriate. Additionally, it is desired to allow AXAF users to mix ASC software with their own local software. The need to support heterogeneous analysis environments is not special to the AXAF project, and therefore finding mechanisms for coordinating heterogeneous programs is an important problem for astronomical software today. The approach to solving this problem has been to develop two interfaces that allow the scientific user to run heterogeneous programs together. The first is an IRAF-compatible parameter interface that provides non-IRAF programs with IRAF's parameter handling capabilities. Included in the interface is an application programming interface to manipulate parameters from within programs, and also a set of host programs to manipulate parameters at the command line or from within scripts. The parameter interface has been implemented to support parameter storage formats other than IRAF parameter files, allowing one, for example, to access parameters that are stored in data bases. An X Windows graphical user interface called 'agcl' has been developed, layered on top of the IRAF-compatible parameter interface, that provides a standard graphical mechanism for interacting with IRAF and non-IRAF programs. Users can edit parameters and run programs for both non-IRAF programs and IRAF tasks. The agcl interface allows one to communicate with any command line environment in a transparent manner and without any changes to the original environment. For example, the authors routinely layer the GUI on top of IRAF, ksh, SMongo, and IDL. The agcl, based on the facilities of a system called Answer Garden, also has sophisticated support for examining documentation and help files, asking questions of experts, and developing a knowledge base of frequently required information. Thus, the GUI becomes a total environment for running programs, accessing information, examining documents, and finding human assistance. Because the agcl can communicate with any command-line environment, most projects can make use of it easily. New applications are continually being found for these interfaces. It is the authors' intention to evolve the GUI and its underlying parameter interface in response to these needs - from users as well as developers - throughout the astronomy community. This presentation describes the capabilities and technology of the above user interface mechanisms and tools. It also discusses the design philosophies guiding the work, as well as hopes for the future.

Mandel, Eric↗

Approach to Managing MeaSURES Data at the GSFC Earth Science Data and Information Services Center (GES DISC)

A major need stated by the NASA Earth science research strategy is to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. (NASA Solicitation for Making Earth System data records for Use in Research Environments (MEaSUREs) 2006-2010) Selected projects create long term records of a given parameter, called Earth Science Data Records (ESDRs), based on mature algorithms that bring together continuous multi-sensor data. ESDRs, associated algorithms, vetted by the appropriate community, are archived at a NASA affiliated data center for archive, stewardship, and distribution. See http://measures-projects.gsfc.nasa.gov/ for more details. This presentation describes the NASA GSFC Earth Science Data and Information Services Center (GES DISC) approach to managing the MEaSUREs ESDR datasets assigned to GES DISC. (Energy/water cycle related and atmospheric composition ESDRs) GES DISC will utilize its experience to integrate existing and proven reusable data management components to accommodate the new ESDRs. Components include a data archive system (S4PA), a data discovery and access system (Mirador), and various web services for data access. In addition, if determined to be useful to the user community, the Giovanni data exploration tool will be made available to ESDRs. The GES DISC data integration methodology to be used for the MEaSUREs datasets is presented. The goals of this presentation are to share an approach to ESDR integration, and initiate discussions amongst the data centers, data managers and data providers for the purpose of gaining efficiencies in data management for MEaSUREs projects.

Vollmer, Bruce↗

TESS Science Data Products Description Document: EXP-TESS-ARC-ICD-0014 Rev F

This document discusses data product formats that are produced primarily by the TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center. Data products are sent to the TESS Science Operations Center (SOC) at MIT where they are disseminated to the Mikulski Archive for Space Telescopes (MAST) and the TESS Science Office (TSO).

TESS↗