(U) Archiving Physics Data for Today and Tomorrow [Slides]
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GSFC program in telemetry data archiving, discussing necessity of data accessing capability
A brief review is presented of a three-part project (partially supported by NASA), which promotes greater utilization of social survey data for gaining new information about human response to environmental noise. The goal is accomplished by (1) publishing a catalog of existing social surveys on environmental noise, (2) establishing a data archive for noise survey data sets, and (3) reanalyzing selected surveys to address substantial and methodological issues. A finding about annoyance scales illustrates the use of a comparative analysis.
In a study concerning the value of using radar imagery from systems with diverse parameters, X-band images of the Northern Louisiana Salt dome area generated by the airborne Goodyear electronic mapping system (GEMS) are analyzed in conjunction with imagery generated by the satelliteborne Seasat/SAR. The GEMS operated with an incidence angle of 75 to 85 deg and a resolution of 12 m, whereas the Seasat/SAR operated with an incidence angle of 23 deg and a resolution of 25 m. It is found that otherwise unattainable data on land management activities, improved delineation of the drainage net, better definition of surface roughness in cleared areas, and swamp identification, became accessible when adjustments for the time lapse between the two missions were made and supporting ground data concerning the physical and vegetative characteristics of the terrain were acquired.
The project consisted of two parts. The first was to obtain new low-dispersion, long-wavelength, high S/N IUE spectra of F-G-K dwarf stars with previously determined abundances, temperatures, and gravities. To insure high quality, the spectra are either trailed, or multiple exposures are taken within the large aperture. Second, the spectra are assembled into a library which combines the new data with existing IUE Archive data to yield mean spectral energy distributions for each important type of star. My principal responsibility is the construction and maintenance of this UV spectral library. It covers the spectral range 1200-3200A and is maintained in two parts: a version including complete wavelength coverage at the full spectral resolution of the Low Resolution cameras; and a selected bandpass version, consisting of the mean flux in pre-selected 20A bands. These bands are centered on spectral features or continuum regions of special utility - e.g. the C IV lambda 1550 or Mg II lambda 2800 feature. In the middle-UV region, special emphasis is given to those features (including continuum 'breaks') which are most useful in the study of F-G-K star spectra in the integrated light of old stellar populations.
Viewgraphs on ACTS Data Center status report are included. Topics covered include: ACTS Data Center Functions; data flow overview; PPD flow; RAW data flow; data compression; PPD distribution; RAW Data Archival; PPD Audit; and data analysis.
The NOAA satellite ozone monitoring program was initiated by the National Environmental Satellite Data and Information Service (NESDIS) in December 1984, with the launch of the NOAA-9 spacecraft carrying the first operational Solar Backscatter Ultraviolet Spectrometer (SBUV/2). This instrument and its successor on NOAA-11, launched in 1988, are similar to the SBUV instrument launched by the NASA in 1978 on the Nimbus-7 research spacecraft. Measurements by the SBUV and SBUV/2 instruments overlap beginning in 1985. These instruments use measurements of the reflected ultraviolet solar radiation from the atmosphere to derive total ozone amounts and ozone vertical profiles. Since launch, the NOAA instruments and the derived products have been undergoing extensive evaluation by scientists of NOAA and NASA. Measurements obtained with these instruments are processed in real time by the NESDIS. These are reprocessed as the SBUV/2 instrument characterization is refined and as the retrieval algorithm for processing the data is improved. The NOAA-9 ozone data archive begins in March 1985 and continues through October 1990. The archive of NOAA-11 data begins in January 1989 and the data continues to be acquired in 1992.
Studies of global change and other regional issues depend on ecological data collected at multiple study areas or sites. An information system model is proposed for compiling diverse data from dispersed sources so that the data are consistent, complete, and readily available. The model includes investigators who collect and analyze field measurements, science teams that synthesize data, a project information system that collates data, a data archive center that distributes data to secondary users, and a master data directory that provides broader searching opportunities. Special attention to format consistency is required, such as units of measure, spatial coordinates, dates, and notation for missing values. Often data may need to be enhanced by estimating missing values, aggregating to common temporal units, or adding other related data such as climatic and soils data. Full documentation, an efficient data distribution mechanism, and an equitable way to acknowledge the original source of data are also required.
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Crowdsourced data streams such as Twitter and other social media are important sources of real-time and historical global information for Earth science applications. At the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we have been exploring the Twitter data stream for its potential in augmenting the validation program of NASA's Global Precipitation Measurement (GPM) mission. To realize this potential, we need to increase the information density and enhance the quality of filtered precipitation tweets. We have implemented various components of a machine learning (ML)-based processing infrastructure for crowdsourced data that outputs, in this instance, useful and usable information derived from precipitation tweets. We have test enriched the Twitter stream with higher quality active tweets from those knowingly contributing to our effort and from existing crowdsourced programs (e.g., mPING, CoCoRaHS). We have experimented with various algorithms for processing tweets, including Naà ve Bayes, Convolutional Neural Network (CNN), Hierarchical Attention Network (HAN), and semi-supervised learning (with tri-training). Our current work focuses on (1) automated review of Earth science-related publications to determine relationships between discipline research needs and ML algorithms; (2) investigating Sequential Generative Adversarial Network (SeqGAN) for processing precipitation tweets for anomaly detection; and (3) managing crowdsourced data in a way that is compatible with existing NASA satellite data archives and using the data for ML applications. Key results include (1) network visualization of NLP-processed publications in various Earth science disciplines; (2) difference between GPM-linked, generated tweets and collected actual tweets that is small for GPM-determined light to moderate rain cases and high for GPM-determined heavy rain cases; and (3) identification of MongoDB for storing raw tweets and Zarr format for gridded tweets (compatible with GPM data). Our results have taken us a step closer to an operational ML-based tweet processing infrastructure and have already demonstrated that tweet-derived precipitation information is potentially useful for validation of Earth science satellite data.
The founding of the Skylab medical data center and archives as a central area to house medical data from space flights is described. Skylab program strip charts, various daily reports and summaries, experiment reports and logs, status report on Skylab data quality, raw data digital tapes, processed data microfilm, and other Skylab documents are housed in the data center. In addition, this memorandum describes how the data center acted as a central point for the coordination of preflight and postflight baseline data and how it served as coordinator for all data processing through computation and analysis. Also described is a catalog identifying Skylab medical experiments and all related data currently archived in the data center.
The lidar data obtained by the Langley Aircraft Lidar in October 1986 in Wisconsin is being reduced in a transparent, simple fashion and will be published in its reduced form in a NASA Reference Publication (RP). This reduced data will also be submitted to the FIRE data archives. Some of this reduced data will be presented at the FIRE FSET Workshop to acquaint the science team with the data format to be used in the archive and the upcoming catalog contained in the RP. A new method was utilized in Wisconsin for obtain the depolarization ratio of aerosols. This method involves using a half-wave plate to calibrate the lidar under field conditions. The theory behind this technique will be presented at this workshop as well as some of the lidar calibration results. The lidar calibration will be utilized in interpreting some of the dual polarization lidar data obtained during the IFO in Wisconsin. Some of these data are also discussed. A continuous wave laser lab-type lidar simulator was constructed during the previous year. One of the primary reasons for the construction of the simulator was to attempt dual-polarization lidar-like calibrations under laboratory, rather than field conditions. The data collected by this system was used to experimentally check and thus, inspire confidence in the algorithms being used to interpret the lidar data obtained in the field. A computer program which simulates noisy lidar data was used as a part of this effort in order to obtain some feel for the noise in the inversion parameters as a function of noise in the actual measurements. The lidar simulation will be described in addition to presenting some of the lab-generated calibration data.
A brief summary of the Earth Observing System Data and Information System (EOSDIS) Core System (ECS) Data Archive and Distribution System (DADS) requirements is given. Among the requirements are the following: the ECS relationship to EOSDIS Version-O; phased implementation of ECS; and data ingest, archive, and distribution daily data volumes anticipated at each of the 7 Distributed Active Archive Centers (DAAC's).
The Planetary Data System Data Model consists of a set of standardized descriptions of entities within the Planetary Science Community. These can be real entities in the space exploration domain such as spacecraft, instruments, and targets; conceptual entities such as data sets, archive volumes, and data dictionaries; or the archive data products such as individual images, spectrum, series, and qubes.
An overview is given of a data base management system that can catalog and archive data at rates up to 50M bits/sec. Emphasis is on the laser disk system that is used for the archive. All key components in the system (3 Vax 11/780s, a SEL 32/2750, a high speed communication interface, and the optical disk) are interfaced to a 100M bits/sec 16-port fiber optic bus to achieve the high data rates. The basic data unit is an autonomous data packet. Each packet contains a primary and secondary header and can be up to a million bits in length. The data packets are recorded on the optical disk at the same time the packet headers are being used by the relational data base management software ORACLE to create a directory independent of the packet recording process. The user then interfaces to the VAX that contains the directory for a quick-look scan or retrieval of the packet(s). The total system functions are distributed between the VAX and the SEL. The optical disk unit records the data with an argon laser at 100M bits/sec from its buffer, which is interfaced to the fiber optic bus. The same laser is used in the read cycle by reducing the laser power. Additional information is given in the form of outlines, charts, and diagrams.
The modular architecture, functionality, and key components of the Hubble Space Telescope Data Archive Distribution Service (DADS) are presented. DADS functions comprise archive management, catalog management, and user interface. The distributed modular architecture utilized is made up of four subsystems, including the archive, host, catalog, and the Science Operations ground System/DADS Interface Processor. All data generated by the HST are archived in DADS on 12-in. optical disks. DADS is a permanent archive with a data capacity of 30 terabytes that can be expanded to 68 terabytes. Supplementary information and stellar observations will be instantly accessible through DADS, which can collect and archive more than 3 gigabytes per day of image and support data over the lifetime of the HST. Electronic and physical media will be accessible through 140 network connections, with a catalogue to assist in data set selection.
The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations - the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.