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Wide-field direct CCD observations supporting the Astro-1 Space Shuttle mission's Ultraviolet Imaging Telescope

Wide field direct CCD observations are being obtained to support and complement the vacuum-ultraviolet (VUV) images provided by Astro's Ultraviolet Imaging Telescope (UIT) during a Space Shuttle flight in December 1990. Because of the wide variety of projects addressed by UIT, the fields observed include (1) galactic supernova remnants such as the Cygnus Loop and globular clusters such as Omega Cen and M79; (2) the Magellanic Clouds, M33, M81, and other galaxies in the Local Group; and (3) rich clusters of galaxies, principally the Perseus cluster and Abell 1367. Ground-based observations have been obtained for virtually all of the Astro-1 UIT fields. The optical images allow identification of individual UV sources in each field and provide the long baseline in wavelength necessary for accurate analysis of UV-bright sources. To facilitate use of our optical images for analysis of UIT data and other projects, we plan to archive them, with the UIT images, at the National Space Science Data Center (NSSDC), where they will be universally accessible via anonymous FTP. The UIT, one of three telescopes comprising the Astro spacecraft, is a 38-cm f/9 Ritchey-Chretien telescope on which high quantum efficiency, solar-blind image tubes are used to record VUV images on photographic film. Five filters with passbands centered between 1250A and 2500A provide both VUV colors and a measurement of extinction via the 2200A dust feature. The resulting calibrated VUV pictures are 40 arcminutes in diameter at 2.5 arcseconds resolution. The capabilities of UIT, therefore, complement HST's WFPC: the latter has 40 times greater collecting area, while UIT's usable field has 170 times WFPC's field area.

Hintzen, Paul↗

EOS Data Products Handbook

The EOS Data Products Handbook provides brief descriptions of the data products that will be produced from a range of missions of the Earth Observing System (EOS) and associated projects. Volume 1, originally published in 1997, covers the Tropical Rainfall Measuring Mission (TRMM), the Terra mission (formerly named EOS AM-1), and the Data Assimilation System, while this volume, Volume 2, covers the Active Cavity Radiometer Irradiance Monitor Satellite (ACRIMSAT), Aqua, Jason-1, Landsat 7, Meteor 3M/Stratospheric Aerosol and Gas Experiment III (SAGE III). the Quick Scatterometer (QuikScat), the Quick Total Ozone Mapping Spectrometer (Quik-TOMS), and the Vegetation Canopy Lidar (VCL) missions. Volume 2 follows closely the format of Volume 1, providing a list of products and an introduction and overview descriptions of the instruments and data processing, all introductory to the core of the book, which presents the individual data product descriptions, organized into 11 topical chapters. The product descriptions are followed by five appendices, which provide contact information for the EOS data centers that will be archiving and distributing the data sets, contact information for the science points of contact for the data products, references, acronyms and abbreviations, and a data products index.

Parkinson, Claire L.↗

Goddard Earth Observing System - Data Assimilation System (GEOS-4 DAS) Data Products at the NASA Goddard Earth Science DISC DAAC

This list contains the names of data products from the Goddard Earth Observing System - Data Assimilation System (GEOS-4 DAS) at the Goddard Earth Science (GES) Data and Information Services Center (DISC) Distributed Active Archive Center (DAAC). The list divides the data products into Assimilated Synoptic Files and Assimilated Time Averaged Files.

Source record↗

AIRS Data Products at GES DISC DAAC

This list contains the names and some characteristics of Atmospheric InfraRed Sounder (AIRS) data products at the Goddard Earth Sciences (GES) Data and Information Services Center (DISC) Distributed Active Archive Center (DAAC). The list includes variables, units, dimensions, and descriptions for each of the data products, which include infrared radiances and brightness temperatures.

Source record↗

NASA GES DISC DAAC Satellite Data for GIS

NASA's Goddard Earth Science (GES) Data and Information Services Center (DISC) Distributed Active Archive Center (DAAC) makes available a large and continually growing collection of spatially continuous global satellite observations of environmental parameters. These products include those from the MODIS (Moderate Resolution Imaging Spectroradiometer) on both Terra and Aqua platforms, and the Tropical Rainfall Measuring Mission (TRMM). These data products are well suited for use within Geographic Information Systems (GIS), as both backdrops to cartographic products as well as spatial analysis. However, data format, file size, and other issues have limited their widespread use by traditional GIS users. To address these data usability issues, the GES DISC DAAC recently updated tools and improved documentation of conversion procedures. In addition, the GES DISC DAAC has also been working with a major GIS software vendor to incorporate the ability to read the native Hierarchial Data Format (HDF), the format in which most of the NASA data is stored. The result is the enabling of GIS users to realize the benefit of GES DISC DAAC data without a substantial expenditure in resources to incorporate these data into their GIS. Several documents regarding the potential uses of GES DISC DAAC satellite data in GIS have recently been created. These show the combinations of concurrent data from different satellite products with traditional GIS vector products for given geographic areas. These map products include satellite imagery of Hurricane Isabel and the California wildfires, and can be viewed at http://daac.gsfc.nasa.gov/MODIS/GIS/.

Nickless, Darryl↗

Newly Released TRMM Version 7 Products, Other Precipitation Datasets and Data Services at NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is home of global precipitation product archives, in particular, the Tropical Rainfall Measuring Mission (TRMM) products. TRMM is a joint U.S.-Japan satellite mission to monitor tropical and subtropical (40 S - 40 N) precipitation and to estimate its associated latent heating. The TRMM satellite provides the first detailed and comprehensive dataset on the four dimensional distribution of rainfall and latent heating over vastly undersampled tropical and subtropical oceans and continents. The TRMM satellite was launched on November 27, 1997. TRMM data products are archived at and distributed by GES DISC. The newly released TRMM Version 7 consists of several changes including new parameters, new products, meta data, data structures, etc. For example, hydrometeor profiles in 2A12 now have 28 layers (14 in V6). New parameters have been added to several popular Level-3 products, such as, 3B42, 3B43. Version 2.2 of the Global Precipitation Climatology Project (GPCP) dataset has been added to the TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/), allowing online analysis and visualization without downloading data and software. The GPCP dataset extends back to 1979. Version 3 of the Global Precipitation Climatology Centre (GPCC) monitoring product has been updated in TOVAS as well. The product provides global gauge-based monthly rainfall along with number of gauges per grid. The dataset begins in January 1986. To facilitate data and information access and support precipitation research and applications, we have developed a Precipitation Data and Information Services Center (PDISC; URL: http://disc.gsfc.nasa.gov/precipitation). In addition to TRMM, PDISC provides current and past observational precipitation data. Users can access precipitation data archives consisting of both remote sensing and in-situ observations. Users can use these data products to conduct a wide variety of activities, including case studies, model evaluation, uncertainty investigation, etc. To support Earth science applications, PDISC provides users near-real-time precipitation products over the Internet. At PDISC, users can access tools and software. Documentation, FAQ and assistance are also available. Other capabilities include: 1) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Mirador is designed to be fast and easy to learn; 2)TOVAS; 3) NetCDF data download for the GIS community; 4) Data via OPeNDAP (http://disc.sci.gsfc.nasa.gov/services/opendap/). The OPeNDAP provides remote access to individual variables within datasets in a form usable by many tools, such as IDV, McIDAS-V, Panoply, Ferret and GrADS; 5) The Open Geospatial Consortium (OGC) Web Map Service (WMS) (http://disc.sci.gsfc.nasa.gov/services/wxs_ogc.shtml). The WMS is an interface that allows the use of data and enables clients to build customized maps with data coming from a different network.

Liu, Zhong↗

Tropical Rainfall Measuring Mission (TRMM) Precipitation Data and Services for Research and Applications

Precipitation is a critical component of the Earth's hydrological cycle. Launched on 27 November 1997, TRMM is a joint U.S.-Japan satellite mission to provide the first detailed and comprehensive data set of the four-dimensional distribution of rainfall and latent heating over vastly under-sampled tropical and subtropical oceans and continents (40 S - 40 N). Over the past 14 years, TRMM has been a major data source for meteorological, hydrological and other research and application activities around the world. The purpose of this short article is to inform that the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides TRMM archive and near-real-time precipitation data sets and services for research and applications. TRMM data consist of orbital data from TRMM instruments at the sensor s resolution, gridded data at a range of spatial and temporal resolutions, subsets, ground-based instrument data, and ancillary data. Data analysis, display, and delivery are facilitated by the following services: (1) Mirador (data search and access); (2) TOVAS (TRMM Online Visualization and Analysis System); (3) OPeNDAP (Open-source Project for a Network Data Access Protocol); (4) GrADS Data Server (GDS); and (5) Open Geospatial Consortium (OGC) Web Map Service (WMS) for the GIS community. Precipitation data application services are available to support a wide variety of applications around the world. Future plans include enhanced and new services to address data related issues from the user community. Meanwhile, the GES DISC is preparing for the Global Precipitation Measurement (GPM) mission which is scheduled for launch in 2014.

Liu, Zhong↗

Update on Apollo Data Restoration by the NSSDC and the PDS Lunar Data Node

The Lunar Data Node (LDN) , under the auspices of the Geosciences Node of the Planetary Data System (PDS) and the National Space Science Data Center (NSSDC), is continuing its efforts to recover and restore Apollo science data. The data being restored are in large part archived with NSSDC on older media, but unarchived data are also being recovered from other sources. They are typically on 7- or 9-track magnetic tapes, often in obsolete formats, or held on microfilm, microfiche, or paper documents. The goal of the LDN is to restore these data from their current form, which is difficult for most researchers to access, into common digital formats with all necessary supporting data (metadata) and archive the data sets with PDS. Restoration involves reading the data from the original media, deciphering the data formats to produce readable digital data and converting the data into usable tabular formats. Each set of values in the table must then be understood in terms of the quantity measured and the units used. Information on instrument properties, operational history, and calibrations is gathered and added to the data set, along with pertinent references, contacts, and other ancillary documentation. The data set then undergoes a peer review and the final validated product is archived with PDS. Although much of this effort has concentrated on data archived at NSSDC in the 1970's, we have also recovered data and information that were never sent to NSSDC. These data, retrieved from various outside sources, include raw and reduced Gamma-Ray Spectrometer data from Apollos 15 and 16, information on the Apollo 17 Lunar Ejecta And Meteorites experiment, Dust Detector data from Apollos 11, 12, 14, and I5, raw telemetry tapes from the Apollo ALSEPs, and Weekly Status Reports for all the Apollo missions. These data are currently being read or organized, and supporting data is being gathered. We are still looking for the calibrated heat flow data from Apollos 15 and 17 for the period 1975-1977, any assistance or information on these data would be welcome. NSSDC has recently been tasked to release its hard-copy archive, comprising photography, microfilm, and microfiche. The details are still being discussed, but we are concentrating on recovering the valuable lunar data from these materials while they are still readily accessible. We have identified the most critical of these data and written a LASER proposal to fund their restoration. Included in this effort are data from the Apollo 15 and 16 Mass Spectrometers and the Apollo 17 Par-UV Spectrometer and ancillary information on the Apollo 17 Surface Electrical Properties Experiment.

Williams, David R.↗

The Astrophysical Multimessenger Observatory Network (AMON)

We summarize the science opportunity, design elements, current and projected partner observatories, and anticipated science returns of the Astrophysical Multimessenger Observatory Network (AMON). AMON will link multiple current and future high-energy, multimessenger, and follow-up observatories together into a single network, enabling near real-time coincidence searches for multimessenger astrophysical transients and their electromagnetic counterparts. Candidate and high-confidence multimessenger transient events will be identified, characterized, and distributed as AMON alerts within the network and to interested external observers, leading to follow-up observations across the electromagnetic spectrum. In this way, AMON aims to evoke the discovery of multimessenger transients from within observatory subthreshold data streams and facilitate the exploitation of these transients for purposes of astronomy and fundamental physics. As a central hub of global multimessenger science, AMON will also enable cross-collaboration analyses of archival datasets in search of rare or exotic astrophysical phenomena.

comparison↗

Nature of and Lessons Learned from Lunar Ice Cube and the First Deep Space Cubesat 'Cluster'

Cubesats operating in deep space face challenges Earth-orbiting cubesats do not. 15 deep space cubesat 'prototypes' will be launched over the next two years including the two MarCO cubesats, the 2018 demonstration of dual communication system at Mars, and the 13 diverse cubesats being deployed from the SLS EM1 mission within the next two years. Three of the EM1 cubesat missions, including the first deep space cubesat 'cluster', will be lunar orbiters with remote sensing instruments for lunar surface/regolith measurements. These include: Lunar Ice Cube, with its 1-4 micron broadband IR spectrometer, BIRCHES, to determine volatile distribution as a function of time of day; Lunar Flashlight, to confirm the presence of surface ice at the lunar poles, utilizing an active source (laser), and looking for absorption features in the returning signal; and LunaH-Map to characterize ice at or below the surface at the poles with a compact neutron spectrometer. In addition, the BIRCHES instrument on Lunar Ice Cube will provide the first demonstration of a microcryocooler (AIM/IRIS) in deep space. Although not originally required to do so, all will be delivering science data to the Planetary Data System, the first formal archiving effort for cubesats. 4 of the 20 recently NASA-sponsored (PSDS3) study groups for deep space cubesat/smallsat mission concepts were lunar mission concepts, most involving 12U cubesats. NASA SIMPLEX 2/SALMON 3 AO will create ongoing opportunities for low-cost missions as 'rides' on government space program or private sector vehicles as these become available.

Ice Cube↗

The Value of Being a Trustworthy Repository

Today, NASA's Earth Observing System Data and Information System (EOSDIS), a system ofactive archives is attaching the CoreTrustSeal to its websites signifying that it merits theconfidence of its user community. But what value does being a trustworthy repository impart to auser? What does it mean to the owners and operators of repositories? What will it mean in thefuture? EOSDIS was started in the 1990s based on a framework of discipline-oriented, geographicallydistributed centers of expertise, named Distributed Active Archive Centers (DAACs). The functionof EOSDIS is to collect Earth Science data sensor measurements (principally those created andneeded by NASA) and manage the data and many derived digital products. EOSDIS providesmany services, including processing, curating, documenting, disseminating, and enabling datadiscovery as well as efficient use of the data. The EOSDIS has been operational over 25 years andmany lessons have been learned relative to the TRUST principles. During the tenure of EOSDIS,many changes have occurred as we have increased the size of the collection from gigabytes totens of petabytes and the distribution of the data to millions of users. We have had severalstages of system evolution that have improved EOSDIS in order to meet both stakeholder andcustomer expectations. This type of evolution is an on-going process to ensure that ourrepositories remain trustworthy. It is also important that our own community of data managersand system engineers add value in being trustworthy. This paper will discuss approaches to change within a large system of Earth Science data and services, while remaining a trustworthyrepository.

Behnke, Jeanne↗

Machine Learning-Based Atmospheric Phenomena Detection Platform

As the number of Earth pointing satellites has increased over the last several decades, the data volume retrieved from instruments onboard these satellites has also increased. It is expected that this trend will continue as more data intensive missions and small satellite constellations are launched. Currently, feature detection - namely atmospheric phenomena - in these datasets is performed manually and is thus not scalable with the growing data archives. Recent advancements in computational efficiency allow for the Earth science community to leverage machine learning to identify interesting atmospheric phenomena. Given the wide range of distinctive features in various atmospheric phenomena, a specialized machine learning model is required for accurate detection of these phenomena independently. The Phenomena Portal, developed at NASA IMPACT, is designed to provide visualization for the output from these machine learning models. In addition, detected events for each atmospheric phenomena are stored in a database that can be used to more easily use/subset larger spatiotemporal datasets. The user interface also incorporates additional features to enhance the user experience including spatiotemporal analysis, multiple base layer images, and a slider to filter events with lower probabilities of positive detection. Each detection supports user feedback on whether the detection is true or false that can then be stored and used to improve the machine learning model performance.

Gurung, Iksha↗

Nature of and Lessons Learned from Lunar Ice Cube and the First Deep Space Cubesat 'Cluster'

Cubesats operating in deep space face challenges Earth-orbiting cubesats do not. 15 deep space cubesat 'prototypes' will be launched over the next two years including the two MarCO cubesats, the 2018 demonstration of dual communication system at Mars, and the 13 diverse cubesats being deployed from the SLS EM1 mission within the next two years. Three of the EM1 cubesat missions, including the first deep space cubesat 'cluster', will be lunar orbiters with remote sensing instruments for lunar surface/regolith measurements. These include: Lunar Ice Cube, with its 1-4 micron broadband IR spectrometer, BIRCHES, to determine volatile distribution as a function of time of day; Lunar Flashlight, to confirm the presence of surface ice at the lunar poles, utilizing an active source (laser), and looking for absorption features in the returning signal; and LunaH-Map to characterize ice at or below the surface at the poles with a compact neutron spectrometer. In addition, the BIRCHES instrument on Lunar Ice Cube will provide the first demonstration of a microcryocooler (AIM/IRIS) in deep space. Although not originally required to do so, all will be delivering science data to the Planetary Data System, the first formal archiving effort for cubesats. 4 of the 20 recently NASA-sponsored (PSDS3) study groups for deep space cubesat/smallsat mission concepts were lunar mission concepts, most involving 12U cubesats. NASA SIMPLEX 2/SALMON 3 AO will create ongoing opportunities for low-cost missions as 'rides' on government space program or private sector vehicles as these become available.

Bujold, Emily↗

Enabling Collaborative Space Weather Research at the Community Coordinated Modeling Center (CCMC)

Space weather models have been actively developed by the international research community, covering extensive spatial and physical domains. Still, many of the ground-breaking models remain a granular effort, insulated from a wider research audience, particularly that in different domains, and possible end users. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) seeks to remove such barriers to collaboration and coordination by providing a convenient platform for hosting space weather models and associated services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, as well as collaborate on a continuously updated archive of model run results. Moreover, the multi-disciplinary science support team at CCMC facilitates and enables collaboration across domains. In our presentation, we will discuss the space weather model services at CCMC, including Runs-on-Request, Real-Time Continuous Runs, and Instant Runs. We will also review new and updated models added to the extensive collection of space weather models hosted at CCMC. We will focus on trends in model, service, and science support utilization at CCMC as a proxy to the most pressing needs of the collaborative modeling community.

space weather↗

NASA's Earth Observing Data and Information System - Near-Term Challenges

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of the NASA Earth observation program since the 1990's. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, digital elevation, atmosphere dynamics and composition, and inter-disciplinary research, and many others. One of the key components of EOSDIS is a set of twelve discipline-based Distributed Active Archive Centers (DAACs) distributed across the United States. Managed by NASA's Earth Science Data and Information System (ESDIS) Project at Goddard Space Flight Center, these DAACs serve over 3 million users globally. The ESDIS Project provides the infrastructure support for EOSDIS, which includes other components such as the Science Investigator-led Processing systems (SIPS), common metadata and metrics management systems, specialized network systems, standards management, and centralized support for use of commercial cloud capabilities. Given the long-term requirements, and the rapid pace of information technology and changing expectations of the user community, EOSDIS has evolved continually over the past three decades. However, many challenges remain. Challenges addressed in this paper include: growing volume and variety, achieving consistency across a diverse set of data producers, managing information about a large number of datasets, migration to a cloud computing environment, optimizing data discovery and access, incorporating user feedback from a diverse community, keeping metadata updated as data collections grow and age, and ensuring that all the content needed for understanding datasets by future users is identified and preserved.

Remote Sensing↗

The Suomi National Polar-Orbiting Partnership (SNPP): Continuing NASA Research and Applications

The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).

remote sensing↗

ASDC’s Python-Based Metadata Extraction Pipeline for Suborbital Campaigns

The FAIRness of data products, especially findability and accessibility depend on rich metadata which, when extracted, can allow for proper curation. Over the past few years, the Atmospheric Science Data Center (ASDC) suborbital science support team has developed a metadata extraction pipeline to ensure the required metadata can be retrieved systematically, effectively, and efficiently to ensure the data can be used by a broad community. The development of a pipeline has presented many, but necessary, challenges to support archival and distribution of ASDC’s 30+ suborbital missions. Though sufficient metadata is provided by instrument scientists, the metadata may not be readily machine actionable due to different formats and templates. Further complicating metadata extraction, our team has found that the nature of metadata can be quite diverse given the difference in measurement types, instruments, and measurement platforms. A metadata extraction pipeline has been developed to provide an efficient, plugin-in based, method for adding new parsers, a configuration system that lets non-developers customize how files are processed, and a system for identifying and logging metadata quality issues to ensure they are readily found and addressed. The metadata extraction pipeline identifies critical pieces of metadata that are needed to promote data FAIRness, including location, file revision, measurement start/end datetime and can be easily modified to extract further information (such as variables). Given the wide-ranging datasets, the pipeline has been modified to accommodate multiple file formats, including multiple versions of ICARTT (International Consortium for Atmospheric Research on Transport and Transformation), HDF (Hierarchical Data Format), netCDF (network Common Data Form), and multiple versions of the Ames File Format. The pipeline also supports building metadata for file formats that cannot have metadata easily extracted from them, such as PDF (Portable Document Format) and GIF (Graphics Interchange Format). The pipeline has allowed our team to maintain a consistent flow of data and metadata to archival and distribution services, ensuring the ASDC meets the needs of the suborbital science community. This presentation will highlight the ASDC’s suborbital metadata extraction pipeline, its development, how it’s been modified to support data FAIRness, and plans for maintaining the pipeline and adding new features.

Abraham Porter↗

Explore Earth Science Datasets for STEM with the NASA GES DISC Online Visualization and Analysis Tool, Giovanni

The NASA Goddard Earth Sciences (GES) Data and Information Services Center(DISC) is one of twelve NASA Science Mission Directorate (SMD) Data Centers that provide Earth science data, information, and services to users around the world including research and application scientists, students, citizen scientists, etc. The GESDISC is the home (archive) of remote sensing datasets for NASA Precipitation and Hydrology, Atmospheric Composition and Dynamics, etc. To facilitate Earth science data access, the GES DISC has been developing user-friendly data services for users at different levels in different countries. Among them, the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni, http:giovanni.gsfc.nasa.gov) allows users to explore satellite-based datasets using sophisticated analyses and visualization without downloading data and software, which is particularly suitable for novices (such as students) to use NASA datasets in STEM (science, technology, engineering and mathematics) activities. In this presentation, we will briefly introduce Giovanni along with examples for STEM activities.

precipitation↗