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Coping with all the earth science data

A report on the NASA-sponsored Earth Science and Applications Data Systems (ESADS) Workshop is presented. The ESADS report is reviewed and the task groups of the workshop are listed. The program set up to implement the recommendations of the workshop is discussed. The priorities of the ESADS committee recommendations include the development of standards and guidelines for data and metadata exchange, the creation of interoperable catalogs and directories, the development of guidelines for ancillary data archives, development of standard user interfaces, providing greater bandwidth in the user environment, collecting information about data storage technologies, and providing improved network connectivity.

Kahn, Ralph↗

DC-8 mission planning

A number of tasks needed to be performed to operate the DC-8 aircraft in the Arctic Ozone Expedition during 1989. These included development of improved navigational computer programs and performing advanced planning for flight tracks. The missions required further work in the field to plan flight tracks and to establish a data archive. The DC-8 aircraft was operated during the deployment phase of the Arctic Ozone Expedition. Data were collected revealing the presence of extensive systems of polar stratospheric clouds. The data also showed the evolution of the chlorine and nitrogen chemistry within the Arctic vortex. A navigational computer code was improved so that the DC-8 navigators could perform their function more efficiently.

Toon, Owen B.↗

Long-Term Space Astrophysics Program

This is the final report for our Long-Term Space Astrophysics Program (NRA 94-OSS-12) grant NAG 5-3225. The proposal is entitled 'Spectral and Temporal Properties of Black Hole Candidates', and began funding in May 1995, and ran through 31 Aug 2000. The project summary from the original proposal was as follows: 'We will study the spectral and temporal properties of black hole candidates (BHC) by using data from archival sources (e.g., EXOSAT, Ginga, ROSAT) and proposed follow-up observations with modern instruments (e.g., ASCA, XTE). Our spectral studies will focus on identifying the basic characteristics and luminosities of the emission components in the various 'states' of BHC. We hope to understand and quantify the global energetics of these states. Our temporal studies will focus on expanding and classifying our knowledge of BHC variability properties in each state. We will explore the nature of quasi-periodic oscillations in BHC. We will combine our spectral and temporal studies by analyzing time lags and variability coherence between energy channels. In addition, we will investigate ways of correlating observed variability behavior with specific emission components.' We have accomplished many of these goals laid out within the original proposal. As originally proposed, we have utilized both archival and proprietary satellite data. In terms of archival data, we have utilized data from the Advanced Satellite for Cosmology and Astrophysics (ASCA), ROSAT, and the Rossi X-ray Timing Explorer (RXTE). We also obtained proprietary data from ASCA, RXTE, and the Extreme Ultraviolet Explorer (EUVE). In terms of sources, we have examined a wide variety of both galactic black hole candidates and extra-galactic black holes. For the galactic black holes we have observed and analyzed both the low/hard state and the high/soft state. We have performed both spectral and timing analyses on all of these objects. In addition, we have also examined a number of neutron stars or potential neutron stars. All of our research on the above mentioned objects has resulted in one or more publications in peer-reviewed journals. Attached is a list of refereed publications of research results which have been funded by this grant over approximately the past five and a half years. In addition, we have included a list of conference proceedings and other similar reports that have been associated with this grant.

Nowark, Michael A.↗

Toward a Common Earth Data Publication Framework

Data publication is an essential activity for all data archives. Each of NASA's twelve Distributed Active Archive Centers (DAACs) have established publication workflows which account for the heterogeneous suite of missions, instruments, data providers, and datasets managed within the Earth Observation System Data and Information System (EOSDIS) program. Some aspects of data publication vary across DAACs: workflows range from manual to automatic, terms used to describe publication elements differ, and systems used to publish and manage data vary. Despite these differences, the DAAC data publication processes are generally the same: obtain the data and related information from data providers, describe the data with metadata and documentation, and release the data for access by the user community. In order to improve consistency and reduce the time required to publish data, we have developed a cross-DAAC initiative called the Common Earthdata Publication Framework (Earthdata Pub). Earthdata Pub seeks to: standardize communications and interactions with data providers; identify and standardize common workflows and steps in the data publication process; and design/implement a front-end system with features that include a common web interface, email & status tracking, and common application programming interfaces (APIs) to communicate with various DAAC-specific software components (services and applications) on the back-end. We will present the latest updates on this effort's progress and future plans.

data publication↗

Near 40 Years MERRA-2 Data at NASA GES DISC -Opportunity and Challenge to Support Extremes Study

To the end of 2019, 40 years NASA climate reanalysis data sets from the Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) will be available at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 consists atmosphere, land, and ocean data, which may be used for the studies ranging from the short scale weather events to the large scale decadal vulnerabilities. The hourly products, such as precipitation, soil moisture, temperature, and aerosols etc., have been used widely to study extreme events.In supporting users from broad communities, GES DISC have developed various data access services, including subsetter for downloading only data of interest with preferred format; OPeNDAP - for machine-to-machine data access; and Giovanni- for online visualization and analysis, etc. A big challenge for extreme study is to downloading and processing long-term hourly or daily data. The data downloading performance is not very satisfied by many users with current services and the native archived data structure. Late June 2019, many people in Europe had experienced extreme heat waves. The temperatures in several countries exceeded 40°C (104°F). For example, MERRA-2 shows that the near surface daily maximum temperature of June 28 2019 over Marseille, a city in southern France, reached 41.1 °C (106°F), which is the record breaking temperature in the last 40 years. GES DISC is working together with domain science experts to improve the performance of long time series access, making analysis ready data sets in supporting application researches, such as extreme study. In this presentation, using Europe heat wave as an example, we will show prototype of the in developing service for finding extremes from near 40 years MERRA-2 data at a given location. MERRA-2 data can be accessed from NASA GES DISC(https://disc.gsfc.nasa.gov/ ) by search keyword "MERRA-2".

Shen, Suhung↗

Data Quality Challenges for Analysis Ready Data (ARD)

Data quality plays a critical role in research and applications. The Earth Science Information Partners (ESIP) Information Quality Cluster (IQC) defines four aspects of information quality: Science, Product, Stewardship, and Services. The ESIP IQC has become internationally recognized as an authoritative and responsive resource of information and guidance to data producers and distributors on how to implement data quality standards and best practices for their science data systems, datasets, and data/metadata dissemination services. In recent years, cloud computing environments have provided scale-up capabilities such as data archives and services, enabling interdisciplinary science and applications. More value-added products are expected from data service providers, including Analysis Ready Data (ARD). ARD refers to data that has been preprocessed into a form that allows immediate analysis by the end user, processed to a minimum set of requirements and provides interoperability over time and across multiple datasets. Once a dataset has been developed from its original form to produce ARD, what quality characteristics should the derived dataset or ARD possess? Also, is it safe to assume that the quality of the ARD is consistent with the quality of the source data, or are there special attributes to an ARD that would warrant a secondary, independent quality assessment? What provenance (also called “data lineage”) information needs to be included in ARD? It is important to answer these questions, especially given the ease of use of ARD, and the consequent temptation by users to trust ARD without understanding the limitations or possible variations in quality compared to the source data. In this presentation, we will discuss data quality challenges for ARD products and services and introduce IQC for participation.

data quality↗

Intelligent Archives in the Context of Knowledge Building Systems: Concepts for the Future

The technical objectives are: 1. Formulate concepts and architectures that support data archiving for NASA science research and applications in the 10 to 20 year time frame. 2. Focus on architectural strategies that will support intelligent processes and functions. 3. Identify and characterize science and applications scenarios that drive intelligent archive requirements. 4. Assess technologies and research that will need the development of an intelligent archive. 5. Identify and characterize potential research projects that will be needed to develop and create an intelligent archive.

Ramapriyan, H. K.↗

Standardized Sky Partitioning for the Next Generation Astronomy and Space Science Archives

The Johns Hopkins University and Space Telescope Science Institute are working together on this project to develop a library of standard software for data archives that will benefit the wider astronomical community. The ultimate goal was to develop and distribute a software library aimed at providing a common system for partitioning and indexing the sky in manageable sized regions and provide complex queries on the objects stored in this system. Whilst ongoing maintenance work will continue the primary goal has been completed. Most of the next generation sky surveys in the different wavelengths like 2MASS, GALEX, SDSS, GSC-II, DPOSS and FIRST have agreed on this common set of utilities. In this final report, we summarize work on the work elements assigned to the STScI project team.

Lal, Nand↗

BindingDB in 2024: a FAIR knowledgebase of protein-small molecule binding data

Abstract BindingDB (bindingdb.org) is a public, web-accessible database of experimentally measured binding affinities between small molecules and proteins, which supports diverse applications including medicinal chemistry, biochemical pathway annotation, training of artificial intelligence models and computational chemistry methods development. This update reports significant growth and enhancements since our last review in 2016. Of note, the database now contains 2.9 million binding measurements spanning 1.3 million compounds and thousands of protein targets. This growth is largely attributable to our unique focus on curating data from US patents, which has yielded a substantial influx of novel binding data. Recent improvements include a remake of the website following responsive web design principles, enhanced search and filtering capabilities, new data download options and webservices and establishment of a long-term data archive replicated across dispersed sites. We also discuss BindingDB’s positioning relative to related resources, its open data sharing policies, insights gleaned from the dataset and plans for future growth and development.

Liu, Tiqing↗

Optical Particle Measurements during EPCAPE Field Campaign Report

This campaign requested the deployment of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility optical particle counter (OPC) at the first ARM Mobile Facility (AMF1) located at the Scripps Pier in La Jolla, California during the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE). The addition of the OPC was requested for two reasons. (1) Close the gap between the scanning mobility particle sizer (SMPS) and aerodynamic particle sizer (APS) size distribution from the Aerosol Observing System (AOS) measurements. (2) Principal investigator Petters has been working with Tracking Aerosol Convection Interaction Experiment (TRACER) data to compute particle fluxes from Doppler lidar (Petters et al. 2024). Briefly, backscatter flux is obtained using the eddy covariance technique using the Doppler vertical velocity and attenuated backscatter. Building upon prior studies, we were able to relate backscatter to particle number concentration by calibrating the lidar retrievals against optical particle counter-measured ground-based aerosol size distribution and radiosonde-interpolated relative humidity at lidar sample height. Performing similar analysis was of interest to EPCAPE to better understand the emissions and vertical transport of large particles into the overlying stratus clouds. However, as stated above, this analysis requires an optical size distribution that covers the 0.3-30-μm-diameter size range. The OPC was deployed between 2023-04-14 and 2024-02-14. The deployment, data quality analysis, and data archiving was handled by the DOE ARM instrument mentor team without additional involvement by the principal investigator. Data quality was marked as “routine” for the majority of the campaign.

54 ENVIRONMENTAL SCIENCES↗

Chandra Serendipitous and Cycle 1 Targeted Surveys

A team led by scientists at the Chandra X-ray Center (CXC, formally known as the AXAF Science Center) is developing plans for a Serendipitous Survey using a selected subset of Chandra observations starting with Cycle 1. This survey will include two parts: (1) for sources sufficiently bright to be identified in available sky surveys (V approximately < 21), probable optical identifications and related imaging data will be, provided with the X-ray data as part of the Chandra data products. (2) at fainter flux X-ray source identifications will be determined from publically available, archival data and new optical imaging observations. We estimate that this survey will yield approximately 2500 source identifications in Cycle 1 down to X-ray flux levels approximately 10(exp -15) erg/sq cm.s and covering an area of sky approximately 10 sq degs. Optical spectroscopy and radio imaging will also be obtained for a subset of these sources. We are exploring appropriate ways to involve interested Chandra observers as well as other scientists in this survey project. A general overview of the various surveys which comprise a portion of the Chandra Cycle 1 GTO and GO programs and are not covered elsewhere in these proceedings will also be presented.

Wilkes, Belinda↗

Toward a Virtual Solar Observatory: Starting Before the Petabytes Fall

Although a few, large, space- and groundbased solar physics databases exist at selected locations, there is as yet only limited standardization or interoperability. I describe the outline of a plan to facilitate access to a distributed network of online solar data archives, both large and small. The underlying principle is that the user need not know where- the data are, only how to specify which data are desired. At the least, such an approach could considerably simplify the scientific user's access to the enormous amount of solar physics data to be obtained in the next decade. At best, it might mean the withering away of traditional data centers, and all the bureaucracy they entail. This work is supported by the Sun-Earth Connections Division of NASA Office of Space Science, thanks to an anomalous act of largess on the part of the 2001 SEC Senior Review.

Gurman, Joseph↗

TPSAS-NF1676L-17867-DND

In response to the exponential growth in science data analysis and visualization capabilities, data centers have been developing new processes to package and deliver large volumes of aggregated subsets of archived data. New standards are evolving to help data providers and application programmers manage the growing needs of the science community. These standards evolve from the best practices gleaned from new products and capabilities. The NASA Atmospheric Sciences Data Center (ASDC) has developed and deployed production provider-specific search and subset web applications for the CALIPSO, CERES, TES, and MOPITT missions. This presentation explores a CERES CCCM (CALIPSO, CloudSat, CERES, MODIS) data validation use case that leverages aggregated subset results from CERES CCCM (Level2), CERES SSF (Level2), and CALIPSO LIDAR (Level) datasets. Additionally, it examines the standards and formats that ASDC developers have applied to the delivered files as well as the implementation strategies for subsetting and processing the aggregated products.

Walter E Baskin↗

Evaluation of DVD-R for Archival Applications

For more than a decade, CD-ROM and CD-R have provided an unprecedented level of reliability, low cost and cross-platform compatibility to support federal data archiving and distribution efforts. However, it should be remembered that years of effort were required to achieve the standardization that has supported the growth of the CD industry. Incompatibilities in the interpretation of the ISO-9660 standard on different operating systems had to be dealt with, and the imprecise specifications in the Orange Book Part n and Part Hi led to incompatibilities between CD-R media and CD-R recorders. Some of these issues were presented by the authors at Optical Data Storage '95. The major current problem with the use of CD technology is the growing volume of digital data that needs to be stored. CD-ROM collections of hundreds of volumes and CD-R collections of several thousand volumes are becoming almost too cumbersome to be useful. The emergence of Digital Video Disks Recorder (DVD-R) technology promises to reduce the number of discs required for archive applications by a factor of seven while providing improved reliability. It is important to identify problem areas for DVD-R media and provide guidelines to manufacturers, file system developers and users in order to provide reliable data storage and interchange. The Data Distribution Laboratory (DDL) at NASA's Jet Propulsion Laboratory began its evaluation of DVD-R technology in early 1998. The initial plan was to obtain a DVD-Recorder for preliminary testing, deploy reader hardware to user sites for compatibility testing, evaluate the quality and longevity of DVD-R media and develop proof-of-concept archive collections to test the reliability and usability of DVD-R media and jukebox hardware.

Martin, Michael D.↗

Aggregation Tool to Create Curated Data albums to Support Disaster Recovery and Response

Despite advances in science and technology of prediction and simulation of natural hazards, losses incurred due to natural disasters keep growing every year. Natural disasters cause more economic losses as compared to anthropogenic disasters. Economic losses due to natural hazards are estimated to be around $6-$10 billion dollars annually for the U.S. and this number keeps increasing every year. This increase has been attributed to population growth and migration to more hazard prone locations such as coasts. As this trend continues, in concert with shifts in weather patterns caused by climate change, it is anticipated that losses associated with natural disasters will keep growing substantially. One of challenges disaster response and recovery analysts face is to quickly find, access and utilize a vast variety of relevant geospatial data collected by different federal agencies such as DoD, NASA, NOAA, EPA, USGS etc. Some examples of these data sets include high spatio-temporal resolution multi/hyperspectral satellite imagery, model prediction outputs from weather models, latest radar scans, measurements from an array of sensor networks such as Integrated Ocean Observing System etc. More often analysts may be familiar with limited, but specific datasets and are often unaware of or unfamiliar with a large quantity of other useful resources. Finding airborne or satellite data useful to a natural disaster event often requires a time consuming search through web pages and data archives. Additional information related to damages, deaths, and injuries requires extensive online searches for news reports and official report summaries. An analyst must also sift through vast amounts of potentially useful digital information captured by the general public such as geo-tagged photos, videos and real time damage updates within twitter feeds. Collecting and aggregating these information fragments can provide useful information in assessing damage in real time and help direct recovery efforts. The search process for the analyst could be made much more efficient and productive if a tool could go beyond a typical search engine and provide not just links to web sites but actual links to specific data relevant to the natural disaster, parse unstructured reports for useful information nuggets, as well as gather other related reports, summaries, news stories, and images. This presentation will describe a semantic aggregation tool developed to address similar problem for Earth Science researchers. This tool provides automated curation, and creates "Data Albums" to support case studies. The generated "Data Albums" are compiled collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; information about the event contained in news reports, and images or videos to supplement research analysis. An ontology-based relevancy-ranking algorithm drives the curation of relevant data sets for a given event. This tool is now being used to generate a catalog of Hurricane Case Studies at Global Hydrology Resource Center (GHRC), one of NASA's Distribute Active Archive Centers. Another instance of the Data Albums tool is currently being created in collaboration with NASA/MSFC's SPoRT Center, which conducts research on unique NASA products and capabilities that can be transitioned to the operational community to solve forecast problems. This new instance focuses on severe weather to support SPoRT researchers in their model evaluation studies

Ramachandran, Rahul↗

GammaCore: The Compton Observatory research environment

The Compton Observatory Science Support Center (COSSC) is developing a coherent analysis environment for the analysis of Compton and other gamma-ray astronomy data. This environment, GammaCore, allows the astronomer to access the data analysis systems developed at the Principal Investigator (PI) sites for the four Compton Observatory instruments. In addition users have access to standard astronomical tools such as IRAF, IDL, and XANADU. The user interface of GammaCore is the AGCL (AnswerGarden Command Language), developed at the AXAF Science Center. The parameter interface supported by the AGCL allows GammaCore to access all PI software systems in a uniform fashion. These systems are quite different, having been developed independently on heterogeneous systems without much concern for general portability. The data kibitzer concept, where a window running in a specific PI environment is controlled by the AGCL, has been used extensively. Users can choose to view what is going on in the native environment, to use the window to control PI software directly, or to ignore the PI systems entirely and to work only through the homogeneous AGCL interface. Software developed at the COSSC is also integrated within GammaCore. Extensive facilities for conversions of PI data formats to and from FITS have been developed. Access to the Compton data archive and catalogs will also be completely integrated with the GammaCore. Users can retrieve any publicly available Compton data. This paper examines the issues that have arisen in attempting to meld these widely diverse systems. The advantages and limitations of the parameter interface and the kibitzer are discussed along with issues of data portability, documentation, and the feasibility of multi-instrument analysis. Limited capabilities are now available within GammaCore with significant enhancements planned over the coming year. An implementation including all PI systems will be available within that time. Instructions on how to access GammaCore and how to get more information are given.

Mcglynn, T. A.↗

Online Visualization and Analysis of NASA Satellite-Based Global and Regional Precipitation Products Through Giovanni

Observational data are essential for Earth science research and applications. Traditional ground-based observations suffer from many limitations (e.g. costly deployment). As a result, data are often sparse and inconsistent, especially over vast oceans that cover nearly 71% of the Earth's surface, and for remote continents. Precipitation is one of the important physical parameters in the global hydrological cycle and other disciplines. Each year, severe floods and droughts happen in different parts of the world and cause significant damage to the economy, as well as human casualties (e.g. Hurricane Katrina, the Dust Bowl). Accurate and timely precipitation observations and predictions are important for research and applications. However, ground-based precipitation observations are quite limited, especially in remote and mountainous regions. Since the satellite era began, satellite-based precipitation products have gained popularity in Earth science research, applications, and education. Accessing satellite products can be a daunting task to many users, especially those who do not have prior experience or knowledge with satellite data. Recognizing this obstacle, the NASA Goddard Earth Sciences and Data and Information Services Center (GES DISC), home to data archives for the NASA-JAXA Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM), has developed data services including an online visualization and analysis tool, Giovanni (the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure), enabling users at different levels to access, explore, and evaluate NASA satellite-based data products without downloading either data and software, or requiring coding. Currently, global and regional precipitation products from different satellite missions (TRMM, GPM) and projects (e.g. the Modern Era Retrospective-analysis for Research and Applications Version 2 (MERRA-2), and the North American Land Data Assimilation System (NLDAS)), ranging from half-hourly to monthly temporal resolution, are available in Giovanni. There are over 1900 variables in Giovanni, covering measurements in precipitation, hydrology, atmospheric dynamics, atmospheric chemistry, etc. In this poster presentation, we will provide a live demonstration of Giovanni and its latest development, including precipitation-related variables, and new basic features such as polar projections. The session will also provide a Q&A opportunity for attendees.

Giovanni↗

Expanding Repository Data Available For Sharing and Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

Biology↗