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At least 73 records · Page 4

Atmospheric Data-Driven Visualization of Air Quality Variation in Megacities

The growth and spread of human settlements and increasing urban density are important processes in global change. Urbanization has accelerated with population growth, and more densely populated urban areas have major effects on the local and regional environments. Air quality in megacities has been a concern for decades. Data for anthropogenic emissions, pollutants, and particulate matter can inform research on the interactions between urban landscapes and the atmosphere, assist policy makers in developing sustainable, healthy environments, and inform the general public. To better assist researchers, students, the public, and policymakers in understanding the annual and seasonal variation of aerosol and gas intensity in megacities, the Science Outreach Team at NASA Langley Research Center’s Atmospheric Science Data Center (ASDC) Distributed Active Archive Center (DAAC) demonstrate data products at the ASDC that can be used to visualize these parameters. The presentation uses data from the ASDC-supported NASA missions Measurements Of Pollution In The Troposphere (MOPITT), Cloud-Aerosol and Infrared Pathfinder Satellite Observation (CALIPSO), Tropospheric Emission Spectrometer (TES), and Multi-angle Imaging Spectro Radiometer (MISR)

Air Quality↗

Improving Data Discovery, Analysis, and Visualizations With Cloud-Based User Services

The Global Hydrometeorology Resource Center (GHRC) Distributed Active Archive Center (DAAC) is one of 12 DAACs managed by the United States National Aeronautics and Space Administration (NASA) Earth Science Data and Information System (ESDIS) project [1]. GHRC and the other DAACs are designed to process, archive, document, and distribute NASA Earth-observing data, ranging from satellite missions to field campaigns [2]. A major goal of the DAACs is to enable science with these data. Science enabling can be difficult as datasets can be very large, use multiple formats, come from numerous platforms, and require three-dimensional visualization. GHRC is using its expertise with cloud-based technologies to develop open source and open science tools to empower users to explore, coincidentally visualize, and analyze multiple datasets. Being open source, the user community can develop visualizations for their own datasets. This presentation will expand on this objective and highlight the capabilities available to the international community now.

GHRC↗

Automated Metadata Scoring Approaches for Earth Observation Data

The Common Metadata Repository (CMR) contains metadata records describing NASA’s Earth observation data products which are archived across 12 data centers also known as Distributed Active Archive Centers (DAACs). To ensure that NASA’s data is discoverable, accessible, and usable, the Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, assesses the quality of these metadata records. The ARC team currently uses a combination of automated and manual methods to check metadata records for quality dimensions such as completeness, correctness, and consistency. In addition to these quality assessments, the team is currently exploring various metadata scoring methods in order to provide normalized results across the twelve DAACs. This method is conducted by using automated methods to assess metadata fields and then provide a numeric score, or grade, based on the analysis. To implement this process, two different approaches have been theorized and are currently being explored by the ARC team. This presentation will describe ARC's two proposed methodologies in more detail, and the pros and cons to using these metadata scoring methods.

Jenny Wood↗

Stewardship of NASA's Earth Science Data and Ensuring Long-Term Active Archives

Program, NASA has followed an open data policy, with non-discriminatory access to data with no period of exclusive access. NASA has well-established processes for assigning and or accepting datasets into one of 12 Distributed Active Archive Centers (DAACs) that are parts of EOSDIS. EOSDIS has been evolving through several information technology cycles, adapting to hardware and software changes in the commercial sector. NASA is responsible for maintaining Earth science data as long as users are interested in using them for research and applications, which is well beyond the life of the data gathering missions. For science data to remain useful over long periods of time, steps must be taken to preserve: (1) Data bits with no corruption, (2) Discoverability and access, (3) Readability, (4) Understandability, (5) Usability' and (6). Reproducibility of results. NASAs Earth Science data and Information System (ESDIS) Project, along with the 12 EOSDIS Distributed Active Archive Centers (DAACs), has made significant progress in each of these areas over the last decade, and continues to evolve its active archive capabilities. Particular attention is being paid in recent years to ensure that the datasets are published in an easily accessible and citable manner through a unified metadata model, a common metadata repository (CMR), a coherent view through the earthdata.gov website, and assignment of Digital Object Identifiers (DOI) with well-designed landing product information pages.

Data Management↗

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↗

EOS MLS Science Data Processing System: A Description of Architecture and Capabilities

This paper describes the architecture and capabilities of the Science Data Processing System (SDPS) for the EOS MLS. The SDPS consists of two major components--the Science Computing Facility and the Science Investigator-led Processing System. The Science Computing Facility provides the facilities for the EOS MLS Science Team to perform the functions of scientific algorithm development, processing software development, quality control of data products, and scientific analyses. The Science Investigator-led Processing System processes and reprocesses the science data for the entire mission and delivers the data products to the Science Computing Facility and to the Goddard Space Flight Center Earth Science Distributed Active Archive Center, which archives and distributes the standard science products.

Microwave Limb Sounder (MLS)↗

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↗

A data and information system for processing, archival, and distribution of data for global change research

Work on this project was focused on information management techniques for Marshall Space Flight Center's EOSDIS Version 0 Distributed Active Archive Center (DAAC). The centerpiece of this effort has been participation in EOSDIS catalog interoperability research, the result of which is a distributed Information Management System (IMS) allowing the user to query the inventories of all the DAAC's from a single user interface. UAH has provided the MSFC DAAC database server for the distributed IMS, and has contributed to definition and development of the browse image display capabilities in the system's user interface. Another important area of research has been in generating value-based metadata through data mining. In addition, information management applications for local inventory and archive management, and for tracking data orders were provided.

Graves, Sara J.↗

Proto-Examples of Data Access and Visualization Components of a Potential Cloud-Based GEOSS-AI System

Once a research or application problem has been identified, one logical next step is to search for available relevant data products. Thus, an early component of a potential GEOSS-AI system, in the continuum between observations and end point research, applications, and decision making, would be one that enables transparent data discovery and access by users. Such a component might be effected via the systems data agents. Presumably, some kind of data cataloging has already been implemented, e.g., in the GEOSS Common Infrastructure (GCI). Both the agents and cataloging could also leverage existing resources external to the system. The system would have some means to accept and integrate user-contributed agents. The need or desirability for some data format internal to the system should be evaluated. Another early component would be one that facilitates browsing visualization of the data, as well as some basic analyses.Three ongoing projects at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provide possible proto-examples of potential data access and visualization components of a cloud-based GEOSS-AI system. 1. Reorganizing data archived as time-step arrays to point-time series (data rods), as well as leveraging the NASA Simple Subset Wizard (SSW), to significantly increase the number of data products available, at multiple NASA data centers, for production as on-the-fly (virtual) data rods. SSWs data discovery is based on OpenSearch. Both pre-generated and virtual data rods are accessible via Web services. 2. Developing Web Feature Services to publish the metadata, and expose the locations, of pre-generated and virtual data rods in the GEOSS Portal and enable direct access of the data via Web services. SSW is also leveraged to increase the availability of both NASA and non-NASA data.3.Federating NASA Giovanni (Geospatial Interactive Online Visualization and Analysis Interface), for multi-sensor data exploration, that would allow each cooperating data center, currently the NASA Distributed Active Archive Centers (DAACs), to configure its own Giovanni deployment, while also allowing all the deployments to incorporate each others data. A federated Giovanni comprises Giovanni Virtual Machines, which can be run on local servers or in the cloud.

access↗

Tools and Data Services from the GSFC Earth Sciences DAAC for Aura Science Data Users

In these times of rapidly increasing amounts of archived data, tools and data services that manipulate data and uncover nuggets of information that potentially lead to scientific discovery are becoming more and more essential. The Goddard Space Flight Center (GSFC) Earth Sciences (GES) Distributed Active Archive Center (DAAC) has made great strides in facilitating science and applications research by, in consultation with its users, developing innovative tools and data services. That is, as data users become more sophisticated in their research and more savvy with information extraction methodologies, the GES DAAC has been responsive to this evolution. This presentation addresses the tools and data services available and under study at the GES DAAC, applied to the Earth sciences atmospheric data. Now, with the data from NASA's latest Atmospheric Chemistry mission, Aura, being readied for public release, GES DAAC tools, proven successful for past atmospheric science missions such as MODIS, AIRS, TRMM, TOMS, and UARS, provide an excellent basis for similar tools updated for the data from the Aura instruments. GES DAAC resident Aura data sets are from the Microwave Limb Sounder (MLS), Ozone Monitoring Instrument (OMI), and High Resolution Dynamics Limb Sounder (HIRDLS). Data obtained by these instruments afford researchers the opportunity to acquire accurate and continuous visualization and analysis, customized for Aura data, will facilitate the use and increase the usefulness of the new data. The Aura data, together with other heritage data at the GES DAAC, can potentially provide a long time series of data. GES DAAC tools will be discussed, as well as the GES DAAC Near Archive Data Mining (NADM) environment, the GIOVANNI on-line analysis tool, and rich data search and order services. Information can be found at: http://daac.gsfc.nasa.gov/upperatm/aura/. Additional information is contained in the original extended abstract.

Kempler, S.↗

The Importance of User Feedback in Sustaining Trusted Repositories

The NASA Earth Observation System Data and Information System (EOSDIS) has been operating since 1994 and is serving a global user community with well-managed Earth science data in a variety of scientific disciplines. EOSDIS processes, archives and distributes data and information products resulting from spaceborne and airborne instruments as well as in situ measurements from field campaigns. The Earth Science Data and Information System (ESDIS) Project at the NASA Goddard Space Flight Center manages EOSDIS with its 12 Distributed Active Archive Centers (DAACs) located across the United States. During the entire life of EOSDIS, the ESDIS Project and the DAACs have deployed many different mechanisms for user feedback, which have proven extremely valuable to their evolution and performance in their service to user communities. Some of the inputs from our user groups have resulted in fundamental changes in the architecture, design and operations of EOSDIS, while others have provided novel ideas for incremental changes. The EOSDIS DAACs have User Working Groups (UWGs) that represent broad user communities in the Earth science disciplines served by the DAACs. The UWGs meet periodically to assess and provide feedback on dataset and service priorities. As regular users of the data and services of the DAAC and experts in the scientific disciplines, the UWG members provide valuable inputs for planning and prioritizing the services, as well as addition of new datasets, for the benefit of the community. The EOSDIS is evaluated annually through an independently administered survey of its users resulting in the American Customer Satisfaction Index (ACSI). The survey provides an ACSI score as well as free-text suggestions from users, which are also helpful in making specific system improvements. In addition, each of the DAACs has a user services group that address on-going requests for help and other comments from users. The ESDIS Project has established a mechanism through the "earthdata" website (http://earthdata.nasa.gov) for users to provide feedback of any kind and these questions/comments are routed to the appropriate individuals in the Project or the DAACs. These various forms of receiving user feedback and responding to them continue to be extremely valuable in evolving and sustaining our Earth Science repository.

Behnke, Jeanne↗

NASA Remote Sensing Data in Earth Sciences: Processing, Archiving, Distribution, Applications at the GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of the major Distributed Active Archive Centers (DAACs) archiving and distributing remote sensing data from the NASA's Earth Observing System. In addition to providing just data, the GES DISC/DAAC has developed various value-adding processing services. A particularly useful service is data processing a t the DISC (i.e., close to the input data) with the users' algorithms. This can take a number of different forms: as a configuration-managed algorithm within the main processing stream; as a stand-alone program next to the on-line data storage; as build-it-yourself code within the Near-Archive Data Mining (NADM) system; or as an on-the-fly analysis with simple algorithms embedded into the web-based tools (to avoid downloading unnecessary all the data). The existing data management infrastructure at the GES DISC supports a wide spectrum of options: from data subsetting data spatially and/or by parameter to sophisticated on-line analysis tools, producing economies of scale and rapid time-to-deploy. Shifting processing and data management burden from users to the GES DISC, allows scientists to concentrate on science, while the GES DISC handles the data management and data processing at a lower cost. Several examples of successful partnerships with scientists in the area of data processing and mining are presented.

Leptoukh, Gregory G.↗

Global Data Assembly Center (GDAC) Report to the GHRSST Science Team

In 2012-2013 the Global Data Assembly Center (GDAC) at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) continued its role as the primary clearinghouse and access node for operational GHRSST data streams, as well as its collaborative role with the NOAA Long Term Stewardship and Reanalysis Facility (LTSRF) for archiving. Our presentation reported on our data management activities and infrastructure improvements since the last science team meeting in 2012.

user reports↗

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↗

Report on the Global Data Assembly Center (GDAC) to the 12th GHRSST Science Team Meeting

In 2010/2011 the Global Data Assembly Center (GDAC) at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) continued its role as the primary clearinghouse and access node for operational Group for High Resolution Sea Surface Temperature (GHRSST) datastreams, as well as its collaborative role with the NOAA Long Term Stewardship and Reanalysis Facility (LTSRF) for archiving. Here we report on our data management activities and infrastructure improvements since the last science team meeting in June 2010.These include the implementation of all GHRSST datastreams in the new PO.DAAC Data Management and Archive System (DMAS) for more reliable and timely data access. GHRSST dataset metadata are now stored in a new database that has made the maintenance and quality improvement of metadata fields more straightforward. A content management system for a revised suite of PO.DAAC web pages allows dynamic access to a subset of these metadata fields for enhanced dataset description as well as discovery through a faceted search mechanism from the perspective of the user. From the discovery and metadata standpoint the GDAC has also implemented the NASA version of the OpenSearch protocol for searching for GHRSST granules and developed a web service to generate ISO 19115-2 compliant metadata records. Furthermore, the GDAC has continued to implement a new suite of tools and services for GHRSST datastreams including a Level 2 subsetter known as Dataminer, a revised POET Level 3/4 subsetter and visualization tool, a Google Earth interface to selected daily global Level 2 and Level 4 data, and experimented with a THREDDS catalog of GHRSST data collections. Finally we will summarize the expanding user and data statistics, and other metrics that we have collected over the last year demonstrating the broad user community and applications that the GHRSST project continues to serve via the GDAC distribution mechanisms. This report also serves by extension to summarize the activities of the GHRSST Data Assembly and Systems Technical Advisory Group (DAS-TAG).

sea surface temperature (SST)↗

Earth observing system. Output data products and input requirements, version 2.0. Volume 3: Algorithm summary tables and non-EOS data products

Volume 3 assists Earth Observing System (EOS) investigators in locating required non-EOS data products by identifying their non-EOS input requirements and providing the information on data sets available at various Distributed Active Archive Centers (DAAC's), including those from Pathfinder Activities and Earth Probes. Volume 3 is intended to complement, not to duplicate, the the EOSDIS Science Data Plan (SDP) by providing detailed data set information which was not presented in the SDP. Section 9 of this volume discusses the algorithm summary tables containing information on retrieval algorithms, expected outputs and required input data. Section 10 describes the non-EOS input requirements of instrument teams and IDS investigators. Also described are the current and future data holdings of the original seven DAACS and data products planned from the future missions and projects including Earth Probes and Pathfinder Activities. Section 11 describes source of information used in compiling data set information presented in this volume. A list of data set attributes used to describe various data sets is presented in section 12 along with their descriptions. Finally, Section 13 presents the SPSO's future plan to improve this report .

Lu, Yun-Chi↗

Global Data Assembly Center (gdac) Report to the GHRSST Science Team

In 2019-2020 the Global Data Assembly Center (GDAC) at NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC) provided ingest, archive, distribution and user services for GHRSST operational data streams with improved and evolved tools, services, and tutorials, and interfaced with the user community to address technical inquiries. Several new GHRSST datasets including reprocessed MODIS Aqua/Terra L2P with improved cloud screening were made available. The PO.DAAC participated in the evolving GHRSST data management re architecture and development activities. GHRSST Science Team member Edward Armstrong assumed the role of co-leader of the CEOS SST Virtual Constellation. The following sections summarize and document the specific achievements of the GDAC to the GHRSST community.

Finch, Chris↗

Using OPeNDAP In The Cloud to Connect NASA Data Centers and Support Open Data Access

NASA DAACs (Distributed Active Archive Centers), including the Goddard Earth Sciences Data Information and Services Center (GES DISC), are currently transitioning from on-premises servers to a shared Earthdata Cloud in order to build more interoperability, cross-collaboration, and streamlined services between their data centers. Migrating its on-premises OPeNDAP service to the cloud is a critical component of making this interconnectedness between NASA DAACs possible. To improve their cloud services, GES DISC is leveraging open-source platforms like Github to collect user feedback, create use cases, and develop resources to enable real-time learning for users about OPeNDAP in the cloud. This presentation gives an overview of the OPeNDAP in the cloud, resources developed to access this service, and considerations for improved user guidance and experience to further support NASA's commitment to the Open-Source Science Initiative (OSSI).

Christopher Battisto↗