Improving Access to NASA's Earth Science Data through Collaborative Metadata Curation
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NASA's Earth Observing System Data and Information System (EOSDIS) has been working towards a vision of a cloud-based, highly-flexible, ingest, archive, management, and distribution system for its ever-growing and evolving data holdings. This system, Cumulus, is emerging from its prototyping stages and is poised to make a huge impact on how NASA manages and disseminates its Earth science data. This talk will outline the motivation for this work, present the achievements and hurdles of the past 18 months and will chart a course for the future expansion of the Cumulus expansion. We will explore on not just the technical, but also the socio-technical challenges that we face in evolving a system of this magnitude into the cloud and how we are rising to meet those challenges through open collaboration and intentional stakeholder engagement.
Growing collection of NASA Earth science data is archived and distributed by EOSDIS’s 12 Distributed Active Archive Centers (DAACs). Each collection and granule is described by a metadata record housed in the Common Metadata Repository (CMR). Multiple metadata standards are in use, and core elements of each are mapped to and from a common model – the Unified Metadata Model (UMM). Work done by the Analysis and Review of CMR (ARC) Team.
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.
NASAs Earth Science Data System (ESDS) Program serves as a central cog in order to facilitate the implementation of NASA's Earth Science strategic plan. Since 1994, the ESDS Program has committed to the full and open sharing of Earth science data obtained from NASA instruments to all users. One of the key responsibilities of the ESDS Program is to continuously evolve the entire data and information system to maximize returns on the collected NASA data. An independent review was conducted in 2015 to holistically review the EOSDIS in order to identify gaps. The review recommendations were to investigate two areas: one, whether commercial cloud providers offer potential for storage, processing, and operational efficiencies, and two, the potential development of new data access and analysis paradigms. In response, ESDS has initiated several prototypes investigating the advantages and risks of leveraging cloud computing. This paper describes one such prototyping activity named Cumulus. Cumulus is being designed and developed as a "native" cloud-based data ingest, archive and management system that can be used for all future NASA Earth science data streams. Cumulus will foster design of new analysisvisualization tools that can leverage collocated data from all of the distributed DAACs as well as elastic cloud computing resources.
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. The data collected by NASA represent a significant public investment in research. Consequently, NASA developed a free, open and non-discriminatory policy consistent with existing international policies to maximize access to data. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, geodesy, atmosphere dynamics and composition, and inter-disciplinary research, and many others.
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. The data collected by NASA represent a significant public investment in research. Consequently, NASA developed a free, open and non-discriminatory policy consistent with existing international policies to maximize access to data. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, geodesy, atmosphere dynamics and composition, and inter-disciplinary research, and many others. This presentation will discuss data stewardship and archive activities.
Presentation of the Earth Science Data Systems Program major components. Will discuss EOSDIS, data system evolution, standards and interoperability and the IMPACT team.
The ARC Project: The ARC Team located at NASA’s Marshall Space Flight Center conducts quality assessments of metadata records that catalog NASA’s collection of over 9,000 Earth observation data products, stored in a centralized database called the Common Metadata Repository (CMR). The ARC Team has developed a metadata quality assessment framework to evaluate metadata completeness, correctness, and consistency with the goal of making NASA’s data products more discoverable, accessible, and usable. ARC = Analysis and Review of the CMR
The International Space Station is a valuable platform for research in space, but the benefits are limited if research is only conducted by individual countries. Through the efforts of the ISS Program Science Forum, international science working groups, and interagency cooperation, international collaboration on the ISS has expanded as ISS utilization has matured. Members of science teams benefit from working with counterparts in other countries. Scientists and institutions bring years of experience and specialized expertise to collaborative investigations, leading to new perspectives and approaches to scientific challenges. Combining new ideas and historical results brings synergy and improved peer-reviewed scientific methods and results. World-class research facilities can be expensive and logistically complicated, jeopardizing their full utilization. Experiments that would be prohibitively expensive for a single country can be achieved through contributions of resources from two or more countries, such as crew time, up- and down mass, and experiment hardware. Cooperation also avoids duplication of experiments and hardware among agencies. Biomedical experiments can be completed earlier if astronauts or cosmonauts from multiple agencies participate. Countries responding to natural disasters benefit from ISS imagery assets, even if the country has no space agency of its own. Students around the world participate in ISS educational opportunities, and work with students in other countries, through open curriculum packages and through international competitions. Even experiments conducted by a single country can benefit scientists around the world, through specimen sharing programs and publicly accessible "open data" repositories. For ISS data, these repositories include GeneLab, the Physical Science Informatics System, and different Earth data systems. Scientists can conduct new research using ISS data without having to launch and execute their own experiments. Multilateral collections of research results publications, maintained by the ISS international partnership and accessible via nasa.gov, make ISS results available worldwide, and encourage new users, ideas and research.
Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. At the NASA Marshall Space Flight Center (MSFC), the Data Science and Informatics Group (DSIG) has been using deep learning for a variety of Earth science applications. This paper provides examples of the applications and also addresses some of the challenges that were encountered.
In 1997 the Office of Biological Informatics and Outreach (OBIO), Biological Resources Division, US Geological Survey and NASA, Office of Earth Science (OES), initiated a coordinated effort for applying Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data and analysis, as a technology transfer project, to critical DOI environmental issues in four study sites throughout the United States. This work was accomplished by four US Department of the Interior (DOI) study teams with support from NASA/OES principal investigators and the Office of Earth Science programs. The studies, including personnel, objectives, background, project plans, and milestones were documented in a project website at . This report summarizes the final outcomes of the project, detailing accomplishments, lessons learned, and benefits realized to NASA, the US Geological Survey, and the participating DOI bureaus.
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Artisanal and small-scale gold mining (ASGM) is responsible for a large fraction of deforestation and disturbance in Amazonia. These activities cause severe impacts on the rainforest ecosystem and socioeconomic state of the region. NASA DEVELOP partnered with the Asociación para la Conservación de la Cuenca Amazónica (ACCA), NASA SERVIR Science Coordination Office, and the Spatial Informatics Group to enhance ASGM-related deforestation detection methods. ACCA currently uses the Omnibus Q-test Change Point Detection Algorithm to identify changes in Synthetic Aperture Radar (SAR) monthly-aggregated temporal data from the Sentinel-1 satellite. The team determined the algorithm's accuracy by comparing a stratified random sample of change points against data from January 2019 to June 2020 identified using PlanetScope and Landsat 8 Operational Land Imager (OLI) Earth observations through Collect Earth Online. Our results indicated a users' accuracy of 55% for temporal change detection and producer's and user's accuracies of 99% and 97%, respectively, for detecting when change did not occur. Of the labeled change points, only 19% were due to mining activity. This research can help our partners have a more accurate understanding of where illegal gold mining may be taking place and inform decisions to remediate this activity.
Artisanal and small-scale gold mining (ASGM) is responsible for a large fraction of deforestation and disturbance in Amazonia. These activities cause severe impacts on the rainforest ecosystem and socioeconomic state of the region. NASA DEVELOP partnered with the Asociación para la Conservación de la Cuenca Amazónica (ACCA), NASA SERVIR Science Coordination Office, and the Spatial Informatics Group to enhance ASGM-related deforestation detection methods. ACCA currently uses the Omnibus Q-test Change Point Detection Algorithm to identify changes in Synthetic Aperture Radar (SAR) monthly-aggregated temporal data from the Sentinel-1 satellite. The team determined the algorithm's accuracy by comparing a stratified random sample of change points against data from January 2019 to June 2020 identified using PlanetScope and Landsat 8 Operational Land Imager (OLI) Earth observations through Collect Earth Online. Our results indicated a users' accuracy of 55% for temporal change detection and producer's and user's accuracies of 99% and 97%, respectively, for detecting when change did not occur. Of the labeled change points, only 19% were due to mining activity. This research can help our partners have a more accurate understanding of where illegal gold mining may be taking place and inform decisions to remediate this activity.
Title: Warming Permafrost Model Intercomparision Project (WrPMIP): Pan-Arctic Perturbation Warming Simulations Description: WrPMIP Pan-Arctic simulations including historial baseline and two warming simulations. Models were perturbed similarly to known experimental warming trials that have been implemented across the Pan-Arctic over the last several decades. More information about the dataset can be found at the following links: https://warmingpermafrost.nau.edu/ The dataset is available at: https://esgf-node.ornl.gov/search/project=WrPMIP&mip_era=CMIP6&activity_id=WrPMIP
The Astromaterials Acquisition and Curation Office at NASA's Johnson Space Center (JSC) is the designated facility for curating all of NASA's extraterrestrial samples. The suite of collections includes the lunar samples from the Apollo missions, cosmic dust particles falling into the Earth's atmosphere, meteorites collected in Antarctica, comet and interstellar dust particles from the Stardust mission, asteroid particles from the Japanese Hayabusa mission, and solar wind atoms collected during the Genesis mission. To support planetary science research on these samples, NASA's Astromaterials Curation Office hosts the Astromaterials Curation Digital Repository, which provides descriptions of the missions and collections, and critical information about each individual sample. Our office is implementing several informatics initiatives with the goal of better serving the planetary research community. One of these initiatives aims to increase the availability and discoverability of sample data and images through the use of a newly designed common architecture for Astromaterials Curation databases.
(1) Goal: The scientific objective to the proposed research is to develop a proto-type downscaled (<1 km) version of the root-zone soil moisture product called SoilMERGE or SMERGE. This objective is linked as root zone soil moisture is a critical climate variable that has a more direct influence on plant growth than precipitation. Therefore, the developed downscaled version of SMERGE can be used as input into biodiversity informatic techniques (i.e., maximum entropy modeling) Development of downscaled SMERGE will be facilitated by Department of Energy (DOE) resources specifically data from the DOE Atmospheric Radiation Measurement (ARM) facility and modeling platforms such as the Energy Exascale Earth System Model (E3SM).