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NASA NTRS2011

Collaboration Portals for NASA's Airborne Field Campaigns

The University of Alabama in Huntsville (UAH), in collaboration with the Global Hydrology Resource Center, a NASA Earth Science Data Center, has provided information management for a number of NASA Airborne Field campaigns, both hurricane science investigations and satellite instrument validation. Effective field campaign management requires communication and coordination tools, including utilities for personnel to upload and share flight plans, weather forecasts, a variety of mission reports, preliminary science data, and personal photos. Beginning with the Genesis and Rapid Intensification Processes (GRIP) hurricane field campaign in 2010, we have provided these capabilities via a Drupal-based collaboration portal. This portal was reused and modified for the Midlatitude Continental Convective Clouds Experiment (MC3E), part of the Global Precipitation Measurement mission ground validation program. An end goal of these development efforts is the creation of a Drupal profile for field campaign management. This presentation will discuss experiences with Drupal in developing and using these collaboration portals. Topics will include Drupal modules used, advantages and disadvantages of working with Drupal in this context, and how the science teams used the portals in comparison with other communication and collaboration tools.

Conover, Helen↗

NASA NTRS1993

NASA space and Earth science data on CD-ROM

The National Space Science Data Center (NSSDC) is very interested in facilitating the widest possible use of the scientific data acquired through NASA spaceflight missions. Therefore, NSSDC has participated with projects and data management elements throughout the NASA science environment in the creation, archiving, and dissemination of data using Compact Disk-Read Only Memory (CD-ROM). This CD-ROM technology has the potential to enable the dissemination of very large data volumes at very low prices to a great many researchers, students and their teachers, and others. This catalog identifies and describes the scientific CD-ROM's now available from NSSDC including the following data sets: Einstein Observatory CD-ROM, Galileo Cruise Imaging on CD-ROM, International Halley Watch, IRAS Sky Survey Atlas, Infrared Thermal Mapper (IRTM), Magellan (MIDR), Magellan (ARCDR's), Magellan (GxDR's), Mars Digital Image Map (MDIM), Outer Planets Fields & Particles Data, Pre-Magellan, Selected Astronomical Catalogs, TOMS Gridded Ozone Data, TOMS Ozone Image Data, TOMS Update, Viking Orbiter Images of Mars, and Voyager Image.

Towheed, Syed S.↗

NASA NTRS2002

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Johnston, William E.↗

NASA NTRS2008

Automated Data Assimilation and Flight Planning for Multi-Platform Observation Missions

This is a progress report on an effort in which our goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few if any of these advanced techniques are currently being integrated into daily mission operations. Consequently, there are significant gaps in the knowledge that can be derived from the models and data that are used each day for guiding mission activities. The result can be sub-optimal observation plans, lack of useful data, and wasteful use of resources. Recent advances in data mining, machine learning, and planning make it feasible to migrate these technologies into the daily mission planning cycle. We describe the design of a closed loop system for data acquisition, processing, and flight planning that integrates the results of machine learning into the flight planning process.

Oza, Nikunj↗

NASA NTRS2017

NASA's EOSDIS, Trust and Certification

NASA's Earth Observing System Data and Information System (EOSDIS) has been in operation since August 1994, managing most of NASA's Earth science data from satellites, airborne sensors, filed campaigns and other activities. Having been designated by the Federal Government as a project responsible for production, archiving and distribution of these data through its Distributed Active Archive Centers (DAACs), the Earth Science Data and Information System Project (ESDIS) is responsible for EOSDIS, and is legally bound by the Office of Management and Budgets circular A-130, the Federal Records Act. It must follow the regulations of the National Institute of Standards and Technologies (NIST) and National Archive and Records Administration (NARA). It must also follow the NASA Procedural Requirement 7120.5 (NASA Space Flight Program and Project Management). All these ensure that the data centers managed by ESDIS are trustworthy from the point of view of efficient and effective operations as well as preservation of valuable data from NASA's missions. Additional factors contributing to this trust are an extensive set of internal and external reviews throughout the history of EOSDIS starting in the early 1990s. Many of these reviews have involved external groups of scientific and technological experts. Also, independent annual surveys of user satisfaction that measure and publish the American Customer Satisfaction Index (ACSI), where EOSDIS has scored consistently high marks since 2004, provide an additional measure of trustworthiness. In addition, through an effort initiated in 2012 at the request of NASA HQ, the ESDIS Project and 10 of 12 DAACs have been certified by the International Council for Science (ICSU) World Data System (WDS) and are members of the ICSUWDS. This presentation addresses questions such as pros and cons of the certification process, key outcomes and next steps regarding certification. Recently, the ICSUWDS and Data Seal of Approval (DSA) organizations merged their Core Trustworthy Data Repositories Requirements and require that members be recertified every three years. Given the rigor with which NASA manages the ESDIS Project and the DAACs, the recertification through WDSDSA, while involving some additional work, is a relatively simple process.

Certification↗

NASA NTRS2011

Framework for Integrating Science Data Processing Algorithms Into Process Control Systems

A software framework called PCS Task Wrapper is responsible for standardizing the setup, process initiation, execution, and file management tasks surrounding the execution of science data algorithms, which are referred to by NASA as Product Generation Executives (PGEs). PGEs codify a scientific algorithm, some step in the overall scientific process involved in a mission science workflow. The PCS Task Wrapper provides a stable operating environment to the underlying PGE during its execution lifecycle. If the PGE requires a file, or metadata regarding the file, the PCS Task Wrapper is responsible for delivering that information to the PGE in a manner that meets its requirements. If the PGE requires knowledge of upstream or downstream PGEs in a sequence of executions, that information is also made available. Finally, if information regarding disk space, or node information such as CPU availability, etc., is required, the PCS Task Wrapper provides this information to the underlying PGE. After this information is collected, the PGE is executed, and its output Product file and Metadata generation is managed via the PCS Task Wrapper framework. The innovation is responsible for marshalling output Products and Metadata back to a PCS File Management component for use in downstream data processing and pedigree. In support of this, the PCS Task Wrapper leverages the PCS Crawler Framework to ingest (during pipeline processing) the output Product files and Metadata produced by the PGE. The architectural components of the PCS Task Wrapper framework include PGE Task Instance, PGE Config File Builder, Config File Property Adder, Science PGE Config File Writer, and PCS Met file Writer. This innovative framework is really the unifying bridge between the execution of a step in the overall processing pipeline, and the available PCS component services as well as the information that they collectively manage.

Mattmann, Chris A.↗

NASA NTRS2018

Technologies and Methods Used at the Laboratory for Atmospheric and Space Physics (LASP) to Serve Solar Irradiance Data

The Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado in Boulder, USA operates the Solar Radiation and Climate Experiment (SORCE) NASA mission, as well as several other NASA spacecraft and instruments. Dozens of Solar Irradiance data sets are produced, managed, and disseminated to the science community. Data are made freely available to the scientific immediately after they are produced using a variety of data access interfaces, including the LASP Interactive Solar Irradiance Datacenter (LISIRD), which provides centralized access to a variety of solar irradiance data sets using both interactive and scriptable/programmatic methods. This poster highlights the key technological elements used for the NASA SORCE mission ground system to produce, manage, and disseminate data to the scientific community and facilitate long-term data stewardship. The poster presentation will convey designs, technological elements, practices and procedures, and software management processes used for SORCE and their relationship to data quality and data management standards, interoperability, NASA data policy, and community expectations.

Pankratz, Chris↗

NASA NTRS1992

Space Station Freedom data management system growth and evolution report

The Information Sciences Division at the NASA Ames Research Center has completed a 6-month study of portions of the Space Station Freedom Data Management System (DMS). This study looked at the present capabilities and future growth potential of the DMS, and the results are documented in this report. Issues have been raised that were discussed with the appropriate Johnson Space Center (JSC) management and Work Package-2 contractor organizations. Areas requiring additional study have been identified and suggestions for long-term upgrades have been proposed. This activity has allowed the Ames personnel to develop a rapport with the JSC civil service and contractor teams that does permit an independent check and balance technique for the DMS.

Bartlett, R.↗

DOE OSTI2023

CreelCat, a Catalog of United States Inland Creel and Angler Survey Data

The United States Inland Creel and Angler Survey Catalog (CreelCat) contains a national compilation of angler and creel survey data collected by natural resource management agencies across the United States (including Washington, D.C. and Puerto Rico). These surveys are used to help inform the management of recreational fisheries, by collecting information about anglers including what they are catching and harvesting, the amount of effort they expend, their angling preferences, and demographic information. As of May 1, 2023, CreelCat houses over 14,729 surveys from 33 states, Puerto Rico, and Washington, D.C., comprising 235 data fields across 8 tables. These tables contain 235,015 records of fish catch and harvest metrics, 27,250 angler preference metrics, 14,729 records of survey characteristics, 13,576 records of effort metrics, and 409 records of angler demographics. Though individual creel surveys are often deployed to meet local science and management objectives, creel data aggregated across jurisdictions has the potential to address larger scale research and management needs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Materials data science using CRADLE: A distributed, data-centric approach

Abstract There is a paradigm shift towards data-centric AI, where model efficacy relies on quality, unified data. The common research analytics and data lifecycle environment (CRADLE™) is an infrastructure and framework that supports a data-centric paradigm and materials data science at scale through heterogeneous data management, elastic scaling, and accessible interfaces. We demonstrate CRADLE’s capabilities through five materials science studies: phase identification in X-ray diffraction, defect segmentation in X-ray computed tomography, polymer crystallization analysis in atomic force microscopy, feature extraction from additive manufacturing, and geospatial data fusion. CRADLE catalyzes scalable, reproducible insights to transform how data is captured, stored, and analyzed. Graphical abstract

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2018

Subsetting Satellite Level 2 Data at NASA GES DISC

Working with Level 2 satellite swath data can prove challenging for many users. The variety of metadata, high resolution, and orbit-based nature of such data makes it difficult to acquire and manage. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has developed a general-purpose Level 2 Subsetting service that facilitates access to Level 2 data products. The Level 2 Subsetter enables users to sub-sample swath and gridded data in a variety of ways: by location (in a lat/lon box, within a circle of given radius, or at a specific point), by time (via swath segments or collections of granules), by any nonspatial dimension, or by selecting specific variables. The Level 2 Subsetting service also allows users to specify output data configuration and file format. In this presentation, we will detail and demonstrate the capabilities of this new service.

Huwe, Paul↗

DOE OSTI2024

DMTN-065: Data Management for LSST Special Programs

Special Programs are additional survey areas and/or observing strategies that are driven by specific science goals which build on, or are beyond, the core science pillars of the Wide Fast Deep Main Survey. In order to meet the requirements and enable science related to Special Programs, this document provides recommendations for Rubin Data Management regarding processing and serving data products for Special Programs. Hardware and processing boundaries on the potential diversity of data from Special Programs are discussed along with scenarios in which user-generated processing and data products might be needed to meet Special Programs' science goals.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRSDate not supplied

Overview of the NASA Earth Action Strategies Wildland Fire Initiative

As part of NASA’s new Earth Action strategy, the Wildland Fire initiative was established, which includes both the NASA Wildland Fire Program (WFP) and the FireSense project. NASA has over 50 years of experience generating data and technology to enhance fire science and operational management. The WFP’s mission is threefold: 1) assemble communities of practice through collaborative efforts with government, academia, and the private sector; 2) co-develop knowledge and applications with relevant partners and stakeholders in the wildfire community; and 3) improve wildland fire management through the transitioning of NASA data, technology, tools, and science to stakeholder organizations. The WFP is focusing on supporting proactive fire management, including situational awareness, preparedness, and risk mitigation. This will be accomplished through selected projects that identify management challenges, relevant to partners and end users, and the NASA data that will be utilized to deliver innovative solutions to enhance the management of wildland fires. Examples include: i) investigation of evaporative stress from OpenET to help predict the risk of wildfire occurrence in watersheds; ii) incorporation of space based LiDAR for the generation of 3-dimensional forest fuel metrics, used to improve wildfire risk and behavior models; iii) integration of global, multi-platform geostationary active-fire data in near-real-time into NASA’s Fire Information for Resource Management System (FIRMS); and iv) identification of post-fire ecohydrological conditions using thermal, multispectral, synthetic aperture radar (SAR), and hyperspectral remotely-sensed data to improve flood hazard forecast models. The FireSense project is a US-focused 5-year project that will focus on delivering NASA’s unique Earth science and technological capabilities to operational agencies, striving towards enhancing fire fighting and air quality management. The project will include airborne campaigns and new technology that will likely have global implications. Initial stakeholder engagement led FireSense to focus on four use-cases focused on the characterization and measurement of: (i) pre-fire fuels conditions, (ii) active fire-dynamics; (iii) post-fire impact and threats; and iv) air quality impacts and forecasting, each-developed with identified stakeholders.

Wildland Fire program↗

NASA NTRS1989

Integrating NASA's Land Analysis System (LAS) image processing software with an appropriate Geographic Information System (GIS): A review of candidates in the public domain

A user requirements analysis (URA) was undertaken to determine and appropriate public domain Geographic Information System (GIS) software package for potential integration with NASA's LAS (Land Analysis System) 5.0 image processing system. The necessity for a public domain system was underscored due to the perceived need for source code access and flexibility in tailoring the GIS system to the needs of a heterogenous group of end-users, and to specific constraints imposed by LAS and its user interface, Transportable Applications Executive (TAE). Subsequently, a review was conducted of a variety of public domain GIS candidates, including GRASS 3.0, MOSS, IEMIS, and two university-based packages, IDRISI and KBGIS. The review method was a modified version of the GIS evaluation process, development by the Federal Interagency Coordinating Committee on Digital Cartography. One IEMIS-derivative product, the ALBE (AirLand Battlefield Environment) GIS, emerged as the most promising candidate for integration with LAS. IEMIS (Integrated Emergency Management Information System) was developed by the Federal Emergency Management Agency (FEMA). ALBE GIS is currently under development at the Pacific Northwest Laboratory under contract with the U.S. Army Corps of Engineers' Engineering Topographic Laboratory (ETL). Accordingly, recommendations are offered with respect to a potential LAS/ALBE GIS linkage and with respect to further system enhancements, including coordination with the development of the Spatial Analysis and Modeling System (SAMS) GIS in Goddard's IDM (Intelligent Data Management) developments in Goddard's National Space Science Data Center.

Rochon, Gilbert L.↗

NASA NTRS2005

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.↗

NASA NTRS2007

Using Selection Pressure as an Asset to Develop Reusable, Adaptable Software Systems

The Goddard Earth Sciences Data and Information Services Center (GES DISC) at NASA has over the years developed and honed several reusable architectural components for supporting large-scale data centers with a large customer base. These include a processing system (S4PM) and an archive system (S4PA) based upon a workflow engine called the Simple Scalable Script based Science Processor (S4P) and an online data visualization and analysis system (Giovanni). These subsystems are currently reused internally in a variety of combinations to implement customized data management on behalf of instrument science teams and other science investigators. Some of these subsystems (S4P and S4PM) have also been reused by other data centers for operational science processing. Our experience has been that development and utilization of robust interoperable and reusable software systems can actually flourish in environments defined by heterogeneous commodity hardware systems the emphasis on value-added customer service and the continual goal for achieving higher cost efficiencies. The repeated internal reuse that is fostered by such an environment encourages and even forces changes to the software that make it more reusable and adaptable. Allowing and even encouraging such selective pressures to software development has been a key factor In the success of S4P and S4PM which are now available to the open source community under the NASA Open source Agreement

Berrick, Stephen↗

DOE OSTI2020

Plant science decadal vision 2020–2030: Reimagining the potential of plants for a healthy and sustainable future

Abstract Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2012

Frameworks Coordinate Scientific Data Management

Jet Propulsion Laboratory computer scientists developed a unique software framework to help NASA manage its massive amounts of science data. Through a partnership with the Apache Software Foundation of Forest Hill, Maryland, the technology is now available as an open-source solution and is in use by cancer researchers and pediatric hospitals.

Source record↗