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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2015

Architectures Toward Reusable Science Data Systems

Science Data Systems (SDS) comprise an important class of data processing systems that support product generation from remote sensors and in-situ observations. These systems enable research into new science data products, replication of experiments and verification of results. NASA has been building systems for satellite data processing since the first Earth observing satellites launched and is continuing development of systems to support NASA science research and NOAAs Earth observing satellite operations. The basic data processing workflows and scenarios continue to be valid for remote sensor observations research as well as for the complex multi-instrument operational satellite data systems being built today. System functions such as ingest, product generation and distribution need to be configured and performed in a consistent and repeatable way with an emphasis on scalability. This paper will examine the key architectural elements of several NASA satellite data processing systems currently in operation and under development that make them suitable for scaling and reuse. Examples of architectural elements that have become attractive include virtual machine environments, standard data product formats, metadata content and file naming, workflow and job management frameworks, data acquisition, search, and distribution protocols. By highlighting key elements and implementation experience we expect to find architectures that will outlast their original application and be readily adaptable for new applications. Concepts and principles are explored that lead to sound guidance for SDS developers and strategists.

Data Processing↗

NASA NTRS2014

Architectures Toward Reusable Science Data Systems

Data Processing↗

NASA NTRSDate not supplied

Open-Source Science-led Development of the Atmosphere Observing System (AOS) Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David Giles↗

NASA NTRS1989

The OMV Data Compression System Science Data Compression Workshop

The Video Compression Unit (VCU), Video Reconstruction Unit (VRU), theory and algorithms for implementation of Orbital Maneuvering Vehicle (OMV) source coding, docking mode, channel coding, error containment, and video tape preprocessed space imagery are presented in viewgraph format.

Lewis, Garton H., Jr.↗

NASA NTRS2015

NASA's Earth Science Data Systems

NASA's Earth Science Data Systems (ESDS) Program has evolved over the last two decades, and currently has several core and community components. Core components provide the basic operational capabilities to process, archive, manage and distribute data from NASA missions. Community components provide a path for peer-reviewed research in Earth Science Informatics to feed into the evolution of the core components. The Earth Observing System Data and Information System (EOSDIS) is a core component consisting of twelve Distributed Active Archive Centers (DAACs) and eight Science Investigator-led Processing Systems spread across the U.S. The presentation covers how the ESDS Program continues to evolve and benefits from as well as contributes to advances in Earth Science Informatics.

Data Systems↗

NASA NTRS1994

NASA Johnson Space Center Life Sciences Data System

The Life Sciences Project Division (LSPD) at JSC, which manages human life sciences flight experiments for the NASA Life Sciences Division, augmented its Life Sciences Data System (LSDS) in support of the Spacelab Life Sciences-2 (SLS-2) mission, October 1993. The LSDS is a portable ground system supporting Shuttle, Spacelab, and Mir based life sciences experiments. The LSDS supports acquisition, processing, display, and storage of real-time experiment telemetry in a workstation environment. The system may acquire digital or analog data, storing the data in experiment packet format. Data packets from any acquisition source are archived and meta-parameters are derived through the application of mathematical and logical operators. Parameters may be displayed in text and/or graphical form, or output to analog devices. Experiment data packets may be retransmitted through the network interface and database applications may be developed to support virtually any data packet format. The user interface provides menu- and icon-driven program control and the LSDS system can be integrated with other workstations to perform a variety of functions. The generic capabilities, adaptability, and ease of use make the LSDS a cost-effective solution to many experiment data processing requirements. The same system is used for experiment systems functional and integration tests, flight crew training sessions and mission simulations. In addition, the system has provided the infrastructure for the development of the JSC Life Sciences Data Archive System scheduled for completion in December 1994.

Rahman, Hasan↗

NASA NTRS2012

Cloud Computing at JPL Science Data Systems

Cloud computing is an approach and tool to support "Big Data".

Earth Science Data Systems↗

NASA NTRS2003

Reusable software services for science data systems

A common science data processing software framework yields the benefits of reuse while remaining adaptable to address requirements that are unique to the mission.

Management↗

NASA NTRS2007

NASA's NPOESS Preparatory Project Science Data Segment: A Framework for Measurement-based Earth Science Data Systems

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) provides a framework for the future of NASA s distributed Earth science data systems. The NPP SDS performs research and data product assessment while using a fully distributed architecture. The components of this architecture are organized around key environmental data disciplines: land, ocean, ozone, atmospheric sounding, and atmospheric composition. The SDS thus establishes a set of concepts and a working prototypes. This paper describes the framework used by the NPP Project as it enabled Measurement-Based Earth Science Data Systems for the assessment of NPP products.

Schwaller, Mathew R.↗

NASA NTRS2016

Developing the Next Generation of Science Data System Engineers

At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects.The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peermentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breadth of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multidiscipline science and practitioner communities expect to have access to all types of observational data.This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.

Next Generation of Science↗

NASA NTRS2004

Overview of NASA's Earth Science Data Systems

For over the last 15 years, NASA's Earth Science Enterprise (ESE) has devoted a tremendous effort to design and build the Earth Observing System (EOS) Data and Information System (EOSDIS) to acquire, process, archive and distribute the data of the EOS series of satellites and other ESE missions and field programs. The development of EOSDIS began with an early prototype to support NASA data from heritage missions and progressed through a formal development process to today's system that supports the data from multiple missions including Landsat 7, Terra, Aqua, SORCE and ICESat. The system is deployed at multiple Distributed Active Archive Centers (DAACs) and its current holdings are approximately 4.5 petabytes. The current set of unique users requesting EOS data and information products exceeds 2 million. While EOSDIS has been the centerpiece of NASA's Earth Science Data Systems, other initiatives have augmented the services of EOSDIS and have impacted its evolution and the future directions of data systems within the ESE. ESDIS had an active prototyping effort and has continued to be involved in the activities of the Earth Science Technology Office (ESTO). In response to concerns from the science community that EOSDIS was too large and monolithic, the ESE initiated the Earth Science Information Partners (ESP) Federation Experiment that funded a series of projects to develop specialized products and services to support Earth science research and applications. Last year, the enterprise made 41 awards to successful proposals to the Research, Education and Applications Solutions Network (REASON) Cooperative Agreement Notice to continue and extend the ESP activity. The ESE has also sponsored a formulation activity called the Strategy for the Evolution of ESE Data Systems (SEEDS) to develop approaches and decision support processes for the management of the collection of data system and service providers of the enterprise. Throughout the development of its earth science data systems, NASA has had an active collaboration with a number of interagency and international partners. One of the mechanisms that has been extremely helpful in initiating and promoting this collaboration has been NASA's participation in the Committee on Earth Observation Satellites (CEOS) and its Working Group on Information Systems and Services (WGISS). The CEOS members, working together, have implemented an International Directory Network that enables users to locate collections of earth science data held by the international community and an International Catalog System to search and order specific data products. CEOS WGISS has also promoted the international interest in the Open GIS Consortium s specifications that further advance the access and use of geospatial data and the interoperation of GTS components. These are just a few highlights of the benefits that member agencies gain from CEOS participation.

McDonald, Kenneth↗

NASA NTRS2013

Smarter Earth Science Data System

The explosive growth in Earth observational data in the recent decade demands a better method of interoperability across heterogeneous systems. The Earth science data system community has mastered the art in storing large volume of observational data, but it is still unclear how this traditional method scale over time as we are entering the age of Big Data. Indexed search solutions such as Apache Solr (Smiley and Pugh, 2011) provides fast, scalable search via keyword or phases without any reasoning or inference. The modern search solutions such as Googles Knowledge Graph (Singhal, 2012) and Microsoft Bing, all utilize semantic reasoning to improve its accuracy in searches. The Earth science user community is demanding for an intelligent solution to help them finding the right data for their researches. The Ontological System for Context Artifacts and Resources (OSCAR) (Huang et al., 2012), was created in response to the DARPA Adaptive Vehicle Make (AVM) programs need for an intelligent context models management system to empower its terrain simulation subsystem. The core component of OSCAR is the Environmental Context Ontology (ECO) is built using the Semantic Web for Earth and Environmental Terminology (SWEET) (Raskin and Pan, 2005). This paper presents the current data archival methodology within a NASA Earth science data centers and discuss using semantic web to improve the way we capture and serve data to our users.

data center↗

NASA NTRS2009

A Science Data System Approach for the SMAP Mission

Though Science Data System (SDS) development has not traditionally been part of the mission concept phase, lessons learned and study of past Earth science missions indicate that SDS functionality can greatly benefit algorithm developers in all mission phases. We have proposed a SDS approach for the SMAP Mission that incorporates early support for an algorithm testbed, allowing scientists to develop codes and seamlessly integrate them into the operational SDS. This approach will greatly reduce both the costs and risks involved in algorithm transitioning and SDS development.

PCS↗

NASA NTRS2007

NASA's Earth Science Data Systems Standards Process Experiences

NASA has impaneled several internal working groups to provide recommendations to NASA management on ways to evolve and improve Earth Science Data Systems. One of these working groups is the Standards Process Group (SPC). The SPG is drawn from NASA-funded Earth Science Data Systems stakeholders, and it directs a process of community review and evaluation of proposed NASA standards. The working group's goal is to promote interoperability and interuse of NASA Earth Science data through broader use of standards that have proven implementation and operational benefit to NASA Earth science by facilitating the NASA management endorsement of proposed standards. The SPC now has two years of experience with this approach to identification of standards. We will discuss real examples of the different types of candidate standards that have been proposed to NASA's Standards Process Group such as OPeNDAP's Data Access Protocol, the Hierarchical Data Format, and Open Geospatial Consortium's Web Map Server. Each of the three types of proposals requires a different sort of criteria for understanding the broad concepts of "proven implementation" and "operational benefit" in the context of NASA Earth Science data systems. We will discuss how our Standards Process has evolved with our experiences with the three candidate standards.

Ullman, Richard E.↗

NASA NTRS2019

Federated Cloud Challenges in NASA's Earth Science Data Systems (Why So Difficult?)

NASA is presented with a number of opportunities and challenges in federating its Earth Science Data Systems in the burgeoning world of cloud computing. Cloud hosting of Earth Science data provides a new way of bringing data together, at least from a virtual location sense, and is one of the main motives for NASA to host data there. However, NASA is also faced with a Big Data Variety challenge, brought on by the variety of the EO datasets in its archives. This diversity requires many diverse science archives to service the different science communities. As a result, nearly every major function in the Earth Observing System Data and Information System (EOSDIS) must also be federated across its data centers. This pattern is repeated with many of the outside agencies and organizations that EOSDIS federates with, such as the Committee for Earth Observing Satellites, leading to pioneering work on "deep federation" in a joint project with the European Space Agency to develop a Multi-Mission Algorithm and Analysis Platform.

Lynnes, Christopher↗

NASA NTRS2015

The Role and Evolution of NASA's Earth Science Data Systems

One of the three strategic goals of NASA is to Advance understanding of Earth and develop technologies to improve the quality of life on our home planet (NASA strategic plan 2014). NASA's Earth Science Data System (ESDS) Program directly supports this goal. NASA has been launching satellites for civilian Earth observations for over 40 years, and collecting data from various types of instruments. Especially since 1990, with the start of the Earth Observing System (EOS) Program, which was a part of the Mission to Planet Earth, the observations have been significantly more extensive in their volumes, variety and velocity. Frequent, global observations are made in support of Earth system science. An open data policy has been in effect since 1990, with no period of exclusive access and non-discriminatory access to data, free of charge. NASA currently holds nearly 10 petabytes of Earth science data including satellite, air-borne, and ground-based measurements and derived geophysical parameter products in digital form. Millions of users around the world are using NASA data for Earth science research and applications. In 2014, over a billion data files were downloaded by users from NASAs EOS Data and Information System (EOSDIS), a system with 12 Distributed Active Archive Centers (DAACs) across the U. S. As a core component of the ESDS Program, EOSDIS has been operating since 1994, and has been evolving continuously with advances in information technology. The ESDS Program influences as well as benefits from advances in Earth Science Informatics. The presentation will provide an overview of the role and evolution of NASAs ESDS Program.

Remote Sensing↗

NASA NTRSDate not supplied

Open-Source Science-Driven Development of the Science Data System (SDS) for Earth System Observatory (ESO) Atmospheric Missions

The NASA Earth System Observatory (ESO) atmospheric missions will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The Science Data System (SDS) will deploy the adaptive processing system (APS) developed within the Cloud to manage the research and operational processing of ESO atmospheric mission orbital and suborbital sensors and curate these data for near real-time and collection reprocessing and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage and distribution. Further, the SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The SDS follows NASA’s commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the SDS system components will be developed with open-source concepts including components of APS itself as well as ESO atmospheric mission algorithms. This presentation describes the framework of the SDS and its integral part in facilitating OSS within the ESO atmospheric missions.

David M. Giles↗

NASA NTRS2008

Aquarius's Instrument Science Data System (ISDS) Automated to Acquire, Process, Trend Data and Produce Radiometric System Assessment Reports

The Aquarius Radiometer, a subsystem of the Aquarius Instrument required a data acquisition ground system to support calibration and radiometer performance assessment. To support calibration and compose performance assessments, we developed an automated system which uploaded raw data to a ftp server and saved raw and processed data to a database. This paper details the overall functionalities of the Aquarius Instrument Science Data System (ISDS) and the individual electrical ground support equipment (EGSE) which produced data files that were infused into the ISDS. Real time EGSEs include an ICDS Simulator, Calibration GSE, Labview controlled power supply, and a chamber data acquisition system. ICDS Simulator serves as a test conductor primary workstation, collecting radiometer housekeeping (HK) and science data and passing commands and HK telemetry collection request to the radiometer. Calibration GSE (Radiometer Active Test Source) provides source choice from multiple targets for the radiometer external calibration. Power Supply GSE, controlled by labview, provides real time voltage and current monitoring of the radiometer. And finally the chamber data acquisition system produces data reflecting chamber vacuum pressure, thermistor temperatures, AVG and watts. Each GSE system produce text based data files every two to six minutes and automatically copies the data files to the Central Archiver PC. The Archiver PC stores the data files, schedules automated uploads of these files to an external FTP server, and accepts request to copy all data files to the ISDS for offline data processing and analysis. Aquarius Radiometer ISDS contains PHP and MATLab programs to parse, process and save all data to a MySQL database. Analysis tools (MATLab programs) in the ISDS system are capable of displaying radiometer science, telemetry and auxiliary data in near real time as well as performing data analysis and producing automated performance assessment reports of the Aquarius Radiometer.

Source record↗