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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Transcriptomics Processing Pipelines for Space Biology: An Open Source and Consensus-Driven Approach

Transcriptomics holds significant value in elucidating the relationship between gene expression, experimental factors, biological factors, and various types of omics data. Enhancing our understanding of these connections is paramount for foundational biology, which plays a pivotal role in devising solutions for challenges pertinent to both space travel and terrestrial life. The NASA GeneLab project, part of the Open Science Data Repository (OSDR.nasa.gov), seeks to accelerate space biology research through cataloging and democratizing ‘omics data, including transcriptomics. Since raw omics data are largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community via the Open Science Analysis Working Groups (AWGs) to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data have greater immediate value to diverse users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. As of June 2023, transcriptomics studies comprise over half of GeneLab datasets hosted on the OSDR, including data from bulk RNA-seq and Affymetrix or Agilent 1-Channel DNA microarray assays. In collaboration with the AWGs, GeneLab developed consensus processing pipelines for these transcriptomics data types that includes quality control, background correction (microarray only), data normalization and quantification, culminating in the detection and annotation of differentially expressed genes. The work presented here describes Nextflow implementations of GeneLab’s consensus transcriptomics pipelines that automates and accelerates processing of these datasets. In addition to the core data processing, these workflows also include raw data staging and a robust verification and validation program to identify errors in real-time, stop additional downstream computation, and preserve computational resources. These workflows are used to generate GeneLab processed data hosted on the OSDR, and are publicly available as open source software for others to use at: https://github.com/nasa/GeneLab_Data_Processing.

Jonathan Oribello↗
NASA NTRS2002

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: Earth System Modeling Software Framework Survey

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task, both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation. while maintaining high performance across numerous supercomputer and workstation architectures. This document surveys numerous software frameworks for potential use in Earth science modeling. Several frameworks are evaluated in depth, including Parallel Object-Oriented Methods and Applications (POOMA), Cactus (from (he relativistic physics community), Overture, Goddard Earth Modeling System (GEMS), the National Center for Atmospheric Research Flux Coupler, and UCLA/UCB Distributed Data Broker (DDB). Frameworks evaluated in less detail include ROOT, Parallel Application Workspace (PAWS), and Advanced Large-Scale Integrated Computational Environment (ALICE). A host of other frameworks and related tools are referenced in this context. The frameworks are evaluated individually and also compared with each other.

Talbot, Bryan↗
NASA NTRSDate not supplied

Advancing Open Source Science Initiatives Through Public-Private Partnerships

Collaboration is fundamental to advancing open science within the science community. With the recent developments in technology and research, the establishment of formal partnerships between the private sector and government agencies are needed to bridge the knowledge gaps and expedite the time to actionable science. NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT) seeks to address this challenge by establishing non-reimbursable Space Act Agreements with industry leaders in cloud computing, artificial intelligence (AI) and machine learning. The purpose of these agreements is to advance open source science initiatives in the areas of data discovery, access and use of high value NASA science data sets on the cloud. As well as, jointly work on common research problems to accelerate the development and adoption of new AI technologies. Current success stories include co-locating NASA datasets from multiple science disciplines on one platform using Amazon Web Services Open Data Registry, developing AI Foundation Models for Science with IBM and co-hosting training workshops and tutorials for the science community aimed at providing hands-on experience with using NASA data and AI models on the cloud. In summary, we will present an overview of our partnerships supporting open source science initiatives, describe current activities and lessons learned that may be useful to others considering similar partnerships with the private sector.

Elizabeth Fancher↗
NASA NTRS1994

CESDIS

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. The 1993-94 CESDIS year included a broad range of computer science research applied to NASA problems. This report provides an overview of these research projects and programs as well as a summary of the various other activities of CESDIS in support of NASA and the university research community, We have had an exciting and challenging year.

Source record↗
NASA NTRS1991

A guide to NASA's Pilot Land Data System (PLDS)

NASA's Pilot Land Data System (PLDS) is a distributed information management system designed to support NASA's land science community. The PLDS provides a wide range of services including management of information about scientific data, access to a library of scientific data, a data ordering capability, communications, connection to data analysis facilities, and electronic mail. The PLDS provides these services by offering the scientist the capability to search for and order data, and to communicate electronically with other scientists and computers. Three functions enable scientists to find what data are available and where they reside. The first two, Find data summaries and Read detailed descriptions give summary and detailed descriptions about data sets or groups of related data sets, science, projects, and institutions which archive land data. The third, gives information about specific pieces of data. This last function has two components, Search systemwide inventory and Search local inventory. The first component enables the user to find data elements (images, geological samples, transects, maps, etc.) that exist anywhere in the PLDS while the second has only information about data at the local site. The first enables the user to find pieces of data from several different data sets with the same temporal and spatial coverage and other elements common to most data sets, while the second allows the user to select a data set based on these descriptors and on those that are unique to a data set. The PLDS provides capabilities that enable electronic file transfers, intercomputer connection, and electronic mail. Both TCP/IP and DECnet protocols are supported via the NASA Science Internet (NIS). Access is also available through Telenet.

Source record↗
NASA NTRS2001

Generic Divide and Conquer Internet-Based Computing

The rapid growth of internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of new, internet-oriented software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high -performance computing applications community. The general goal of this research project is to contribute to better understanding of the transition to internet-based high -performance computing and to develop solutions for some of the difficulties of this transition. More specifically, our goal is to design an architecture for generic divide and conquer internet-based computing, to develop a portable implementation of this architecture, to create an example library of high-performance divide-and-conquer computing agents that run on top of this architecture, and to evaluate the performance of these agents. We have been designing an architecture that incorporates a master task-pool server and utilizes satellite computational servers that operate on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. Our designed architecture is intended to be complementary to and accessible from computational grids such as Globus, Legion, and Condor. Grids provide remote access to existing high-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end internet nodes. Our project is focused on a generic divide-and-conquer paradigm and its applications that operate on a loose and ever changing pool of lower-end internet nodes.

Radenski, Atanas↗
NASA NTRS2009

Flightspeed Integral Image Analysis Toolkit

The Flightspeed Integral Image Analysis Toolkit (FIIAT) is a C library that provides image analysis functions in a single, portable package. It provides basic low-level filtering, texture analysis, and subwindow descriptor for applications dealing with image interpretation and object recognition. Designed with spaceflight in mind, it addresses: Ease of integration (minimal external dependencies) Fast, real-time operation using integer arithmetic where possible (useful for platforms lacking a dedicated floatingpoint processor) Written entirely in C (easily modified) Mostly static memory allocation 8-bit image data The basic goal of the FIIAT library is to compute meaningful numerical descriptors for images or rectangular image regions. These n-vectors can then be used directly for novelty detection or pattern recognition, or as a feature space for higher-level pattern recognition tasks. The library provides routines for leveraging training data to derive descriptors that are most useful for a specific data set. Its runtime algorithms exploit a structure known as the "integral image." This is a caching method that permits fast summation of values within rectangular regions of an image. This integral frame facilitates a wide range of fast image-processing functions. This toolkit has applicability to a wide range of autonomous image analysis tasks in the space-flight domain, including novelty detection, object and scene classification, target detection for autonomous instrument placement, and science analysis of geomorphology. It makes real-time texture and pattern recognition possible for platforms with severe computational restraints. The software provides an order of magnitude speed increase over alternative software libraries currently in use by the research community. FIIAT can commercially support intelligent video cameras used in intelligent surveillance. It is also useful for object recognition by robots or other autonomous vehicles

Thompson, David R.↗
NASA NTRS2013

SPICE: A Geometry Information System Supporting Planetary Mapping, Remote Sensing and Data Mining

SPICE is an information system providing space scientists ready access to a wide assortment of space geometry useful in planning science observations and analyzing the instrument data returned therefrom. The system includes software used to compute many derived parameters such as altitude, LAT/LON and lighting angles, and software able to find when user-specified geometric conditions are obtained. While not a formal standard, it has achieved widespread use in the worldwide planetary science community

planetary science investigations↗
NASA NTRS2016

On-Orbit Calibration and Performance of S-NPP VIIRS DNB

The S-NPP VIIRS instrument has successfully operated since its launch in October 2011. The VIIRS Day-Night Band (DNB) is a panchromatic channel covering wavelengths from 0.5 to 0.9 m that is capable of observing Earth scenes during both day and nighttime orbits at a spatial resolution of 750 m. To cover the large dynamic range, the DNB operates at low, mid, or high gain stages, and it uses an onboard solar diffuser (SD) for its low gain stage calibration. The SD observations also provide a means to compute gain ratios of low-to-mid and mid-to-high gain stages. This paper describes the DNB on-orbit calibration methodologies used by the VIIRS Characterization Support Team (VCST) in supporting the NASA earth science community with consistent VIIRS sensor data records (SDRs) made available by the Land Science Investigator-led Processing Systems (SIPS). It provides an assessment and update of DNB on-orbit performance, including the SD degradation in the DNB spectral range, detector gain and gain ratio trending, stray light contamination and its correction. Also presented in this paper are performance validations based on earth scenes and lunar observations.

Chen, H.↗
NASA NTRS2017

Suomi-NPP VIIRS Day-Night Band On-Orbit Calibration and Performance

The Suomi national polar-orbiting partnership Visible Infrared Imaging Radiometer Suite (VIIRS) instrument has successfully operated since its launch in October 2011. The VIIRS day-night band (DNB) is a panchromatic channel covering wavelengths from 0.5 to 0.9 microns that is capable of observing Earth scenes during both daytime and nighttime at a spatial resolution of 750 m. To cover the large dynamic range, the DNB operates at low-, middle-, and high-gain stages, and it uses an on-board solar diffuser (SD) for its low-gain stage calibration. The SD observations also provide a means to compute the gain ratios of low-to-middle and middle-to-high gain stages. This paper describes the DNB on-orbit calibration methodology used by the VIIRS characterization support team in supporting the NASA Earth science community with consistent VIIRS sensor data records made available by the land science investigator-led processing systems. It provides an assessment and update of the DNB on-orbit performance, including the SD degradation in the DNB spectral range, detector gain and gain ratio trending, and stray-light contamination and its correction. Also presented in this paper are performance validations based on Earth scenes and lunar observations, and comparisons to the calibration methodology used by the operational interface data processing segment.

Chen, Hongda↗
NASA NTRS2017

X-Ray Computed Tomography: The First Step in Mars Sample Return Processing

The Mars 2020 rover mission will collect and cache samples from the martian surface for possible retrieval and subsequent return to Earth. If the samples are returned, that mission would likely present an opportunity to analyze returned Mars samples within a geologic context on Mars. In addition, it may provide definitive information about the existence of past or present life on Mars. Mars sample return presents unique challenges for the collection, containment, transport, curation and processing of samples [1] Foremost in the processing of returned samples are the closely paired considerations of life detection and Planetary Protection. In order to achieve Mars Sample Return (MSR) science goals, reliable analyses will depend on overcoming some challenging signal/noise-related issues where sparse martian organic compounds must be reliably analyzed against the contamination background. While reliable analyses will depend on initial clean acquisition and robust documentation of all aspects of developing and managing the cache [2], there needs to be a reliable sample handling and analysis procedure that accounts for a variety of materials which may or may not contain evidence of past or present martian life. A recent report [3] suggests that a defined set of measurements should be made to effectively inform both science and Planetary Protection, when applied in the context of the two competing null hypotheses: 1) that there is no detectable life in the samples; or 2) that there is martian life in the samples. The defined measurements would include a phased approach that would be accepted by the community to preserve the bulk of the material, but provide unambiguous science data that can be used and interpreted by various disciplines. Fore-most is the concern that the initial steps would ensure the pristine nature of the samples. Preliminary, non-invasive techniques such as computed X-ray tomography (XCT) have been suggested as the first method to interrogate and characterize the cached samples without altering the materials [1,2]. A recent report [4] indicates that XCT may minimally alter samples for some techniques, and work is needed to quantify these effects, maximizing science return from XCT initial analysis while minimizing effects.

Welzenbach, L. C.↗
NASA NTRS2018

NASA's Earth Observing Data and Information System - Near-Term Challenges

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.

Remote Sensing↗
NASA NTRS1976

NASA Langley Research Center outreach in astronautical education

The Langley Research Center has traditionally maintained an active relationship with the academic community, especially at the graduate level, to promote the Center's research program and to make graduate education available to its staff. Two new institutes at the Center - the Joint Institute for Acoustics and Flight Sciences, and the Institute for Computer Applications - are discussed. Both provide for research activity at the Center by university faculties. The American Society of Engineering Education Summer Faculty Fellowship Program and the NASA-NRC Postdoctoral Resident Research Associateship Program are also discussed.

Duberg, J. E.↗
NASA NTRS2003

Generic Divide and Conquer Internet-Based Computing

The growth of Internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of Peer to Peer (P2P) software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high-performance computing applications community. The general goal of this project is to achieve better understanding of the transition to Internet-based high-performance computing and to develop solutions for some of the technical challenges of this transition. In particular, we are interested in creating long-term motivation for end users to provide their idle processor time to support computationally intensive tasks. We believe that a practical P2P architecture should provide useful service to both clients with high-performance computing needs and contributors of lower-end computing resources. To achieve this, we are designing dual -service architecture for P2P high-performance divide-and conquer computing; we are also experimenting with a prototype implementation. Our proposed architecture incorporates a master server, utilizes dual satellite servers, and operates on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. A dual satellite server comprises a high-performance computing engine and a lower-end contributor service engine. The computing engine provides generic support for divide and conquer computations. The service engine is intended to provide free useful HTTP-based services to contributors of lower-end computing resources. Our proposed architecture is complementary to and accessible from computational grids, such as Globus, Legion, and Condor. Grids provide remote access to existing higher-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end Internet nodes. Our project is focused on a generic divide and conquer paradigm and on mobile applications of this paradigm that can operate on a loose and ever changing pool of lower-end Internet nodes.

Follen, Gregory J.↗
NASA NTRS2019

Earth Science Technology Office (ESTO) New Observing Strategies (NOS) and NOS-Testbed (NOS-T)

With the advancement of space hardware technologies such as smaller spacecraft, component and instrument miniaturization and high performance space processors, and with the advancement of software technologies in artificial intelligence, big data analysis and autonomous decision making, Earth Science is looking at novel ways to observe phenomena that previously could not have been studied or would have been too expensive to study with traditional missions. In particular, the New Observing Strategies (NOS) component of the NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program aims at leveraging these novel technologies as well as low cost and easy access to space to acquire multi-temporal or simultaneous multi-angular, multi-locations, multi-resolution and multi-spectral observations that will provide better multi-source measurements and will build a more dynamic and comprehensive picture of Earth Science phenomena that need to be studied and analyzed. For applications such as water resources management, air quality monitoring, biodiversity studies or disaster management, NOS will integrate the use of small instruments, small spacecraft, constellations of spacecraft and networks of sensors to design new missions that will provide the necessary measurements to improve future forecast and science modeling systems.Measurement acquisition will therefore be approached as a system of systems rather than on a mission basis, and a system of this complexity should not be expected to work without full integration and experimental characterization. Although most of the individual technologies enabling to link and coordinate multi-source observations are more or less mature, a few technologies need to be developed and all of them need to be integrated and tested as a system. In order for this validation to occur, the AIST Program is developing the NOS Testbed that includes 3 main goals:1.Validate novel NOS technologies, independently and as a system2.Demonstrate novel distributed operations concepts3.Socialize new Distributed Spacecraft Mission (DSM) and SensorWeb (SW) technologies and concepts to the science community by significantly retiring the risk of integrating these new technologies.The NOS Testbed will consist of multiple sensing nodes, simulated or actual, representing space, air and/or ground measurements, that are interconnected by a communications fabric (infrastructure that permits nodes to transmit and receive data between one another and interact with each other). Each node will be supported by hardware capabilities required to perform nodes monitoring and command & control, as well as intelligent "onboard" computing. The nodes will work together in a collaborative manner to demonstrate optimal science capabilities. The testbed will enable to validate technologies such as inter-node communication models, techniques and protocols; inter-node coordination; real-time data fusion and understanding; planning; sensor re-targeting; etc. Additionally, the testbed will have the capability to interact with various mission design tools, OSSEs and one or several forecast models. More details about the NOS Testbed will be presented at the confererence.

Earth Science missions; Advanced information Syste↗
NASA NTRS2002

Real World Connections Through Videoconferences

The Learning Technologies Project (LTP) is a partner in the National Aeronautics and Space Administration's (NASA's) educational technology program unit, an electronic community center that fosters interaction, collaboration, and sharing among educators, learners, and scientists. The goal of the NASA Glenn Research Center's Learning Technologies Project is to increase students' interest and proficiency in mathematics, science, and technology through the use of computing and communications technology and by using NASA's mission in aerospace technology as a theme. The primary components are: (1) Beginner's Guide to Aeronautics, including interactive simulation packages and teacher-created online activities. (2) NASA Virtual Visits, videoconferences (with online pre-post-conference activities) connecting students and teachers to NASA scientists and researchers.

Peterson, Ruth↗
NASA NTRSDate not supplied

Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)

The scientific community is faced with a need for greatly improved data sharing, analysis, visualization and advanced collaboration based firmly on open science principles. Recent and upcoming launches of new satellite missions with more complex and voluminous data, as well as the ever more urgent need to better understand the global carbon budget and related ecological processes, provided the immediate rational for the ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP). This highly collaborative joint project of ESA and NASA established a framework between ESA and NASA to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by ESA and NASA EO data users. Presented to the public in October 2021, the current version of MAAP provides a common cloud-based platform with computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of global above-ground biomass. Data from the Global Ecosystem Dynamics Investigation (GEDI) mission on the International Space Station and the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) have been instrumental in the first products of MAAP including the first comprehensive map of Boreal above-ground Biomass and a current Global Biomass Harmonization Activity, but the platform is also being specifically designed to support the forthcoming ESA Biomass mission and incorporate data from the upcoming NASA-ISRO SAR (NISAR) mission. While these missions and the corresponding research which includes airborne, field, and calibration/validation data collection and analyses, provide a wealth of data and information relating to global biomass estimation, they also present data storing, processing and sharing challenges. The NISAR mission alone will produce about 80TB/day. These large data volumes present a challenge that would otherwise place accessibility limits on the scientific community and impact scientific progress. Other challenges being addressed by MAAP include: 1) Enabling researchers to easily discover, process, visualize and analyze large volumes of data from both agencies; 2) Providing a wide variety of data in the same coordinate reference frame to enable comparison, analysis, data evaluation, and data generation; 3) Providing a version-controlled science algorithm development environment that supports tools, co-located data and processing resources; and 4) Addressing intellectual property and sharing challenges related to collaborative algorithm development and sharing of data and algorithms. MAAP products can be explored on the MAAP Dashboard at https://earthdata.nasa.gov/maap-biomass or the joint platform entrance at scimaap.net. MAAP also can be accessed through individual NASA (https://maap-project.org) and ESA (https://esa-maap.org/) landing pages.

cloud computing↗
NASA NTRS1993

EOSDIS - Its role in the EOS program and its importance to the scientific community

In order to manage the global data sets required to understand the earth as a system, the EOS Data and Information System (EOSDIS) will collect and store satellite, aircraft, and in situ measurements and their resultant data products, and will distribute the data conveniently. EOSDIS will also provide product generation and science computing facilities to support the development, processing, and validation of standard EOS science data products. The overall architecture of EOSDIS, and how the Distributed Active Archive Centers fit into that structure, are shown. EOSDIS will enable users to query data bases nationally, make use of keywords and other mnemonic identifiers, and see graphic images of subsets of available data prior to ordering full (or selected pieces of) data sets for use in their 'home' environment.

Price, Robert D.↗