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Use of antarctic analogs to support the space exploration initiative

This report has discussed the Space Exploration Initiative (SEI) and the U.S. Antarctic Program (USAP) in the context of assessing the potential rationale and strategy for conducting a cooperative NASA/NSF (National Science Foundation) effort. Specifically, such an effort would address shared research and data on living and conducting scientific research in isolated, confined, hostile, and remote environments. A review of the respective goals and requirements of NASA and the NSF indicates that numerous opportunities exist to mutually benefit from sharing relevant technologies, data, and systems. Two major conclusions can be drawn: (1) The technologies, experience, and capabilities existing and developing in the aerospace community would enhance scientific research capabilities and the efficiency and effectiveness of operations in Antarctica. The transfer and application of critical technologies (e.g., power, waste management, life support) and collaboration on crew research needs (e.g., human behavior and medical support needs) would streamline the USAP operations and provide the scientific community with advancements in facilities and tools for Antarctic research. (2) Antarctica is the most appropriate earth analog for the environments of the the Moon and Mars. Using Antarctica in this way would contribute substantially to near- and long-term needs and plans for the SEI. Antarctica is one of the few ground-based analogs that would permit comprehensive and integrated studies of three areas deemed critical to productive and safe operations on the Moon and Mars: human health and productivity; innovative scientific research techniques; and reliable, efficient technologies and facilities.

Wharton, Robert↗

Articulation Management for Intelligent Integration of Information

When combining data from distinct sources, there is a need to share meta-data and other knowledge about various source domains. Due to semantic inconsistencies and heterogeneity of representations, problems arise in combining multiple domains when the domains are merged. The knowledge that is irrelevant to the task of interoperation will be included, making the result unnecessarily complex. This heterogeneity problem can be eliminated by mediating the conflicts and managing the intersections of the domains. For interoperation and intelligent access to heterogeneous information, the focus is on the intersection of the knowledge, since intersection will define the required articulation rules. An algebra over domain has been proposed to use articulation rules to support disciplined manipulation of domain knowledge resources. The objective of a domain algebra is to provide the capability for interrogating many domain knowledge resources, which are largely semantically disjoint. The algebra supports formally the tasks of selecting, combining, extending, specializing, and modifying Components from a diverse set of domains. This paper presents a domain algebra and demonstrates the use of articulation rules to link declarative interfaces for Internet and enterprise applications. In particular, it discusses the articulation implementation as part of a production system capable of operating over the domain described by the IDL (interface description language) of objects registered in multiple CORBA servers.

Maluf, David A.↗

Interactive Sectoring and Animation of Global Change Data

In order to analyze and share results of global change data sets, scientists require a venue in which to exchange their results. One appropriate medium for these collaborative efforts is the world wide web. Intuitive and efficient user interfaces, and background processes have been developed at the Global Hydrology and Climate Center to interactively view weather satellite, radar, global temperature anomaly, and model output data using the world wide web. These tools combine scripts, Java and C code which allows the user to easily interact with data, to create high resolution sector images, and sectored animation sequences. This paper examines the architecture and interfaces and how they are used for collaborative research.

Meyer, Paul J.↗

County Level Annual Population Projections for SSP3 and SSP5

This dataset consist of annual (2020-2100) county-level population projections for the United States (U.S.) for Shared Socioeconomic Pathways (SSPs) 3 and 5. The original decadal state-level data is used as an input to the gridded population data model to downscale the state-level projections for each SSP to a 1 km grid. The 1 km data is then aggregated to the county-level using the 2020 TIGER/Line county shapefiles from the U.S. Census Bureau. The two data files are shared as .csv files with the following structure: Rows = Data for individual counties which are identified using their Federal Information Processing Standard (FIPS) code. The FIPS code is stored in the first column. Columns = Each year from 2020-2100 is an individual column. For easier reference, the state name associated with each row is stored in the last column. Values in each cell are the downscaled estimated population for that county-year combination. Values are fractional due to the weighting scheme used in the downscaling. The paper and model source code cited in the "Related Works" section describes the initial source of the population projections.

FIPS↗

Space-based Science Operations Grid Prototype

Grid technology is the up and coming technology that is enabling widely disparate services to be offered to users that is very economical, easy to use and not available on a wide basis. Under the Grid concept disparate organizations generally defined as "virtual organizations" can share services i.e. sharing discipline specific computer applications, required to accomplish the specific scientific and engineering organizational goals and objectives. Grids are emerging as the new technology of the future. Grid technology has been enabled by the evolution of increasingly high speed networking. Without the evolution of high speed networking Grid technology would not have emerged. NASA/Marshall Space Flight Center's (MSFC) Flight Projects Directorate, Ground Systems Department is developing a Space-based Science Operations Grid prototype to provide to scientists and engineers the tools necessary to operate space-based science payloads/experiments and for scientists to conduct public and educational outreach. In addition Grid technology can provide new services not currently available to users. These services include mission voice and video, application sharing, telemetry management and display, payload and experiment commanding, data mining, high order data processing, discipline specific application sharing and data storage, all from a single grid portal. The Prototype will provide most of these services in a first step demonstration of integrated Grid and space-based science operations technologies. It will initially be based on the International Space Station science operational services located at the Payload Operations Integration Center at MSFC, but can be applied to many NASA projects including free flying satellites and future projects. The Prototype will use the Internet2 Abilene Research and Education Network that is currently a 10 Gb backbone network to reach the University of Alabama at Huntsville and several other, as yet unidentified, Space Station based science experimenters. There is an international aspect to the Grid involving the America's Pathway (AMPath) network, the Chilean REUNA Research and Education Network and the University of Chile in Santiago that will further demonstrate how extensive these services can be used. From the user's perspective, the Prototype will provide a single interface and logon to these varied services without the complexity of knowing the where's and how's of each service. There is a separate and deliberate emphasis on security. Security will be addressed by specifically outlining the different approaches and tools used. Grid technology, unlike the Internet, is being designed with security in mind. In addition we will show the locations, configurations and network paths associated with each service and virtual organization. We will discuss the separate virtual organizations that we define for the varied user communities. These will include certain, as yet undetermined, space-based science functions and/or processes and will include specific virtual organizations required for public and educational outreach and science and engineering collaboration. We will also discuss the Grid Prototype performance and the potential for further Grid applications both space-based and ground based projects and processes. In this paper and presentation we will detail each service and how they are integrated using Grid

Bradford, Robert N.↗

Mobile Sensor Technologies Being Developed

The NASA Glenn Research Center is developing small mobile platforms for sensor placement, as well as methods for communicating between roving platforms and a central command location. The first part of this project is to use commercially available equipment to miniaturize an existing sensor platform. We developed a five-circuit-board suite, with an average board size of 1.5 by 3 cm. Shown in the preceding photograph, this suite provides all motor control, direction finding, and communications capabilities for a 27- by 21- by 40-mm prototype mobile platform. The second part of the project is to provide communications between mobile platforms, and also between multiple platforms and a central command location. This is accomplished with a low-power network labeled "SPAN," Sensor Platform Area Network, a local area network made up of proximity elements. In practice, these proximity elements are composed of fixed- and mobile-sensor-laden science packages that communicate to each other via radiofrequency links. Data in the network will be shared by a central command location that will pass information into and out of the network through its access to a backbone element. The result will be a protocol portable to general purpose microcontrollers satisfying a host of sensor networking tasks. This network will enter the gap somewhere between television remotes and Bluetooth but, unlike 802.15.4, will not specify a physical layer, thus allowing for many data rates over optical, acoustical, radiofrequency, hardwire, or other media. Since the protocol will exist as portable C-code, developers may be able to embed it in a host of microcontrollers from commercial to space grade and, of course, to design it into ASICs. Unlike in 802.15.4, the nodes will relate to each other as peers. A demonstration of this protocol using the two test bed platforms was recently held. Two NASA modified, commercially available, mobile platforms communicated and shared data with each other and a central command location. Web-based control and interrogation of similar mobile sensor platforms have also been demonstrated. Expected applications of this technology include robotic planetary exploration, astronaut-to-equipment communication, and remote aerospace engine inspections.

FROM↗

Experimenter's laboratory for visualized interactive science

The science activities of the 1990's will require the analysis of complex phenomena and large diverse sets of data. In order to meet these needs, we must take advantage of advanced user interaction techniques: modern user interface tools; visualization capabilities; affordable, high performance graphics workstations; and interoperable data standards and translator. To meet these needs, we propose to adopt and upgrade several existing tools and systems to create an experimenter's laboratory for visualized interactive science. Intuitive human-computer interaction techniques have already been developed and demonstrated at the University of Colorado. A Transportable Applications Executive (TAE+), developed at GSFC, is a powerful user interface tool for general purpose applications. A 3D visualization package developed by NCAR provides both color shaded surface displays and volumetric rendering in either index or true color. The Network Common Data Form (NetCDF) data access library developed by Unidata supports creation, access and sharing of scientific data in a form that is self-describing and network transparent. The combination and enhancement of these packages constitutes a powerful experimenter's laboratory capable of meeting key science needs of the 1990's. This proposal encompasses the work required to build and demonstrate this capability.

Hansen, Elaine R.↗

Experimenter's laboratory for visualized interactive science

The science activities of the 1990's will require the analysis of complex phenomena and large diverse sets of data. In order to meet these needs, we must take advantage of advanced user interaction techniques: modern user interface tools; visualization capabilities; affordable, high performance graphics workstations; and interoperatable data standards and translator. To meet these needs, we propose to adopt and upgrade several existing tools and systems to create an experimenter's laboratory for visualized interactive science. Intuitive human-computer interaction techniques have already been developed and demonstrated at the University of Colorado. A Transportable Applications Executive (TAE+), developed at GSFC, is a powerful user interface tool for general purpose applications. A 3D visualization package developed by NCAR provides both color-shaded surface displays and volumetric rendering in either index or true color. The Network Common Data Form (NetCDF) data access library developed by Unidata supports creation, access and sharing of scientific data in a form that is self-describing and network transparent. The combination and enhancement of these packages constitutes a powerful experimenter's laboratory capable of meeting key science needs of the 1990's. This proposal encompasses the work required to build and demonstrate this capability.

Hansen, Elaine R.↗

Online Small-Sat Knowledge Repositories and Modeling Tools for Risk Reduction and Enhanced Mission Success

Developers of small satellites face the challenges of a short development schedule, incomplete information about parts from vendors, and limited budgets. The situation is complicated by the need to use commercial electronic parts rather than radiation hardened parts to meet performance and budget constraints. Fortunately, a number of organizations are standing up new modeling and data resources that are available for free online. Motivation for sharing models, part data, and lessons learned include shorter development times, increased mission success likelihood, and training the next generation of space professionals. The purpose of this paper is to make these resources and their complementary capabilities known to the small satellite community.

Small Satellites↗

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism, behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗

Advanced data management design for autonomous telerobotic systems in space using spaceborne symbolic processors

The use of computers in autonomous telerobots is reaching the point where advanced distributed processing concepts and techniques are needed to support the functioning of Space Station era telerobotic systems. Three major issues that have impact on the design of data management functions in a telerobot are covered. It also presents a design concept that incorporates an intelligent systems manager (ISM) running on a spaceborne symbolic processor (SSP), to address these issues. The first issue is the support of a system-wide control architecture or control philosophy. Salient features of two candidates are presented that impose constraints on data management design. The second issue is the role of data management in terms of system integration. This referes to providing shared or coordinated data processing and storage resources to a variety of telerobotic components such as vision, mechanical sensing, real-time coordinated multiple limb and end effector control, and planning and reasoning. The third issue is hardware that supports symbolic processing in conjunction with standard data I/O and numeric processing. A SSP that currently is seen to be technologically feasible and is being developed is described and used as a baseline in the design concept.

Goforth, Andre↗

Opus: A Coordination Language for Multidisciplinary Applications

Data parallel languages, such as High Performance fortran, can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are multidisciplinary and heterogeneous in nature, and thus do not fit well into the data parallel paradigm. In this paper we present Opus, a language designed to fill this gap. The central concept of Opus is a mechanism called ShareD Abstractions (SDA). An SDA can be used as a computation server, i.e., a locus of computational activity, or as a data repository for sharing data between asynchronous tasks. SDAs can be internally data parallel, providing support for the integration of data and task parallelism as well as nested task parallelism. They can thus be used to express multidisciplinary applications in a natural and efficient way. In this paper we describe the features of the language through a series of examples and give an overview of the runtime support required to implement these concepts in parallel and distributed environments.

Chapman, Barbara↗

Community standards and future opportunities for synthetic communities in plant–microbiota research

Harnessing beneficial microorganisms is seen as a promising approach to enhance sustainable agriculture production. Synthetic communities (SynComs) are increasingly being used to study relevant microbial activities and interactions with the plant host. Yet, the lack of community standards limits the efficiency and progress in this important area of research. Here, to address this gap, we recommend three actions: (1) defining reference SynComs; (2) establishing community standards, protocols and benchmark data for constructing and using SynComs; and (3) creating an infrastructure for sharing strains and data. We also outline opportunities to develop SynCom research through technical advances, linking to field studies, and filling taxonomic blind spots to move towards fully representative SynComs.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancing Discoverability and Management of Atmospheric Data at Scale: Solutions from the ARM Data Center

The Atmospheric Radiation Measurement (ARM) is a multi-laboratory and multi-institutional U.S. Department of Energy (DOE) Office of Science National User Facility. The ARM Data Center (ADC), located at Oak Ridge National Laboratory, collects, archives, and shares vast atmospheric data crucial for climate research. The ADC manages over 7 PB of data from 460 instruments worldwide, processing it into more than 11,000 diverse data products using the Network Common Data Form (NetCDF) for machine-independent accessibility. The primary challenge addressed in this paper is the efficient management and distribution of vast and diverse datasets essential for the climate research community, enhancing accessibility through advanced tools like Data Discovery. The ADC has developed advanced infrastructure and software architecture to handle the continuous influx of heterogeneous data to enhance data discoverability, resulting in increased scientific collaboration. In 2023, users from over 34 countries downloaded and utilized ARM data, resulting in 1,455 publications. The ADC’s efforts have significantly improved the discoverability and usability of atmospheric data, fostering extensive scientific research and collaboration. This paper details the solutions implemented by the ADC team for efficient data discovery and distribution, and it demonstrates ARM’s capability of staging processed data for scientific analysis.

Shah, Chirag [ORNL] (ORCID:0000000203145737)↗

Automatic Data Traffic Control on DSM Architecture

We study data traffic on distributed shared memory machines and conclude that data placement and grouping improve performance of scientific codes. We present several methods which user can employ to improve data traffic in his code. We report on implementation of a tool which detects the code fragments causing data congestions and advises user on improvements of data routing in these fragments. The capabilities of the tool include deduction of data alignment and affinity from the source code; detection of the code constructs having abnormally high cache or TLB misses; generation of data placement constructs. We demonstrate the capabilities of the tool on experiments with NAS parallel benchmarks and with a simple computational fluid dynamics application ARC3D.

Frumkin, Michael↗

A Web-based Collaborative Tool for Mars Analog Data Exploration

Solving today's complex research and modeling challenges are dependent on our ability to discover, access, integrate, and share information from multiple sources. The planetary sciences community is no exception'; over the last few years, the need for data mining and exploration tools that can expedite comparative studies between Martian and terrestrial analogs sites and aid the interpretation of Mars data sets has become evident. Data sharing maximizes scientific return from studies and data sets.

Necsoiu, M.↗

Interactive Sectoring and Animation of Global Change Data

In order to analyze and share results of global change climate data sets, scientists require a venue in which to exchange their results. The perfect medium for these collaborative efforts is the world wide web. Intuitive and efficient user interfaces, and background processes were developed at the Global Hydrology and Climate Center to interactively view weather satellite, radar, global temperature anomaly, and model output data using the world wide web. These tools combine scripts, Java, and C code, which allows the end user to easily interact with data, to create high resolution sector images, and sectored animation sequences. This paper examines the architecture and interfaces which were designed at the Global Hydrology and Climate Center and how they are used for collaborative research.

Meyer, Paul J.↗

Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing 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 data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗