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At least 235 records · Page 13

Arizona State University Requirements Analysis Report

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Between October 2021 and February 2022 staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from Arizona State University (ASU) for the purpose of a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff to better understand the needs of the researchers within the community.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Data, Meet Compute: NASA's Cumulus Ingest Architecture

NASA's Earth Observing System Data and Information System (EOSDIS) houses nearly 30PBs of critical Earth Science data and with upcoming missions is expected to balloon to between 200PBs-300PBs over the next seven years. In addition to the massive increase in data collected, researchers and application developers want more and faster access - enabling complex visualizations, long time-series analysis, and cross dataset research without needing to copy and manage massive amounts of data locally. NASA has looked to the cloud to address these needs, building its Cumulus system to manage the ingest of diverse data in a wide variety of formats into the cloud. In this talk, we look at what Cumulus is from a high level and then take a deep dive into how it manages complexity and versioning associated with multiple AWS Lambda and ECS microservices communicating through AWS Step Functions across several disparate installations

EOSDIS↗

Community Resilience Indicator Analysis: Commonly Used Indicators from Peer-Reviewed Research (Updated for Research Published 2003-2021)

In 2017, FEMA’s National Integration Center (NIC) Technical Assistance (TA) Branch identified a need to establish a data-driven basis for prioritizing locations for TA investment and guiding local emergency management planning. To achieve this goal, FEMA tasked Argonne National Laboratory (Argonne) with identifying commonly used indicators of community resilience across the landscape of published peer-reviewed research. FEMA and Argonne completed the first Community Resilience Indicator Analysis (CRIA) in 2018 and repeated the process in 2022. The CRIA process begins with a literature review and cataloguing of published peer-reviewed assessment methodologies on social vulnerability and community resilience. The literature review findings are then filtered by inclusion criteria established by the CRIA research team to ensure the methodologies are: (1) Quantitative, (2) Data and methodology are publicly available, (3) Calculated at the county level or lower, (4) Examine generalized hazard risk (rather than a singular hazard), and (5) Focused on pre-disaster community conditions. After this, the research team identifies the commonly used indicators across these methodologies and selects the best data source for each indicator. Finally, the research team bins the data for visual display, conducts a correlation analysis and creates a composite index, the FEMA Community Resilience Index (FEMA CRI). In 2018, the CRIA identified eight resilience and vulnerability assessment methodologies and 20 commonly used indicators (indicators used in three or more of the eight methodologies). The FEMA CRI in 2018 was created from these 20 indicators and was produced for at the county level. The 2022 CRIA updated the literature review to expand the list of methodologies examined and followed the same process, resulting in an analysis of 14 methodologies published between 2003 and 2021 and 22 indicators identified as commonly used (indicators used in five or more of the 14 methodologies). In 2022, the research team produced the FEMA CRI at the county and the census tract levels. To make the CRIA data more accessible and more actionable, each individual indicator and the FEMA CRI is binned and included in FEMA’s Resilience Analysis and Planning Tool (RAPT). RAPT enables emergency managers and community partners to quickly visualize relative differences in potential resilience by county, tribe and census tract. By reviewing the data for each of these 22 indicators individually, emergency managers can gain insights for targeted outreach strategies, planning, mitigation investments and response and recovery operations. Communities, regional governments and others can use this data to better understand potential challenges to resilience. As the social science field of examining and validating indicators of resilience evolves, FEMA will update RAPT to provide emergency managers and community partners with additional data and tools to inform planning, mitigation, response and recovery. It is important to understand that the role of the emergency manager is not to change or to “improve” the data, but to plan appropriately for the community characteristics reflected in the data. These datasets are community characteristics that researchers have identified as important considerations for resilience. For example, people with disabilities may have greater challenges to be resilient to disasters. If a community has a high population of people with disabilities, the emergency manager(s) may need to create tailored preparedness outreach programs and strategies to ensure those residents have support if evacuation is necessary. Rather than label these indicators as an absolute measure of resilience, FEMA considers “potential challenges to resilience” a better frame to understand these indicators. Everyone is vulnerable to disasters. While scholars theorize that certain characteristics may make an individual or a household more socially vulnerable, the data does not reflect measures that individuals and/or communities have taken to address potential challenges, such as emergency management planning and outreach or household preparedness measures. To aid emergency managers in understanding how to use these indicators, calling them potential challenges to resilience supports a more positive and strategic application of the data in all phases of emergency management.

99 GENERAL AND MISCELLANEOUS↗

An open-source data storage and visualization platform for collaborative qubit control

Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization ( QubiCSV ), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.

97 MATHEMATICS AND COMPUTING↗

AmeriFlux FLUXNET-1F US-xAE NEON Klemme Range Research Station (OAES)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xAE NEON Klemme Range Research Station (OAES). This is the FLUXNET version of the carbon flux data for the site US-xAE NEON Klemme Range Research Station (OAES) produced by applying the standard ONEFlux (1F) software. Site Description - The 1,560-acre Klemme Range Research Station is a grassland site managed for livestock grazing and pasture, located in the middle of the Rolling Red Plains Resource Area. The Rolling Red Plains extends from south of the Red River to north of the Oklahoma/Kansas border consisting of approximately 9.4 million acres, which occupies a significant portion of Western Oklahoma excluding the Oklahoma Panhandle.

Network), NEON (National Ecological Observatory↗

Cases in the relation of research on remote sensing to decisionmakers in a state agency

The use is considered of various management tools in order to assess their effects on the anticipated relevance of the remote sensing research to the needs of government agencies. Among these tools are different organizational structures and ways of functioning, which are applied to the design and management of projects and to the communication of research results. The characteristics of data and information flow, and technology transfer are discussed along with the management of three projects and a remote sensing data center in terms of the use of some tools for influencing these processes.

Jondrow, J. W.↗

ADAMS: AIRLAB data management system user's guide

The AIRLAB Data Management System (ADAMS) is an online environment that supports research at NASA's AIRLAB. ADAMS provides an easy to use interactive interface that eases the task of documenting and managing information about experiments and improves communication among project members. Data managed by ADAMS includes information about experiments, data sets produced, software and hardware available in AIRLAB as well as that used in a particular experiment, and an on-line engineer's notebook. The User's Guide provides an overview of the ADAMS system as well as details of the operations available within ADAMS. A tutorial section takes the user step-by-step through a typical ADAMS session. ADAMS runs under the VAX/VMS operating system and uses the ORACLE database management system and DEC/FMS (the Forms Management System). ADAMS can be run from any VAX connected via DECnet to the ORACLE host VAX. The ADAMS system is designed for simplicity, so interactions within the underlying data management system and communications network are hidden from the user.

Conrad, C. L.↗

AmeriFlux FLUXNET-1F CA-ER1 Elora Research Station

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-ER1 Elora Research Station. This is the FLUXNET version of the carbon flux data for the site CA-ER1 Elora Research Station produced by applying the standard ONEFlux (1F) software. Site Description - This is an agricultural site that typically grows corn. It is part of a larger research project on N2O fluxes from different fertilizer treatments. The site is relatively flat and homogenous. The site has been managed as agricultural land since the 1960’s and records exist of the previously-grown crops.

Wagner-Riddle, Claudia↗

Automated Network Services for Exascale Data Movement

The Large Hadron Collider (LHC) experiments distribute data by leveraging a diverse array of National Research and Education Networks (NRENs), where experiment data management systems treat networks as a “blackbox” resource. After the High Luminosity upgrade, the Compact Muon Solenoid (CMS) experiment alone will produce roughly 0.5 exabytes of data per year. NREN Networks are a critical part of the success of CMS and other LHC experiments. However, during data movement, NRENs are unaware of data priorities, importance, or need for quality of service, and this poses a challenge for operators to coordinate the movement of data and have predictable data flows across multi-domain networks. The overarching goal of SENSE (The Software-defined network for End-to-end Networked Science at Exascale) is to enable National Labs and universities to request and provision end-to-end intelligent network services for their application workflows leveraging SDN (Software-Defined Networking) capabilities. This work aims to allow LHC Experiments and Rucio, the data management software used by CMS Experiment, to allocate and prioritize certain data transfers over the wide area network. In this paper, we will present the current progress of the integration of SENSE, Multi-domain end-to-end SDN Orchestration with QoS (Quality of Service) capabilities, with Rucio, the data management software used by CMS Experiment.

Balcas, Justas↗

Host genetic variation drives the differentiation in the ecological role of the native Miscanthus root-associated microbiome

Microbiome recruitment is influenced by plant host, but how host plant impacts the assembly, functions, and interactions of perennial plant root microbiomes is poorly understood. Here we examined prokaryotic and fungal communities between rhizosphere soils and the root endophytic compartment in two native Miscanthus species (Miscanthus sinensis and Miscanthus floridulus) of Taiwan and further explored the roles of host plant on root-associated microbiomes. Our results suggest that host plant genetic variation, edaphic factors, and site had effects on the root endophytic and rhizosphere soil microbial community compositions in both Miscanthus sinensis and Miscanthus floridulus, with a greater effect of plant genetic variation observed for the root endophytic communities. Host plant genetic variation also exerted a stronger effect on core prokaryotic communities than on non-core prokaryotic communities in each microhabitat of two Miscanthus species. From rhizosphere soils to root endophytes, prokaryotic co-occurrence network stability increased, but fungal co-occurrence network stability decreased. Furthermore, we found root endophytic microbial communities in two Miscanthus species were more strongly driven by deterministic processes rather than stochastic processes. Root-enriched prokaryotic OTUs belong to Gammaproteobacteria, Alphaproteobacteria, Betaproteobacteria, Sphingobacteriia, and [Saprospirae] both in two Miscanthus species, while prokaryotic taxa enriched in the rhizosphere soil are widely distributed among different phyla. We provide empirical evidence that host genetic variation plays important roles in root-associated microbiome in Miscanthus. The results of this study have implications for future bioenergy crop management by providing baseline data to inform translational research to harness the plant microbiome to sustainably increase agriculture productivity.

54 ENVIRONMENTAL SCIENCES↗

Development of data processing interpretation and analysis system for the remote sensing of trace atmospheric gas species

Problems associated with the development of the measurement of air pollution from satellites (MAPS) experiment program are addressed. The primary thrust of this research was the utilization of the MAPS experiment data in three application areas: low altitude aircraft flights (one to six km); mid altitude aircraft flights (eight to 12 km); and orbiting space platforms. Extensive research work in four major areas of data management was the framework for implementation of the MAPS experiment technique. These areas are: (1) data acquisition; (2) data processing, analysis and interpretation algorithms; (3) data display techniques; and (4) information production.

Casas, J. C.↗

The role of the World Data Centers in handling ocean climate data

The World Data Center System, set up for the International Geophysical Year in 1957, is an international network of data centers that links data contributors to data users in the geosciences. It includes means for the synthesis, analysis, and preparation of data products. It was set up in response to the needs of the international scientific community, and is still overseen by non-governmental scientific organizations. Because it is freely available to researchers in all countries, the World Data Center System has a special role to play in support of ocean climate research and monitoring programs. The World Data Centers face a number of challenges today. Apathy is probably the greatest, since many scientists take the system for granted. There is need to improve access and exploit new technology. The system must establish new links to assure continuity in a world with political changes. The multidisciplinary needs of global change research will demand capabilities for data and information management that go beyond the traditional emphasis on geophysics.

Webster, Ferris↗

Digraph reliability model processing advances and applications

This paper describes a new algorithm, called SourceDoubls, which efficiently solves for singletons and doubletons of a digraph reliability model. Compared with previous methods, the SourceDoubls algorithm provides up to a two order of magnitude reduction in the amount of time required to solve large digraph models. This significant increase in model solution speed allows complex digraphs containing thousands of nodes to be used as knowledge bases for real time automated monitoring and diagnosis applications. Currently, an application to provide monitoring and diagnosis of the Space Station Freedom Data Management System is under development at NASA/Ames Research Center and NASA/Johnson Space Center. This paper contains an overview of this system and provides details of how it will use digraph models processed by the SourceDoubls algorithm to accomplish its task.

Iverson, D. L.↗

Theoretical Studies of Molecular Spectra

This summary describes the research activities of the principal investigator during the reporting period. The research includes spectroscopy, management of molecular databases, and generation of spectral line profiles and opacity data. The spectroscopy research includes oxygen broadening of nitric oxide (NO), analysis of CO2 spectra, analysis of HNO3 spectra, and analysis of CO spectra.

McKay, Christopher↗

Pressure and Temperature Sensitive Paint Field System

This report documents the Pressure and Temperature Sensitive Paint Field System that is used to provide global surface pressure and temperature measurements on models tested in Langley wind tunnels. The system was developed and is maintained by Global Surface Measurements Team personnel of the Data Acquisition and Information Management Branch in the Research Facilities Services Competency. Descriptions of the system hardware and software are presented and operational procedures are detailed.

Sprinkle, Danny R.↗

Managing geometric information with a data base management system

The strategies for managing computer based geometry are described. The computer model of geometry is the basis for communication, manipulation, and analysis of shape information. The research on integrated programs for aerospace-vehicle design (IPAD) focuses on the use of data base management system (DBMS) technology to manage engineering/manufacturing data. The objectives of IPAD is to develop a computer based engineering complex which automates the storage, management, protection, and retrieval of engineering data. In particular, this facility must manage geometry information as well as associated data. The approach taken on the IPAD project to achieve this objective is discussed. Geometry management in current systems and the approach taken in the early IPAD prototypes are examined.

Dube, R. P.↗

NASA's Pilot Land Data System development program

The NASA Pilot Land Data System (PLDS) project is intended to enhance the effectiveness of data processing capabilities used by researchers applying remote sensing data in land science research. Two sites in the centerminous U.S. have been selected as study areas scanned by Landsat, Nimbus and GOES instruments. The data will be analyzed by teams of researchers representing different fields of expertise. The PLDS program will explore data management, networking and communications, system access capabilities, land analysis software, special processes and overall systems engineerng. The data will be processed by researchers working interactively through remote supermicrocomputer workstations using a variety of operating systems and on-site software capabilities.

Price, R. D.↗

A2SD: Accelerating Scientific Innovation Through Autonomous Discovery Systems

The 2025 Advancing Autonomous Scientific Discovery (A2SD) workshop convened researchers from academia, national laboratories, and industry to explore the transformative role of autonomy in scientific discovery. The workshop highlighted a convergence of artificial intelligence, robotics, and computational workflows into autonomous systems capable of accelerating the scientific process. Presentations and discussions spanned autonomous experimentation, intelligent workflow orchestration, digital twins, and agent-based systems for managing complex research ecosystems. Key challenges discussed included interoperability across heterogeneous infrastructures, near real-time data management under FAIR principles, reproducibility, and the integration of human oversight. The workshop also emphasized the need for modular software interfaces, federated learning models, and education initiatives to support a next-generation scientific workforce.

Taufer, Michela [University of Tennessee, Knoxvill↗