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At least 109 records · Page 6

An architecture for a brain-image database

The widespread availability of methods for noninvasive assessment of brain structure has enabled researchers to investigate neuroimaging correlates of normal aging, cerebrovascular disease, and other processes; we designate such studies as image-based clinical trials (IBCTs). We propose an architecture for a brain-image database, which integrates image processing and statistical operators, and thus supports the implementation and analysis of IBCTs. The implementation of this architecture is described and results from the analysis of image and clinical data from two IBCTs are presented. We expect that systems such as this will play a central role in the management and analysis of complex research data sets.

NASA Discipline Neuroscience↗

Data and information system requirements for Global Change Research

Efforts to develop local information systems for supporting interdisciplinary Global Change Research are described. A prototype system, the Interdisciplinary Science Data and Information System (IDS-DIS), designed to interface the larger archives centers of EOS-DIS is presented. Particular attention is given to a data query information management system (IMS), which has been used to tabulate information of Landsat data worldwide. The use of these data in a modeling analysis of deforestation and carbon dioxide emissions is demonstrated. The development of distributed local information systems is considered to be complementary to the development of central data archives. Global Change Research under the EOS program is likely to result in proliferation of data centers. It is concluded that a distributed system is a feasible and natural way to manage data and information for global change research.

Skole, David L.↗

Transforming Drainage Research Data (USDA-NIFA Award No. 2015-68007-23193)

This dataset contains research data compiled by the “Managing Water for Increased Resiliency of Drained Agricultural Landscapes” project a.k.a. Transforming Drainage. This project was funded from 2015-2021 by the United States Department of Agriculture, National Institute of Food and Agriculture (USDA-NIFA, Award No. 2015-68007-23193). Data are also available from a separate web-accessible application (drainagedata.org). At drainagedata.org, users can visualize the data with customized tools, query based on specific sites and measurements of interest, and access site photographs, maps, summaries, and publications. Additional data or edits made following the publication of this data here at USDA NAL Ag Data Commons will be posted under the Versions tab on drainagedata.org. These data began in 1996 and include plot- and field-level measurements for 39 experiments across the Midwest and North Carolina. Practices studied include controlled drainage, drainage water recycling, and saturated buffers. In total, 219 variables are reported and span 207 site-years for tile drainage, 154 for nitrate-N load, 181 for water quality, 92 for water table, and 201 for crop yield.

Modeling↗

Data for publication: "A fresh take: Seasonal changes in terrestrial freshwater inputs impact salt marsh hydrology and vegetation dynamics"

This data repository contains data associated with the manuscript "A fresh take: Seasonal changes in terrestrial freshwater inputs impact salt marsh hydrology and vegetation dynamics". This study was conducted at the Elkhorn Slough National Estuarine Research Reserve in Watsonville, California from October 2019 - June 2022. We sought to understand the role of shallow freshwater inputs from adjacent uplands on salt marsh hydrologic behavior and vegetation productivity. This dataset contains CSV files of the following: daily salt marsh subsurface water level and pore water conductivity, monthly vegetation survey measurements, soil core data. Estuary surface water level, conductivity, and local precipitation were downloaded from the National Estuarine Research Reserve System (Centralized Data Management Office) at https://cdmo.baruch.sc.edu/.

54 ENVIRONMENTAL SCIENCES↗

The Silencing of U.S. Campuses Following the COVID-19 Response: Evaluating Root Mean Square Seismic Amplitudes Using Power Spectral Density Data

In response to the COVID-19 global pandemic, many populated and active regions have become deserted and show significant reductions in their background seismicity, especially campuses across the United States (U.S.). Seismic sensors located in the vicinity of or within U.S. campuses show that anthropogenic seismic noise remains elevated during the ordinary, nonpandemic, academic year, only subduing during periods of recess (e.g., winter break). Here, we use power spectral density (PSD) data computed by the Incorporated Research Institutions for Seismology Data Management Center for quality assessment to calculate root mean square (rms) amplitude and analyze the effects of the COVID-19 school closures. We processed and analyzed PSD data for 46 seismic stations located within 50 m of a U.S. university or college. Results show that 42 campus stations show an overall rms drop following a statewide school closure.

58 GEOSCIENCES↗

New Architecture to Support Integration and Processing of Seismic Data from Heterogeneous Sources

The Geophysical Monitoring Program (GMP) at Lawrence Livermore National Lab (LLNL) maintains a database and supporting infrastructure for geophysical data used in support of the Nuclear Detonation Detection mission. This database includes data from multiple sources, many of which do not distribute data to the public or for which there is no automated means of access. For example, Figure 1 shows (left) the distribution of waveform data in our database by source. The Incorporated Research Institutions for Seismology Data Management Center (IRISDMC) is our major source of waveform data and those data may be retrieved at will using the Federated Digital Seismograph Networks FDSN web Application Programming Interface (API). However, the next 6 most important sources of waveform data have no or only limited automated access to waveforms. As Figure 1 (right) shows, it is very common for waveform records associate with an event in our database to come from two or more sources, and in some cases data come from 10 sources. This diversity of data sources drives our need for efficient and correct integration of metadata, parametric data, and waveform data.

58 GEOSCIENCES↗

Virtual interface environment

A head-mounted, wide-angle, stereoscopic display system controlled by operator position, voice and gesture is under development for use as a multipurpose interface environment. Initial applications of the system are in telerobotics, data-management and human factors research. System configuration and research directions are described.

Fisher, Scott S.↗

Automated extraction of metadata from remotely sensed satellite imagery

The paper discusses research in the Intelligent Data Management project at the NASA/Goddard Space Flight Center, with emphasis on recent improvements in low-level feature detection algorithms for performing real-time characterization of images. Images, including MSS and TM data, are characterized using neural networks and the interpretation of the neural network output by an expert system for subsequent archiving in an object-oriented data base. The data show the applicability of this approach to different arrangements of low-level remote sensing channels. The technique works well when the neural network is trained on data similar to the data used for testing.

Cromp, Robert F.↗

Modifying the Heliophysics Data Policy to Better Enable Heliophysics Research

The Heliophysics (HP) Science Data Management Policy, adopted by HP in June 2007, has helped to provide a structure for the HP data lifecycle. It provides guidelines for Project Data Management Plans and related documents, initiates Resident Archives to maintain data services after a mission ends, and outlines a route to the unification of data finding, access, and distribution through Virtual observatories. Recently we have filled in missing pieces that assure more coherence and a home for the VxOs (through the 'Heliophsyics Data and Model Consortium'), and provide greater clarity with respect to long term archiving. In particular, the new policy which has been vetted with many community members, details the 'Final Archives' that are to provide long-term data access. These are distinguished from RAs in that they provide little additional service beyond servicing data, but critical to their success is that the final archival materials include calibrated data in useful formats such as one finds in CDAWeb and various ASCII or FITS archives. Having a clear goal for legacy products, to be detailed as part of the Mission Archives Plans presented at Senior Reviews, will help to avoid the situation so common in the past of having archival products that preserve bits well but not readily usable information. We hope to avoid the need for the large numbers of 'data upgrade' projects that have been necessary in recent years.

Hayes, Jeffrey↗

Earth Science Informatics Comes of Age

The volume and complexity of Earth science data have steadily increased, placing ever-greater demands on researchers, software developers and data managers tasked with handling such data. Additional demands arise from requirements being levied by funding agencies and governments to better manage, preserve and provide open access to data. Fortunately, over the past 10-15 years significant advances in information technology, such as increased processing power, advanced programming languages, more sophisticated and practical standards, and near-ubiquitous internet access have made the jobs of those acquiring, processing, distributing and archiving data easier. These advances have also led to an increasing number of individuals entering the field of informatics as it applies to Geoscience and Remote Sensing. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of data, information, and knowledge. Informatics also encompasses the use of computers and computational methods to support decisionmaking and other applications for societal benefits.

Jodha, Siri↗

Data Release Report for the Source Physics Experiment Phase II: Dry Alluvium Geology Experiments (DAG-1 through DAG-4), Nevada National Security Site

The Dry Alluvium Geology (DAG) project was Phase II of the Source Physics Experiment and consisted of a series of four chemical explosive tests conducted in the same source hole on the Nevada National Security Site. This hole is located at 37.1146°N and -116.0693°W, with a surface elevation of 1,285.2 meters (m) (4,216.5 feet [ft]) above sea level. The first test (DAG-1) was conducted on July 20, 2018, at 16:51:52.67838 Coordinated Universal Time (UTC). The explosive source for DAG-1 was nitromethane initiated by a small plastic-bonded explosive (PBX) charge, detonated at the depth of 385.0 m (1,263.2 ft) below ground surface. DAG-1 had a trinitrotoluene (TNT) equivalent yield of 0.908 metric tons (2,002 pounds [lbs]). DAG-2 was conducted on December 19, 2018, at 18:45:56.92115 UTC. This test was the largest in the series, with a TNT equivalent yield of 50.997 metric tons (112,429 lbs). The explosive source for DAG-2 was nitromethane initiated by a small PBX charge, detonated at the depth of 299.8 m (983.6 ft) below ground surface. DAG-3 was conducted on April 27, 2019, at 15:49:01.84183 UTC. The explosive source for this test was nitromethane initiated by a small PBX charge, detonated at the depth of 149.9 m (492.0 ft) below ground surface. DAG-3 had a TNT equivalent yield of 0.908 metric tons (2,002 lbs). The final DAG test (DAG-4) was conducted on June 22, 2019, at 21:06:19.87632 UTC. The explosive source for DAG-4 was nitromethane initiated by a small PBX charge, detonated at the depth of 51.6 m (169.3 ft) below ground surface. DAG-4 had a TNT equivalent yield of 10.357 metric tons (22,833 lbs). The four tests were recorded by an extensive set of instrumentation that included sensors both at near-field (less than 200 m) and far-field (200 m or greater) distances. The near-field instruments consisted of three-component (3C) accelerometers installed at various depths ranging from 51.6 to 385 m (169.3 to 1,263.1 ft) below ground surface in boreholes positioned around the source hole, and arrays of single-component and 3C accelerometers on the surface. The far-field network comprised a variety of seismic and acoustic sensors, including short-period geophones, broadband seismometers, and 3C accelerometers at distances of 200 m to 400 kilometers. In addition, the DAG-2, DAG-3, and DAG-4 explosions were recorded by a temporary array of 496 geophones arranged in a densely spaced grid pattern known as “Large N.” This report coincides with the release of these data for analysts and organizations that are not participants in this program. This report describes the four DAG tests and the various types of near-field, far-field, and other data that are available. Assembled data sets are accessible through: Incorporated Research Institutions for Seismology, Data Management Center 1408 NE 45th Street, Suite 201, Seattle, Washington 98105 USA. www.iris.washington.edu

58 GEOSCIENCES↗

An open source fast fluid dynamics model for data center thermal management

Although computational fluid dynamics (CFD) has been widely adopted to improve data center thermal management, the high computational demand limits its applications, such as multivariate optimal design and operation. Fast fluid dynamics (FFD), which has been applied for fast airflow simulation, shows great potential. However, few research applied FFD for optimal design and operation of data center thermal management. This research improves the FFD model for data centers and conducts a comprehensive evaluation and demonstration. First, the FFD model is improved by solving the advection and diffusion equations together using an upwind scheme instead of a semi-Lagrangian advection solver in the conventional FFD model. Second, new features for data centers are added, such as a pressure correction method to simulate plenum airflow and dynamic boundary conditions for IT racks. The new FFD model is first validated with two indoor environment cases and the results show that the new FFD model has slightly better overall prediction accuracy and faster speed compared to the conventional FFD model. It is also observed that both FFD models achieve acceptable accuracy, except for a few localized disparities with experimental data, which might be due to simplified handling of turbulence viscosity near the boundaries. Furthermore, validation with a real data center shows that the FFD model achieves a similar level of accuracy as CFD when compared to the experimental measurements with some level of uncertainties. It is then demonstrated for data center optimal design and operation, which saves 53.4–58.8% of annual energy while still meeting the thermal requirements. In conclusion, with a much faster speed and comparable accuracy compared to CFD, the FFD model parallelized on a graphics processing unit is promising for practical model-based data center early design and operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impact of computer advances on future finite elements computations

Research performed over the past 10 years in engineering data base management and parallel computing is discussed, and certain opportunities for research toward the next generation of structural analysis capability are proposed. Particular attention is given to data base management associated with the IPAD project and parallel processing associated with the Finite Element Machine project, both sponsored by NASA, and a near term strategy for a distributed structural analysis capability based on relational data base management software and parallel computers for a future structural analysis system.

Fulton, Robert E.↗

Small Unmanned Aircraft System Off Nominal Operations Reporting System Unmanned Aircraft System: Traffic Management Technical Capability Level 4 Implementation, Data Collection and Analysis

NASA performed research and development of technologies and requirements for traffic management of small Unmanned Aircraft Systems (UAS). In this effort, a small UAS off-nominal situation reporting system was developed to capture information from off-nominal situations to understand their nature and reduce occurrences. This Technical Memorandum (TM) describes the reporting system and analysis of 116 off-nominal situation reports from 352 small UAS operations, which were conducted at two flight test ranges in Summer 2019.

Jung, Jaewoo↗

Employing Technology to Enable Remote Research Charrettes as a Method for Engaging Industry and Uncovering Best Practices: A Novel Approach for a Post-COVID-19 World

Methods to collect data in construction engineering and management (CEM) research are evolving, informed by recent technological advancements. One such method is research charrettes that allow effective interactions and knowledge sharing between expert industry practitioners and academic researchers, all colocated in a single venue, enabling rich data collection and live communication. A pivot point in technological evolution occurred with the COVID-19 pandemic, forcing a global shift to remote work. Hence, planned in-person research charrettes had to shift to remote sessions, relying on virtual conferencing platforms and online data collection mechanisms. Technology-enabled charrettes have allowed the authors to collect significantly richer data sets and ensure a more diverse representation of participants, while saving tremendous amounts of time. With the continuing emergence of technological applications, the world might not go back to functioning fully in person. The authors believe remote research charrettes (RRCs) will still be used in a post-COVID-19 world because of their superior performance. This paper builds on a previous publication that described traditional research charrettes as a method to enhance CEM research a decade ago; it offers a significantly updated and improved RRC method based on the knowledge gained from transitioning a dozen in-person charrettes into RRCs. It also presents performance comparisons between RRCs and traditional charrettes by quantifying metrics indicating how RRCs are more time-efficient and cost-saving, harness more participants from more diverse locations, and enable the collection of richer data sets and four times more industry comments and expert feedback. This paper also provides guidance on the integration of technology with traditional research charrettes, hence contributing to the CEM body of knowledge.

42 ENGINEERING↗

Data as a Key Resource in Catalysis: A Community Account

The deployment of artificial intelligence (AI) is transforming the scientific fields central to interdisciplinary catalysis research. By enabling more effective use of data, AI (including simpler machine learning and data science tools) holds great promise for accelerating discoveries. However, progress has so far been modest, largely due to the lack of standardized, machine-readable, and openly shared catalysis data. This perspective, accounting for community insights emerging at conferences, analyses the underlying reasons for these challenges and proposes solutions to a future whereFAIR data management becomes an integral part of research in catalysis. In the short-term, we deem that mandatory FAIR data depositing prior to scientific publications along with consensualized top-down guidelines on data sharing powered by ease-to-use tools can make the necessary step change happen to catalyse data as key resource in our community.

36 - MATERIALS SCIENCE↗

Data management at Biosphere 2 center

Throughout the history of Biosphere 2, the collecting and recording of biological data has been sporadic. Currently no active effort to administer and record regular biological surveys is being made. Also, there is no central location, such as an on-site data library, where all records from various studies have been archived. As a research institute, good, complete data records are at the core of all Biosphere 2's scientific endeavors. It is therefore imperative that an effective data management system be implemented within the management and research departments as soon as possible. Establishing this system would require three general phases: (1) Design/implement a new archiving/management program (including storage, cataloging and retrieval systems); (2) Organize and input baseline and intermediate data from existing archives; and (3) Maintain records by inputting new data.

McCreary, Leone F.↗