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ARM Aerosol Measurement Science Group 2019 Strategic Planning Workshop Report

This report summarizes the results of a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility workshop held in November 2019 to advance a science-based strategy for ARM’s aerosol measurement program. This was the second such workshop since the Aerosol Measurement Science Group (AMSG) was chartered in 2015 to enhance coordination of ARM observations of aerosols and atmospheric trace gases with the needs of ARM users. The results presented here reflect the AMSG’s focus in recent years on science-based strategies that will contribute to the increased use of ARM data to fulfill its mission of improving process representations and predictability in climate models. Sessions held during the workshop range from interfacing with models through aerosol sampling strategies to calibration protocols and data products. The AMSG workshops have been designed to recommend actions that will enable ARM to evolve and continue to meet its mission. To that end, the AMSG will develop an actionable plan from the recommendations outlined here. Some are well defined and can reasonably be accomplished in the short term. Others are less definite or of a larger scope that calls for a longer-term implementation. Further discussion will be required to develop and prioritize actionable items related to such areas. Task teams comprising the appropriate expertise and perspective from the AMSG and other members of the community will be formed to achieve this outcome. Some particular topics are recognized as high priority, so plans are underway to develop task teams and to hold follow-on discussions to address them. Four areas currently being considered for short, focused discussion are 1) aerosol measurements on the North Slope of Alaska, 2) improving data usability for modeling, 3) strategies for advancing remote sensing, vertical profiling, and distributed measurements of aerosols, and 4) aerosol sampling strategies at existing ARM sites to provide intensive modes of operation to promote data usage for process and modeling studies.

54 ENVIRONMENTAL SCIENCES↗

Archival, anonymization and presentation of HTCondor logs with GlideinMonitor

GlideinWMS is a pilot framework to provide uniform and reliable HTCondor clusters using heterogeneous and unreliable resources. The Glideins are pilot jobs that are sent to the selected nodes, test them, set them up as desired by the user jobs, and ultimately start an HTCondor schedd to join an elastic pool. These Glideins collect information that is very useful to evaluate the health and efficiency of the worker nodes and invaluable to troubleshoot when something goes wrong. This data, including local stats, the results of all the tests, and the HTCondor log files, is packed and sent to the GlideinWMS Factory. To access this information, developers and troubleshooters must exchange emails with Factory operators and dig manually into files. Furthermore, these files contain also information like email and IP addresses, and user IDs, that we want to protect and limit access to. GlideinMonitor is a Web application to make these logs more accessible and useful: it organizes the logs in an efficient compressed archive; it allows to search, unpack, and inspect them, all in a convenient and secure Web interface; via plugins like the log anonymizer, it can redact protected information preserving the parts useful for troubleshooting.

Mambelli, Marco↗

Microbial sensor system for monitoring the environment and surfaces

A microbial sensor, system and method that can be used to determine the biochemical conditions of waters, saturated sediments, unsaturated soils, rhizosphere and other environments is disclosed. The flexibility of the microbial sensor design allows for the monitoring of surfaces (skin, ventilation conduits, etc.). An electrochemical microbial sensor system is composed of an indicator electrode(s) and a reference electrode. The reference electrode employs a hydrogen permeable membrane. The electrochemical system is interfaced into a signal/communication module allowing the manual or automated collection of data from field deployments and laboratory investigations. The data is transmitted using various communication technologies including Bluetooth™, cellular, satellite and radio telemetry to cloud-based data management systems. The stored data may be downloaded by users using open-source dashboard and visualization software to image the various environments and/or surfaces investigated.

Burge, Scott R.↗

A Numerical Simulation of Transport Phenomena During the Horizontal Single Belt Casting Process Using an Inclined Feeding System

Horizontal single belt casting (HSBC) has great potential to replace current conventional continuous casting (CCC) processes for sheet metal production, by directly casting 3 to 1 mm sheet for the automobile industry. In the present paper, two-dimensional mathematical models were developed to study transport phenomena, for the case of an inclined wall feeding system for a liquid aluminum wrought alloy (AA6111). Based on the commercial software ANSYS FLUENT 14.5 and user-defined functions, a two-layer turbulence model was used to examine the fluid flow emanating from a slot nozzle set above a water-cooled, high-speed, steel belt. The Volume of Fluid (VOF) method was used to predict the shape of the melt-air interface. A transformed coordinate system (x′, y′) was established in order to analyze the fluid flow on the inclined wall of the feeding system. The total pressure gauge gradient (∂p{sub total}/∂x) was used to describe the behavior of the melt film inside the slot nozzle of the head box. The modeling results show that during the melt film falling process, the total gauge pressure varies within the slot nozzle, which can decrease the stability of the falling film. The first impingement between the falling film and the inclined refractory wall of the feeding system gives rise to a local oscillation, and this influences the stability of the melt film moving downwards. At the rear meniscus position between the inclined wall and the moving belt, there is a clear vibration of the air-melt interface, together with a recirculation zone. The weak vibration of the air-melt interface could be induced by the periodic variation of the melt-air interface. Moreover, the formation of tiny air pockets is predicted. Finally, on the inclined wall of the feeding system, a suitable length of the transition area is needed to avoid over-acceleration of the melt film due to the force of gravity.

36 MATERIALS SCIENCE↗

Experimental validation of advanced regulations for superconducting magnet cooling undergoing periodic heat loads

Superconducting magnets used in tokamaks undergo periodic heat load caused by cycling plasma operations inducing AC losses, neutrons fluxes and eddy currents in magnet structures. In the cryogenic system of JT60-SA tokamak, the Auxiliary Cold Box (ACB) distributes helium from the refrigerator to the cryogenic users and in particular to the superconducting magnets. ACB comprises a saturated helium bath with immersed heat exchangers, extracting heat from independent cooling loops. The supercritical helium flow in each cooling loop is driven by a cold circulator. In order to safely operate the refrigerator during plasma pulses, the interface between the ACB and the refrigerator shall be as stable as possible, with well-balanced bath inlet and outlet mass flows during cycling operation. The solution presented in this paper relies on a combination of regulations to smooth pulsed heat loads and to keep a constant refrigeration power during all the cycle. Two smoothing strategies are presented, both regulating the outlet mass flow of the bath: the first one using the bath as a thermal buffer and the second one storing energy in the loop by varying the cold circulator speed. The bath outlet mass flow is also controlled by an immersed resistive heater which enables a constant evaporation rate in the bath when power coming from the loops is decreasing. The refrigeration power is controlled so that the compensating power remains within an acceptable margin. Experimental validation is achieved using the HELIOS facility. This facility running at CEA Grenoble since 2010 is a scaled down model of the ACB bath and Central Solenoid magnet cooling loop of the JT60-SA tokamak. Test results show performances and robustness of the regulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SonicPy: a suite of programs for ultrasound pulse-echo data acquisition and analysis

Sound speed and elastic constants measurements in solids and liquids are commonly performed using the ultrasound pulse-echo technique. Recent advances have expanded the use of this technique at numerous high pressure synchrotron beamlines and offline laboratories. However, the increased experimental throughput has revealed many limitations in existing software for handling the rapid measurement and the subsequent data-reduction. Here, we report the development of a collection of computer programs for sound speed measurements using the ultrasound pulse-echo technique, compatible with stepped multi-frequency, as well as broadband-pulse, couplant-corrected methods. The programs provide a highly interactive graphical interface, enable efficient measurement, exploration and near real-time analysis of the ultrasound data, and contain features useful for working with samples under high pressure and/or high temperature. The included analysis programs can alleviate the time required for data reduction from hours to less than a minute, allowing users to make timely and informed decisions regarding the appropriate experimental parameters.

97 MATHEMATICS AND COMPUTING↗

Scalable Reasoning System (SRS)

SRS is a web-based and mobile toolkit for information visualization and collaboration. It includes server-side components in the form of web services that provide analytical functions such as data clustering and temporal analysis. The SRS client is accessed via a web browser and uses asynchronous javascript and XML (AJAX) to interact with and visualize the results of these web services. Users of SRS can query data sources that are connected to the SRS backend, and query results are presented in the form of coordinated visual displays in a web browser that depict temporal, topical, and spatial relationships in the results. SRS also includes an early stage graphical reasoning diagram interface that helps analysts express and test hypotheses. This software was developed with funding from the Science and Technology Directorate of the U.S. Department of Homeland Security.

Pike, William↗

Charon User Manual (V.2.1) (Rev.01)

This manual gives usage information for the Charon semiconductor device simulator. Charon was developed to meet the modeling needs of Sandia National Laboratories and to improve on the capabilities of the commercial TCAD simulators; in particular, the additional capabilities are running very large simulations on parallel computers and modeling displacement damage and other radiation effects in significant detail. The parallel capabilities are based around the MPI interface which allows the code to be ported to a large number of parallel systems, including linux clusters and proprietary "big iron" systems found at the national laboratories and in large industrial settings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Seascape Interface Control Document

This all-inclusive document describes the components, installation, and usage of the Seascape system. Additionally, this manual outlines the step-by-step processes for setting up your own local instance of Seascape, incorporating new datasets and algorithms into Seascape, and how to use the system itself. A brief overview of Seascape is provided in Section 1.2. System components and the various roles of the intended users of the system are described in Section 1.3. Next, steps on how each role uses Seascape are explained in Section 2.1. Finally, the steps to incorporate data into Seascape-DB and an algorithm into Seascape-VV are outlined in Sections 2.2 and 2.3, respectively. Steps to set up an instance of Seascape can be found in Appendix A.1. Finally, Seascape usage can be found in Section 2.1. The appendix includes code examples, frequently asked questions, terminology, and a list of acronyms.

97 MATHEMATICS AND COMPUTING↗

Modeling Non-UO2 Fuel With UNF-ST&DARDS

The U.S. Department of Energy’s Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) provides an easy-to-use interface to analyze irradiated UO2 fuel by allowing all analysis to be performed within the software and being able to store and use dozens of fuel assembly, canister, and cask designs [1]. However, performing these same analyses with non-UO2 fuel, such as UN or U3Si2, requires more user intervention in the process. This work uses UN, UN-ZrO2, and U3Si2 fuel to demonstrate how to perform criticality analyses in the current versions of UNF-ST&DARDS and how a non-UO2 fuel will compare to UO2. This work is part of a larger effort that also includes shielding and thermal analyses, but they will not be discussed.

Ivanusa, Pavlo↗

Snow ALbedo eVOlution (SALVO) Campaign Snow Depth and Related Surface Properties from April - June, 2024 in Utqiagivk, AK

Detailed transects of snow depths and related measurements were made with a magnaprobe along fixed lines in Utqiagvik, AK. The operator measures snow depth by plunging a rod with a sliding basket into the snow and pressing a trigger. At this point, the data logger records the distance between the tip of the rod and the height of the basket, the measurement number, the time, and the geographic location of the measurement. To measure snow depth, the rod tip must be placed at the snow-ground or snow-sea ice interface. The interface can be hard or soft; in the latter case, it is possible to “over-probe”, producing a snow depth that is too high. At times, the probe was also used to measure the depths of other interfaces within the snowpack (for example, the depth to persistent ice lenses) or the water depths of ponds atop the tundra or sea ice. When these alternative depth measurements were made, the operator recorded the location, measurement number, and composition of the alternative depth measurement in a field notebook. The data logger on the probe stores several thousand points. Data is downloaded to a computer at the end of a day or several days. Probes: We used 2 magnaprobes identified as GEO1 and GEODEL with the following serial numbers: S/N 20240416 (GEO1) and S/N P48066 (GEODEL). Note : There are three data levels available with this dataset: b3, b4, and a6. New users of these data are strongly encouraged to use the level a6 or b4 data.

54 ENVIRONMENTAL SCIENCES↗

Charon User Manual: v. 2.2 (revision1)

This manual gives usage information for the Charon semiconductor device simulator. Charon was developed to meet the modeling needs of Sandia National Laboratories and to improve on the capabilities of the commercial TCAD simulators; in particular, the additional capabilities are running very large simulations on parallel computers and modeling displacement damage and other radiation effects in significant detail. The parallel capabilities are based around the MPI interface which allows the code to be ported to a large number of parallel systems, including linux clusters and proprietary “big iron” systems found at the national laboratories and in large industrial settings.

42 ENGINEERING↗

Extending C++ for Heterogeneous Quantum-Classical Computing

In this report we present qcor - a language extension to C++ and compiler implementation that enables heterogeneous quantum-classical programming, compilation, and execution in a single-source context. Our work provides a first-of-its-kind C++ compiler enabling high-level quantum kernel (function) expression in a quantum-language agnostic manner, as well as a hardware-agnostic, retargetable compiler workflow targeting a number of physical and virtual quantum computing backends. qcor leverages novel Clang plugin interfaces and builds upon the XACC system-level quantum programming framework to provide a state-of-the-art integration mechanism for quantum-classical compilation that leverages the best from the community at-large. qcor translates quantum kernels ultimately to the XACC intermediate representation, and provides user-extensible hooks for quantum compilation routines like circuit optimization, analysis, and placement. This work details the overall architecture and compiler workflow for qcor, and provides a number of illuminating programming examples demonstrating its utility for near-term variational tasks, quantum algorithm expression, and feed-forward error correction schemes.

97 MATHEMATICS AND COMPUTING↗

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗

Guidelines for effective radiation transport for cable SGEMP modeling

This report describes experiences gained in performing radiation transport computations with the SCEPTRE radiation transport code for System Generated ElectroMagnetic Pulse (SGEMP) applications. SCEPTRE is a complex code requiring a fairly sophisticated user to run the code effectively, so this report provides guidance for analysts interested in performing these types of calculations. One challenge in modeling coupled photon/electron transport for SGEMP is to provide a spatial mesh that is sufficiently resolved to accurately model surface charge emission and charge deposition near material interfaces. The method that has been most commonly used to date to compute cable SGEMP typically requires a sub-micron mesh size near material interfaces, which may be difficult for meshing software to provide for complex geometries. We present here an alternative method for computing cable SGEMP that appears to substantially relax this requirement. The report also investigates the effect of refining the energy mesh and increasing the order of the angular approximation to provide some guidance on determining reasonable parameters for the energy/angular approximation needed for x-ray environments. Conclusions for γ-ray environments may be quite different and will be treated in a subsequent report. In the course of the energy-mesh refinement studies, a bug in the cross-section generation software was discovered that may cause underprediction of the result by as much as an order of magnitude for the test problem studied here, when the electron energy group widths are much smaller than those for the photons. Results will be presented and compared using cross sections generated before and after the fix. We also describe adjoint modeling, which provides sensitivity of the total charge drive to the source energy and angle of incidence, which is quite useful for comparing the effect of changing the source environment and for determining most stressing angle of incidence and source energy. This report focusses on cable SGEMP applications, but many of the conclusions will be directly applicable for box Internal ElectroMagnetic Pulse (IEMP) modeling as well.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Dial

A key step in almost all scientific endeavors is answering the question: Given this data I already collected, what new data do I expect will yield the most useful information toward my scientific objective? The area of (sequential) experimental design has long been investigating answers to this question, but in recent years techniques from the machine learning subfield of active learning are increasingly applied. Researchers need a simple software tool for active learning applied to experimental design that can easily integrate into their existing workflows. This computer code, Dial, provides a microservice in ORNL's INTERSECT ecosystem for active learning applied to experimental design. By being part of the INTERSECT ecosystem, Dial is simple to integrate into any INTERSECT-based workflow. Dial provides multiple backend options, where a backend is an implementation of a specific active learning method. Users can select the backend that performs best for their application. Developers can also add new backends as needed. At its core, Dial receives a set of pre-existing measurements and input parameter bounds and then recommends one or more new sets of parameters to measure. Dial also includes interfaces to other microservices in the INTERSECT ecosystem so that it can be incorporated into INTERSECT campaigns. Dial provides a simple, yet powerful interface to convert automated INTERSECT workflows into autonomous workflows that adapt based on the results that are obtained. A shared microservice for active learning prevents duplicated effort by each application team implementing its own adaptive design of experiments tool.

Drane, Lance [Oak Ridge National Laboratory (ORNL)↗

Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) Field Campaign Report

The Southern Ocean (SO) is the stormiest place on earth, buffeted by winds and waves that circle the ice of Antarctica, sheathed in clouds that mantle a dynamic ocean with rich ecosystems. The remote and usually pristine environment, typically removed from anthropogenic and natural continental aerosol sources, makes the SO unique for examining cloud-aerosol interactions for liquid and ice clouds, and the role of primary and secondary marine biogenic aerosols and sea salt. There is strong seasonality in aerosol sources and sinks over the SO that are poorly understood. Weather and climate models are challenged by uncertainties and biases in the simulation of SO clouds, aerosols, precipitation, and radiative transfer that trace to poor physical understanding of these processes, and by cloud feedbacks (e.g., phase changes) in response to warming. Models almost universally underestimate sunlight reflected by near-surface cloud, particularly in the cold sector of cyclonic storm systems, and this may be due to difficulties in representing pervasive supercooled and mixed-phase boundary-layer (BL) clouds. The Southern Ocean Clouds Radiation Transport Aerosol Transport Experimental Study (SOCRATES) white paper (Marchand et al. 2014) describes the motivation, scientific themes, and testable hypotheses that led to a multi-agency and international measurement campaign to study clouds, aerosols, and the air-sea interface over the SO. As a separate project within this international umbrella, the Measurement of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field program was conducted between 29 October 2017 and 25 March 2018. During MARCUS, instruments from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s second Mobile Facility (AMF2) were installed on the Australian icebreaker Aurora Australis as it made resupply missions from Hobart, Tasmania to the Australian Antarctic stations of Casey, Mawson, and Davis, as well as Macquarie Island. Figure 1 shows the voyages conducted during MARCUS. The MARCUS data are unique in that they are the only set of data in the broader international effort that a) acquired comprehensive observations of clouds, aerosols, and radiation south of 60°S, and b) acquired measurements across the full SO latitudinal range in the spring and fall seasons.

atmospheric emitted radiance interferometer↗

THE NEW ONLINE METADATA EDITOR FOR GENERATING STRUCTURED METADATA

Nobody is better suited to “describe” data than the scientist who created it. This “description” about a data is called Metadata. In general terms, Metadata represents the who, what, when, where, why and how of the dataset [1]. eXtensible Markup Language (XML) is the preferred output format for metadata, as it makes it portable and, more importantly, suitable for system discoverability. The newly developed ORNL Metadata Editor (OME) is a Web-based tool that allows users to create and maintain XML files containing key information, or metadata, about the research. Metadata include information about the specific projects, parameters, time periods, and locations associated with the data. Such information helps put the research findings in context. In addition, the metadata produced using OME will allow other researchers to find these data via Metadata clearinghouses like Mercury [2][4]. OME is part of ORNL’s Mercury software fleet [2][3]. It was jointly developed to support projects funded by the United States Geological Survey (USGS), U.S. Department of Energy (DOE), National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA). OME’s architecture provides a customizable interface to support project-specific requirements. Using this new architecture, the ORNL team developed OME instances for USGS’s Core Science Analytics, Synthesis, and Libraries (CSAS&L), DOE’s Next Generation Ecosystem Experiments (NGEE) and Atmospheric Radiation Measurement (ARM) Program, and the international Surface Ocean Carbon Dioxide ATlas (SOCAT).Researchers simply use the ORNL Metadata Editor to enter relevant metadata into a Web-based form. From the information on the form, the Metadata Editor can create an XML file on the server that the editor is installed or to the user’s personal computer. Researchers can also use the ORNL Metadata Editor to modify existing XML metadata files.As an example, an NGEE Arctic scientist use OME to register their datasets to the NGEE data archive and allows the NGEE archive to publish these datasets via a data search portal (http://ngee.ornl.gov/data). These highly descriptive metadata created using OME allows the Archive to enable advanced data search options using keyword, geo-spatial, temporal and ontology filters. Similarly, ARM OME allows scientists or principal investigators (PIs) to submit their data products to the ARM data archive.How would OME help Big Data Centers like the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC)?The ORNL DAAC is one of NASA’s Earth Observing System Data and Information System (EOSDIS) data centers managed by the Earth Science Data and Information System (ESDIS) Project. The ORNL DAAC archives data produced by NASA's Terrestrial Ecology Program. The DAAC provides data and information relevant to biogeochemical dynamics, ecological data, and environmental processes, critical for understanding the dynamics relating to the biological, geological, and chemical components of the Earth's environment. Typically data produced, archived and analyzed is at a scale of multiple petabytes, which makes the discoverability of the data very challenging. Without proper metadata associated with the data, it is difficult to find the data you are looking for and equally difficult to use and understand the data.OME will allow data centers like the NGEE and ORNL DAAC to produce meaningful, high quality, standards-based, descriptive information about their data products in-turn helping with the data discoverability and interoperability. Useful Links:USGS OME: http://mercury.ornl.gov/OME/NGEE OME: http://ngee-arctic.ornl.gov/ngeemetadata/ARM OME: http://archive2.ornl.gov/armome/Contact: Ranjeet Devarakonda (devarakondar@ornl.gov)References:[1] Federal Geographic Data Committee. Content standard for digital geospatial metadata. Federal Geographic Data Committee, 1998.[2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.[3] Wilson, B. E., Palanisamy, G., Devarakonda, R., Rhyne, B. T., Lindsley, C., & Green, J. (2010). Mercury Toolset for Spatiotemporal Metadata.[4] Pouchard, L. C., Branstetter, M. L., Cook, R. B., Devarakonda, R., Green, J., Palanisamy, G., ... & Noy, N. F. (2013). A Linked Science investigation: enhancing climate change data discovery with semantic technologies. Earth science informatics, 6(3), 175-185.

FGDC CSDGM↗

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