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DOE OSTI2024

Challenges of open data in aquatic sciences: issues faced by data users and data providers

Free use and redistribution of data (i.e., Open Data) increases the reproducibility, transparency, and pace of aquatic sciences research. However, barriers to both data users and data providers may limit the adoption of Open Data practices. Here, we describe common Open Data challenges faced by data users and data providers within the aquatic sciences community (i.e., oceanography, limnology, hydrology, and others). These challenges were synthesized from literature, authors’ experiences, and a broad survey of 174 data users and data providers across academia, government agencies, industry, and other sectors. Through this work, we identified seven main challenges: 1) metadata shortcomings, 2) variable data quality and reusability, 3) open data inaccessibility, 4) lack of standardization, 5) authorship and acknowledgement issues 6) lack of funding, and 7) unequal barriers around the globe. Our key recommendation is to improve resources to advance Open Data practices. This includes dedicated funds for capacity building, hiring and maintaining of skilled personnel, and robust digital infrastructures for preparation, storage, and long-term maintenance of Open Data. Further, to incentivize data sharing we reinforce the need for standardized best practices to handle data acknowledgement and citations for both data users and data providers. We also highlight and discuss regional disparities in resources and research practices within a global perspective.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Data Center Cybersecurity, Supply Chain Risk Management, and Emerging Regulation Cohort Summary: Takeaways and Action Plans

This report summarizes the outcomes of the Data Center Cohort under the Department of Energy’s Technical Assistance for Digital Assurance (TADA) initiative, aimed at enhancing grid resilience through cybersecurity, supply chain risk management (SCRM), and Cyber-Informed Engineering (CIE). The cohort engaged 17 organizations across utilities, data center operators, vendors, and technology providers in three sessions combining presentations, discussions, and exercises. Key topics included AI-driven load behavior, cybersecurity vulnerabilities in UPS/BESS and cooling systems, governance gaps at utility–data center boundaries, and supply chain integrity. Five cross-cutting themes emerged: interconnection architecture vulnerabilities, fragmented governance, AI-driven stability risks, lack of regulatory frameworks, and long-term supply chain concerns. Actionable recommendations were developed, including implementing DMZ segmentation, formalizing vendor access agreements, designing AI workload limits, and advancing standards through NERC and state-level programs. These strategies aim to strengthen resilience, clarify responsibilities, and ensure secure integration of data centers into the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1998

CGNS Mid-Level Software Library and Users Guide

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: - The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its I/O software, which handles the actual reading and writing of data from and to external storage media; - The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; - The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and - The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The CGNS Mid-level Library was designed to ease the implementation of CGNS by providing developers with a collection of handy I/O functions. Since knowledge of the ADF core is not required to use this library, it will greatly facilitate the task of interfacing with CGNS. There are currently 48 user callable functions that comprise the Mid-level library and are described in the Users Guide. The library is written in C, but each function has a FORTRAN counterpart.

Poirier, Diane↗

NASA NTRS2003

Overview of the SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division Activities and Technical Projects

The SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division activities include identification and fulfillment of joint industry, government, and academia needs for development and implementation of RMSL technologies. Four Projects in the Probabilistic Methods area and two in the area of RMSL have been identified. These are: (1) Evaluation of Probabilistic Technology - progress has been made toward the selection of probabilistic application cases. Future effort will focus on assessment of multiple probabilistic softwares in solving selected engineering problems using probabilistic methods. Relevance to Industry & Government - Case studies of typical problems encountering uncertainties, results of solutions to these problems run by different codes, and recommendations on which code is applicable for what problems; (2) Probabilistic Input Preparation - progress has been made in identifying problem cases such as those with no data, little data and sufficient data. Future effort will focus on developing guidelines for preparing input for probabilistic analysis, especially with no or little data. Relevance to Industry & Government - Too often, we get bogged down thinking we need a lot of data before we can quantify uncertainties. Not True. There are ways to do credible probabilistic analysis with little data; (3) Probabilistic Reliability - probabilistic reliability literature search has been completed along with what differentiates it from statistical reliability. Work on computation of reliability based on quantification of uncertainties in primitive variables is in progress. Relevance to Industry & Government - Correct reliability computations both at the component and system level are needed so one can design an item based on its expected usage and life span; (4) Real World Applications of Probabilistic Methods (PM) - A draft of volume 1 comprising aerospace applications has been released. Volume 2, a compilation of real world applications of probabilistic methods with essential information demonstrating application type and timehost savings by the use of probabilistic methods for generic applications is in progress. Relevance to Industry & Government - Too often, we say, 'The Proof is in the Pudding'. With help from many contributors, we hope to produce such a document. Problem is - not too many people are coming forward due to proprietary nature. So, we are asking to document only minimum information including problem description, what method used, did it result in any savings, and how much?; (5) Software Reliability - software reliability concept, program, implementation, guidelines, and standards are being documented. Relevance to Industry & Government - software reliability is a complex issue that must be understood & addressed in all facets of business in industry, government, and other institutions. We address issues, concepts, ways to implement solutions, and guidelines for maximizing software reliability; (6) Maintainability Standards - maintainability/serviceability industry standard/guidelines and industry best practices and methodologies used in performing maintainability/ serviceability tasks are being documented. Relevance to Industry & Government - Any industry or government process, project, and/or tool must be maintained and serviced to realize the life and performance it was designed for. We address issues and develop guidelines for optimum performance & life.

Singhal, Surendra N.↗

NASA NTRS2002

SIDS-toADF File Mapping Manual

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: 1) The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its I/O software, which handles the actual reading and writing of data from and to external storage media; 2) The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; 3) The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and 4) The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The SIDS-toADF File Mapping Manual specifies the exact manner in which, under CGNS conventions, CFD data structures (the SIDS) are to be stored in (i.e., mapped onto) the file structure provided by the database manager (ADF). The result is a conforming CGNS database. Adherence to the mapping conventions guarantees uniform meaning and location of CFD data within ADF files, and thereby allows the construction of universal software to read and write the data.

McCarthy, Douglas↗

NASA NTRS1998

Advanced Data Format (ADF) Software Library and Users Guide

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial. Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: 1) The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its 1/0 software, which handles the actual reading and writing of data from and to external storage media; 2) The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; 3) The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and 4) The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The ADF is a generic database manager with minimal intrinsic capability. It was written for the purpose of storing large numerical datasets in an efficient, platform independent manner. To be effective, it must be used in conjunction with external agreements on how the data will be organized within the ADF database such defined by the SIDS. There are currently 34 user callable functions that comprise the ADF Core library and are described in the Users Guide. The library is written in C, but each function has a FORTRAN counterpart.

Smith, Matthew↗

DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2008

Metrology - Beyond the Calibration Lab

We rely on data from measurements every day; a gas-pump, a speedometer, and a supermarket weight scale are just three examples of measurements we use to make decisions. We generally accept the data from these measurements as "valid." One reason we can accept the data is the "legal metrology" requirements established and regulated by the government in matters of commerce. The measurement data used by NASA, other government agencies, and industry can be critical to decisions which affect everything from economic viability, to mission success, to the security of the nation. Measurement data can even affect life and death decisions. Metrology requirements must adequately provide for risks associated with these decisions. To do this, metrology must be integrated into all aspects of an industry including research, design, testing, and product acceptance. Metrology, the science of measurement, has traditionally focused on the calibration of instruments, and although instrument calibration is vital, it is only a part of the process that assures quality in measurement data. For example, measurements made in research can influence the fundamental premises that establish the design parameters, which then flow down to the manufacturing processes, and eventually impact the final product. Because a breakdown can occur anywhere within this cycle, measurement quality assurance has to be integrated into every part of the life-cycle process starting with the basic research and ending with the final product inspection process. The purpose of this paper is to discuss the role of metrology in the various phases of a product's life-cycle. For simplicity, the cycle will be divided in four broad phases, with discussions centering on metrology within NASA. .

Mimbs, Scott M.↗

NASA NTRS2003

Comparison of Flow-Dependent and Static Error Correlation Models in the DAO Ozone Data Assimilation System

In a data assimilation system the forecast error covariance matrix governs the way in which the data information is spread throughout the model grid. Implementation of a correct method of assigning covariances is expected to have an impact on the analysis results. The simplest models assume that correlations are constant in time and isotropic or nearly isotropic. In such models the analysis depends on the dynamics only through assumed error standard deviations. In applications to atmospheric tracer data assimilation this may lead to inaccuracies, especially in regions with strong wind shears or high gradient of potential vorticity, as well as in areas where no data are available. In order to overcome this problem we have developed a flow-dependent covariance model that is based on short term evolution of error correlations. The presentation compares performance of a static and a flow-dependent model applied to a global three- dimensional ozone data assimilation system developed at NASA s Data Assimilation Office. We will present some results of validation against WMO balloon-borne sondes and the Polar Ozone and Aerosol Measurement (POAM) III instrument. Experiments show that allowing forecast error correlations to evolve with the flow results in positive impact on assimilated ozone within the regions where data were not assimilated, particularly at high latitudes in both hemispheres and in the troposphere. We will also discuss statistical characteristics of both models; in particular we will argue that including evolution of error correlations leads to stronger internal consistency of a data assimilation ,

Wargan, K.↗

NASA NTRS2004

The LATEST Project: Operational Assessment of Total Lightning Data in the U.S.

A government, university, and industry alliance has joined forces to transition total lightning observations from ground-based research networks and NASA satellites (LIS/TRMM) to improve the short range prediction of severe weather. This interest builds on the desire of the U.S Weather Research Program to foster a national Nowcasting Test Bed, with this specific transition activity initiated through the NASA short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL. A kick-off national workshop sponsored by the SPoRT Center was held in Huntsville April 1-2 to identify the common goals and objectives of the research and operational community, and to assign roles and responsibilities within the alliance. The workshop agenda, presentations, and summary are available at the SPoRT Center Web site ( h h under the "Meetings" tab. The next national workshop is planned for 2005 in Dallas, TX. The NASA North Alabama regional Lightning Mapping Array &MA) has been operational in the Huntsville area for 3 years, and has continuously sampled a variety of severe weather systems during that period. A gridded version of the LMA total lightning data is currently being supplied to National Weather Service offices in Huntsville, Nashville and Birmingham through the NWS AWES decision support system, for the purposes of assessing the utility of the data in the nowcasting of severe weather such as tornadoes, damaging straight line winds, flash flooding and other weather hazards (lightning induced forest fires, microbursts). While the raw LMA data have been useful to NWS forecasters, even greater utility would be realized if higher-order data products could be supplied through AWIPS along with the gridded data over a larger domain. In 2003-2004 additional LMA systems have been deployed across the southern US. from Florida to New Mexico, providing an opportunity for more than 20 NWS forecast offices to evaluate the incremental value of total lightning data in the warning decision making process.

Goodman, Steven↗

NASA NTRS2019

JPSS-2 VIIRS Version 1 spectral characterization and performance assessment

The JPSS-2 VIIRS instrument is set to be the third VIIRS instrument when it launches in 2022 following S-NPP and NOAA-20 VIIRS which launched in October 2011and November 2017, respectively. To date JPSS-2 VIIRS has undergone extensive pre-launch testing at the instrument system level to determine the radiometric, spatial, and spectral performance. Spectral testing was conducted by the instrument vendor, Raytheon Corporation, at their test facility in mid-to-late 2017 with a test configuration that utilized a double monochrometer with illumination provided by tungsten lamp and ceramic glow bar to cover the full spectral range. The purpose of these measurements was to measure the relative spectral response curve and assess the spectral characteristics necessary to determine compliance with the sensor design requirements. In addition to Raytheon team, the spectral measurements were analyzed by an independent government team with members from NASA, the University of Wisconsin, and Aerospace Corporation. Two RSR curves were released by the government team from this data set: a version 0 release which was the verified RSR as calculated by Raytheon, and version 1 which was the RSR assessment from the government team. The results discussed here are those of the government team (version 1) including the independent assessment of sensor compliance and a comparison of the JPSS-2 VIIRS spectral characteristics with the two previous VIIRS instruments. The version 1 RSR was publicly released to the science community in the fall of 2018, and remains available for their use.

VIIRS↗

NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗

NASA NTRS2011

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗

NASA NTRS1980

Government financial support for civil aircraft research, technology and development in four European countries and the United States

Data on the levels of government financial support for civil aircraft airframe and engine (CAAE) research and technology (R&T) in the United States and Europe (United Kingdom, West Germany, France and The Netherlands) and means of comparing these levels are provided. Data are presented for the years 1974-1977. European R&T expenditure data were obtained through visits to each of the four European countries, to the Washington office of the European Communities, and by a search of applicable literature. CAAE R&T expenditure data for the United States were obtained from NASA and Federal Aviation Administration (FAA).

Chandler, B.↗

DOE OSTI2025

Specifications of Legacy U(Pu)Zr Metallography Data

The DOE Nuclear Energy Advanced Reactor Technologies (ART) Program has supported the creation of several databases with information describing the safety performance of fast reactors, components, and fuels. This growing collection of legacy experimental data, operating data, and analysis is available online to registered users. Metallography data is one of the most important types of PIE data being collected, organized and stored in several ART Fast Reactor Databases (https://frdb.ne.anl.gov), including the Fuels Irradiation & Physics Database (FIPD), Out-of-Pile Transient Database (OPTD), and TREAT (the Transient Reactor Test Facility) Experimental Relational Database (TREXR). These databases contain three main sets of metallography data. The first set is the metallography data from Experimental Breeder Reactor-II (EBR-II) and Fast Flux Test Facility (FFTF) irradiated fuel pins measured in the Hot Fuel Examination Facility (HFEF); the second set is the metallography data from EBR-II irradiated fuel pins measured in the Alpha-Gamma Hot Cell Facility (AGHCF); the third set is the metallography data from transient tested fuel pins (the transients tests include the out-of-pile tests and TREAT tests) measured in AGHCF. Since both the second and third sets of data were measured in AGHCF, they are governed by the same specification. The metallography data in the databases are digital images scanned from either positive or negative photos. The quality of the images, including their resolution and contrast, relies on the preserved quality of the pictures and the scanning conditions. To analyze the microstructure of a fuel pin, a series of preparatory steps must be undertaken. These include sectioning, epoxy mounting, mechanical grinding and polishing, and often etching. The resulting samples were then transferred to a secondary hot cell, or glovebox (depending the strength of radiation field) for microscopy examination. The specifications provided herein focus on the metallography examinations. The sample grinding, polishing and etching processes are also discussed. The procedures involving sectioning and epoxy mounting are out of the scope of the current specification; details can be found in the corresponding operation manuals. If more data are collected and added to the ART Fast Reactor Databases, this specification will be updated to accommodate the additional data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1997

Land-use in Amazonia and the Cerrado of Brazil: State of Knowledge and GIS Database

We have assembled datasets to strengthen the LargeScale Biosphere Atmosphere Experiment in Amazonia (LBA). These datasets can now be accessed through the Woods Hole Research Center homepage (www.whrc.org), and will soon be linked to the Pre-LBA homepages of the Brazilian Space Research Institute's Center for Weather and Climate Prediction (Instituto de Pesquisas Espaciais, Centro de Previsao de Tempo e Estudos Climaticos, INPE/CPTEC) and through the Oak Ridge National Laboratory, Distributed Active Archive Center (ORNL/DMC). Some of the datasets that we are making available involved new field research and/or the digitization of data available in Brazilian government agencies. For example, during the grant period we conducted interviews at 1,100 sawmills across Amazonia to determine their production of sawn timber, and their harvest intensities. These data provide the basis for the first quantitative assessment of the area of forest affected each year by selective logging (Nepstad et al, submitted to Nature). We digitized the locations of all of the rural households in the State of Para that have been mapped by the Brazilian malaria combat agency (SUCAM). We also mapped and digitized areas of deforestation in the state of Tocantins, which is comprised largely of savanna (cerrado), an ecosystem that has been routinely excluded from deforestation mapping exercises.

Nepstad, Daniel C.↗

NASA NTRS2011

Policies and Procedures for Accessing Archived NASA Lunar Data via the Web

The National Space Science Data Center (NSSDC) was established by NASA to provide for the preservation and dissemination of scientific data from NASA missions. This paper describes the policies specifically related to lunar science data. NSSDC presently archives 660 lunar data collections. Most of these data (423 units) are stored offline in analog format. The remainder of this collection consists of magnetic tapes and discs containing approximately 1.7 TB of digital lunar data. The active archive for NASA lunar data is the Planetary Data System (PDS). NSSDC has an agreement with the PDS Lunar Data Node to assist in the restoration and preparation of NSSDC-resident lunar data upon request for access and distribution via the PDS archival system. Though much of NSSDC's digital store also resides in PDS, NSSDC has many analog data collections and some digital lunar data sets that are not in PDS. NSSDC stands ready to make these archived lunar data accessible to both the research community and the general public upon request as resources allow. Newly requested offline lunar data are digitized and moved to near-line storage devices called digital linear tape jukeboxes. The data are then packaged and made network-accessible via FTP for the convenience of a growing segment of the user community. This publication will 1) discuss the NSSDC processes and policies that govern how NASA lunar data is preserved, restored, and made accessible via the web and 2) highlight examples of special lunar data requests.

James, Nathan L.↗

DOE OSTI2025

Hanford Site Freshwater Mussel Monitoring Report for Calendar Year 2024

The U.S. Department of Energy, Hanford Field Office (HFO) conducts ecological monitoring at the Hanford Site to collect and maintain data to ensure compliance with an array of environmental laws, regulations, and policies governing HFO activities. Ecological monitoring data provides baseline information about the plants, animals, and habitats under HFO stewardship at the Hanford Site that is required for decision making under the National Environmental Policy Act of 1969 and the Comprehensive Environmental Response, Compensation, and Liability Act of 1980. In addition, ecological monitoring helps ensure that HFO, its contractors, and other entities conducting activities at the Hanford Site are in compliance with DOE/EIS-0222-F, Final Hanford Comprehensive Land-Use Plan Environmental Impact Statement. HFO places priority on monitoring those plant and animal species or habitats with specific regulatory protections or requirements that are rare and/or declining (i.e., federal or state listed endangered, threatened, or sensitive species) or are of significant interest to federal, state, or tribal governments or the public.

54 ENVIRONMENTAL SCIENCES↗