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USGS2016

Dynamic reusable workflows for ocean science

Digital catalogs of ocean data have been available for decades, but advances in standardized services and software for catalog search and data access make it now possible to create catalog-driven workflows that automate — end-to-end — data search, analysis and visualization of data from multiple distributed sources. Further, these workflows may be shared, reused and adapted with ease. Here we describe a workflow developed within the US Integrated Ocean Observing System (IOOS) which automates the skill-assessment of water temperature forecasts from multiple ocean forecast models, allowing improved forecast products to be delivered for an open water swim event. A series of Jupyter Notebooks are used to capture and document the end-to-end workflow using a collection of Python tools that facilitate working with standardized catalog and data services. The workflow first searches a catalog of metadata using the Open Geospatial Consortium (OGC) Catalog Service for the Web (CSW), then accesses data service endpoints found in the metadata records using the OGC Sensor Observation Service (SOS) for in situ sensor data and OPeNDAP services for remotely-sensed and model data. Skill metrics are computed and time series comparisons of forecast model and observed data are displayed interactively, leveraging the capabilities of modern web browsers. The resulting workflow not only solves a challenging specific problem, but highlights the benefits of dynamic, reusable workflows in general. These workflows adapt as new data enters the data system, facilitate reproducible science, provide templates from which new scientific workflows can be developed, and encourage data providers to use standardized services. As applied to the ocean swim event, the workflow exposed problems with two of the ocean forecast products which led to improved regional forecasts once errors were corrected. While the example is specific, the approach is general, and we hope to see increased use of dynamic notebooks across the geoscience domains.

Journal of Marine Science and Engineering↗

USGS1991

Magellan: Radar performance and data products

The Magellan Venus orbiter carries only one scientific instrument: a 12.6-centimeter wavelength radar system shared among three data-taking modes. The synthetic-aperture mode images radar echoes from the Venus surface at a resolution of between 120 and 300 meters, depending on spacecraft altitude. In the altimetric mode, relative height measurement accuracies may approach 5 meters, depending on the terrain's roughness, although orbital uncertainties place a floor of about 50 meters on the absolute uncertainty. In areas of extremely rough topography, accuracy is limited by the inherent line-of-sight radar resolution of about 88 meters. The maximum elevation observed to date, corresponding to a planetary radius of 6062 kilometers, lies within Maxwell Mons. When used as a thermal emission radiometer, the system can determine surface emissivities to an absolute accuracy of about 0.02. Mosaicked and archival digital data products will be released in compact disk (CDROM) format.

Science↗

USGS2002

Using Christmas Bird Count data in analysis of population change

The scientific credibility of Christmas Bird Count (CBC) results depend on the development and implementation of appropriate methods of statistical analysis. The key to any successful analysis of CBC data is to begin with a careful review of how the limitations of the data are likely to influence the results of the analysis, then to choose methods of analysis that accommodate as much as possible the limitations of the survey. For our analyses of CBC data, we develop a flexible model for effort adjustment and use information from the data to guide the selection of the best model. We include geographic structuring to accommodate the regional variation in number of samples, use a model that allows for overdispersed poisson data appropriate for counts, and employ empirical Bayes procedures to accommodate differences in quality of information in regional summaries. This generalized linear model approach is very flexible, and can be applied to a variety of studies focused on factors influencing wintering bird populations. In particular, the model can be easily modified to contain covariates, allowing for assessment of associations between CBC counts and winter weather, disturbance, and a variety of other environmental factors. These new survey analysis methods have added value in that they provide insights into changes in survey design that can enhance the value of the information. The CBC has been extremely successful as a tool for increasing public interest in birding and bird conservation. Use of the information for bird conservation creates new demands on quality of information, and it is important to maintain a dialogue between users of the information, information needs for the analyses, and survey coordinators and participants. Our work as survey analysts emphasizes the value and limitations of existing data, and provides some indications of what features of the survey could be modified to make the survey a more reliable source of bird population data. Surveys only remain useful if they adapt to current needs, while still maintaining consistency with historical goals.

American Birds↗

USGS2025

A metadata checklist and data formatting guidelines to make eDNA FAIR (Findable, Accessible, Interoperable and Reusable)

The success of environmental DNA (eDNA) approaches for species detection has revolutionized biodiversity monitoring and distribution mapping. Targeted eDNA amplification approaches, such as quantitative PCR, have improved our understanding of species distribution, and metabarcoding-based approaches have enabled biodiversity assessment at unprecedented scales and taxonomic resolution. eDNA datasets, however, are often scattered across repositories with inconsistent formats, varying access restrictions, and inadequate metadata; this limits their interoperation, reuse, and overall impact. Adopting FAIR (Findable, Accessible, Interoperable, and Reusable) data practices with eDNA data can transform the monitoring of biodiversity and individual species and support data-driven biodiversity management across broad scales. FAIR practices remain underdeveloped in the eDNA community, partly due to gaps in adapting existing vocabularies, such as Darwin Core (DwC) and Minimum Information about any (x) Sequence (MIxS), to eDNA-specific needs and workflows. To address these challenges, we propose a comprehensive FAIR eDNA (FAIRe) Metadata Checklist, which integrates existing data standards and introduces new terms tailored to eDNA workflows. Metadata are systematically linked to both raw data (e.g., metabarcoding sequences, Ct/Cq values of targeted qPCR assays) and derived biological observations (e.g., Amplicon Sequence Variant (ASV)/Operational Taxonomic Unit (OTU) tables, species presence/absence). Along with formatting guidelines, tools, templates, and example datasets, we introduce a standardized, ready-to-use approach for FAIR eDNA practices. Through broad collaboration, we seek to integrate these guidelines into established biodiversity and molecular data standards, promote journal data policies, and foster user-driven improvements and uptake of FAIR practices among eDNA data producers. In proposing this standardized approach and developing a long-term plan with key databases and data standard organizations, the goal is to enhance accessibility, maximize reuse, and elevate the scientific impact of these valuable biodiversity data resources.

Environmental DNA↗

USGS2024

Coastal Science Navigator companion guide—Discover the U.S. Geological Survey coastal science products you need

The Coastal Science Navigator is an online gateway to a wide variety of U.S. Geological Survey (USGS) coastal change hazards-related information, data, and tools relevant to stakeholders’ scientific and decision-making needs. The products within the Coastal Science Navigator provide data related to past, present, and future threats to our coastlines. The filter search allows users to see all available products and identify relevant options by time scale, geographic scope, coastal hazard theme, and other filters. The guided search suggests products based on users’ answers to a short series of questions. A comprehensive summary is available for each product. The idea for the Coastal Science Navigator arose in 2020 in response to stakeholder feedback identifying the need for a central source for USGS coastal science information. It was published in July 2023 and initially included 55 products. Regular updates are planned to integrate other existing and new products. This guide introduces some of the many coastal change hazards-related products available through the USGS. In it, we showcase the products included in the Coastal Science Navigator’s initial publication in July 2023. While it is not representative of all the information, tools, and data available, we hope it serves as a compelling snapshot of what the USGS has to offer and encourages you to explore the Coastal Science Navigator to discover more of the products you need. To navigate this guide, the products have been organized by the time scale they are best suited for—past, present, or future—although many products cover multiple time scales. An additional section features software, one of the many product types available as filters within the Coastal Science Navigator. Other products include downloadable data, websites, and geonarratives (web pages that combine text, images, and interactive maps into narratives you can scroll through). Featured geographic scopes are also highlighted within this guide, detailing some of the many regions in which the USGS conducts research and illustrating another way to filter products within the Coastal Science Navigator.

Circular↗

USGS2024

Best practices for genetic and genomic data archiving

Genetic and genomic data are collected for a vast array of scientific and applied purposes. Despite mandates for public archiving, data are typically used only by the generating authors. The reuse of genetic and genomic datasets remains uncommon because it is difficult, if not impossible, due to non-standard archiving practices and lack of contextual metadata. But as the new field of macrogenetics is demonstrating, if genetic data and their metadata were more accessible and FAIR (findable, accessible, interoperable and reusable) compliant, they could be reused for many additional purposes. We discuss the main challenges with existing genetic and genomic data archives, and suggest best practices for archiving genetic and genomic data. Recognizing that this is a longstanding issue due to little formal data management training within the fields of ecology and evolution, we highlight steps that research institutions and publishers could take to improve data archiving.

Nature, Ecology and Evolution↗

USGS2021

A preliminary regional geomorphologic map in Utopia Planitia of the Tianwen-1 Zhurong Landing Region

A geomorphologic map is an important step to understanding the geologic context and history of a site; here, we present an initial geomorphologic map for an area spanning 22°–26°N, 108°–112°E in the Utopia Planitia (UP) region on Mars. This site is of special interest because it contains the May 2021 landing site of the Zhurong rover from Tianwen-1. Utopia Planitia exhibits many lobate features that have been proposed to be lava or mud flows. Lander and rover data should help solve the scientific question concerning the origin of UP flows. We use our map to generate an initial stratigraphic framework of geomorphological features in order to help place future Zhurong data into the regional geologic context. Our mapping effort has detailed the distribution of three geomorphologic units and 11 types of surface features.

Geophysical Research Letters↗

USGS2015

Developing a workflow to identify inconsistencies in volunteered geographic information: a phenological case study

Recent improvements in online information communication and mobile location-aware technologies have led to the production of large volumes of volunteered geographic information. Widespread, large-scale efforts by volunteers to collect data can inform and drive scientific advances in diverse fields, including ecology and climatology. Traditional workflows to check the quality of such volunteered information can be costly and time consuming as they heavily rely on human interventions. However, identifying factors that can influence data quality, such as inconsistency, is crucial when these data are used in modeling and decision-making frameworks. Recently developed workflows use simple statistical approaches that assume that the majority of the information is consistent. However, this assumption is not generalizable, and ignores underlying geographic and environmental contextual variability that may explain apparent inconsistencies. Here we describe an automated workflow to check inconsistency based on the availability of contextual environmental information for sampling locations. The workflow consists of three steps: (1) dimensionality reduction to facilitate further analysis and interpretation of results, (2) model-based clustering to group observations according to their contextual conditions, and (3) identification of inconsistent observations within each cluster. The workflow was applied to volunteered observations of flowering in common and cloned lilac plants ( Syringa vulgaris and Syringa x chinensis ) in the United States for the period 1980 to 2013. About 97% of the observations for both common and cloned lilacs were flagged as consistent, indicating that volunteers provided reliable information for this case study. Relative to the original dataset, the exclusion of inconsistent observations changed the apparent rate of change in lilac bloom dates by two days per decade, indicating the importance of inconsistency checking as a key step in data quality assessment for volunteered geographic information. Initiatives that leverage volunteered geographic information can adapt this workflow to improve the quality of their datasets and the robustness of their scientific analyses.

PLoS ONE↗

USGS2024

Are researchers citing their data? A case study from the U.S. Geological Survey

Data citation promotes accessibility and discoverability of data through measures carried out by researchers, publishers, repositories, and the scientific community. This paper examines how a data citation workflow has been implemented by the U.S. Geological Survey (USGS) by evaluating publication and data linkages. Two different methods were used to identify data citations: examining publication structural metadata and examining the full text of the publication. A growing number of USGS researchers are complying with publisher data sharing policies aimed to capture data citation information in a standardized way within associated publications. However, inconsistencies in how data citation information is documented in publications has limited the accessibility and discoverability of the data. This paper demonstrates how organizational evaluations of publication and data linkages can be used to identify obstacles in advancing data citation efforts and improve data citation workflows.

Data Science Journal↗

USGS2022

Fifty years of Landsat science and impacts

Since 1972, the Landsat program has been continually monitoring the Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, Landsat data were crucial for many scientific and technical advances. Prior to the Landsat program, detailed, synoptic depictions of the Earth's surface were rare, and the ability to acquire and work with large datasets was limited. The early years of the Landsat program delivered a series of technological breakthroughs, pioneering new methods, and demonstrating the ability and capacity of digital satellite imagery, creating a template for other global Earth observation missions and programs. Innovations driven by the Landsat program have paved the way for subsequent science, application, and policy support activities. The economic and scientific value of the knowledge gained through the Landsat program has been long recognized, and despite periods of funding uncertainty, has resulted in the program's 50 years of continuity, as well as substantive and ongoing improvements to payload and mission performance. Free and open access to Landsat data, enacted in 2008, was unprecedented for medium spatial resolution Earth observation data and substantially increased usage and led to a proliferation of science and application opportunities. Here, we highlight key developments over the past 50 years of the Landsat program that have influenced and changed our scientific understanding of the Earth system. Major scientific and programmatic impacts have been realized in the areas of agricultural crop mapping and water use, climate change drivers and impacts, ecosystems and land cover monitoring, and mapping the changing human footprint. The introduction of Landsat collection processing, coupled with the free and open data policy, facilitated a transition in Landsat data usage away from single images and towards time series analyses over large areas and has fostered the widespread use of science-grade data. The launch of Landsat-9 on September 27, 2021, and the advanced planning of its successor mission, Landsat-Next, underscore the sustained institutional support for the program. Such support and commitment to continuity is recognition of both the historic impact the program, and the future potential to build upon Landsat's remarkable 50-year legacy.

Remote Sensing of Environment↗

USGS1983

The international phosphate resource data base; development and maintenance

The IPRDB (International Phosphate Resource Data Base) was developed to provide a single computerized source of geologic information about phosphate deposits worldwide. It is expected that this data base will encourage more thorough scientific analyses of phosphate deposits and assessments of undiscovered phosphate resources, and that methods of data collection and storage will be streamlined. Because the database was intended to serve as a repository for diverse and detailed data, a large amount of the early research effort was devoted to the design and development of the system. To date (1982), the file remains incomplete. All development work and file maintenance work on IPRDB was suspended as of October 1, 1982; this paper is intended to document the steps taken up to that date. The computer programs listed in the appendices were written specifically for the IPRDB phosbib file and are of limited future use.

Open-File Report↗

USGS2003

Irrigation-induced contamination of water, sediment, and biota in the western United States-synthesis of data from the National Irrigation Water Quality Program

In October 1985 the U.S. Department of the Interior (DOI), through the National Irrigation Water Quality Program (NIWQP), began a series of field investigations at 26 areas in the Western United States to determine whether irrigation drainage has had harmful effects on fish, wildlife, and humans or has reduced beneficial uses of water. In 1992 NIWQP initiated the Data Synthesis Project to evaluate data collected during the field investigations. Geologic, climatologic, and hydrologic data were evaluated and water, sediment, and biota from the 26 areas were analyzed to identify commonalities and dominant factors that result in irrigation-induced contamination of water and biota. Data collected for the 26 area investigations have been compiled and merged into a common data base. The structure of the data base is designed to enable assessment of relations between contaminant concentrations in water, sediment, and biota. The data base is available to the scientific community through the World Wide Web at URL http://www.usbr.gov/niwqp. Analysis of the data base for the Data Synthesis included use of summary statistics, factor analysis, and logistic regression. A Geographic Information System was used to store and analyze spatially oriented digital data such as land use, geology and evaporation rates. In the U.S. Department of the Interior (DOI) study areas, samples of water, bottom sediment, and biota were collected for trace-element and pesticide analysis. Contaminants most commonly associated with irrigation drainage were identified by comparing concentrations in water with established criteria. For surface water, the criteria used were typically chronic criteria for the protection of freshwater aquatic life. Because ground water can discharge to the surface where wildlife can be exposed to it, the criteria used for ground water were both the maximum contaminant levels (MCL's) for drinking water and the chronic criteria for the protection of freshwater aquatic life. Data collected by the NIWQP studies indicated that, in surface water, filtered and unfiltered samples had nearly the same concentrations of arsenic, boron, molybdenum, and selenium for concentrations greater than about 10 micrograms per liter. Therefore, in this concentration range, filtered concentrations can be directly compared to biological-effect levels developed for unfiltered samples. In the range of 1 to 10 micrograms per liter there may be a tendency for unfiltered arsenic concentrations to be greater than filtered concentrations. For selenium, however, the data suggest differences from equality in that range result from analytical imprecision and not a general tendency for unfiltered concentrations to be greater than filtered concentrations. This relation may not be true in lentic, nutrient-rich waters because in such settings algae can bioaccumulate large amounts of selenium and other trace elements. Selenium was the trace element in surface water that most commonly exceeded chronic criteria for the protection of freshwater aquatic life; more than 40 percent of the selenium concentrations in surface-water samples exceeded the U.S. Environmental Protection Agency (USEPA) aquatic-life chronic criterion (5 micrograms per liter). In 12 of the 26 areas at least 25 percent of the surface water-samples had selenium concentrations that either equaled or exceeded the chronic criterion (5 micrograms per liter). More than 28 percent of boron concentrations and almost 17 percent of the molybdenum concentrations exceeded the aquatic life criteria established by the State of California (550 and 19 micrograms per liter, respectively). In ground water, more than 22 percent of the arsenic concentrations and more than 35 percent of the selenium concentrations exceeded the MCL (10 and 50 micrograms per liter, respectively). Few samples of uranium in surface water exceeded a criterion for the protection of aquatic life (300 micrograms per liter), but 44 percent

Professional Paper↗

USGS2021

USGS permafrost research determines the risks of permafrost thaw to biologic and hydrologic resources

The U.S. Geological Survey (USGS), in collaboration with university, Federal, Tribal, and independent partners, conducts fundamental research on the distribution, vulnerability, and importance of permafrost in arctic and boreal ecosystems. Scientists, land managers, and policy makers use USGS data to help make decisions for development, wildlife habitat, and other needs. Native villages and cities can forecast landscape change and where soils are vulnerable to thaw with more certainty. The scientific community can use USGS data to develop scenarios of future permafrost change.

Alaska↗

USGS2025

Planting seeds for thriving data management

The volumes and varieties of data coming from all types of scientific instrumentation around the globe and beyond are rapidly growing. To reuse and capitalize on these data effectively, scientists must be able to share and access them efficiently, which requires the data to be well managed. Many scientists intuit that research data management (RDM) done well does not mean using dusty USB drives or aging laptops for storage. Yet the path to strong data management is not always clear. How is RDM done? Who does it? For science to advance, we need to bolster cyberinfrastructure and human capacity to ensure that the data being collected are reusable by both humans and machines.

Eos, American Geophysical Union↗

USGS2022

Landsat data ecosystem case study: Actor perceptions of the use and value of landsat

It is well-known that Earth observation (EO) data plays a critical role in scientific understanding about the global environment. There is also growing support for the use of EO data to provide context-specific insights, with significant implications for their use in decision support systems. Technological development over recent years, including cloud computing infrastructure, machine learning techniques, and rapid expansion of the velocity, volume, and variety of space-borne data sources, offer huge potential to provide solutions to the myriad environmental problems facing society and the planet. The USGS/NASA Landsat Program, the longest continuously gathered source of land surface data, has played a central role in our understanding of environmental change, particularly for its contribution of longitudinal products that offer greater context for present research and decision support activities. The challenge facing the Landsat and EO data community, however, now lies in moving beyond context-specific knowledge generation to translating such knowledge into tangible value for society. Drawing from an open data ecosystem framework and qualitative social science methods, we map the Landsat data ecosystem (LDE) and the relationships linking multiple actors responsible for processing, indexing, analyzing, synthesizing, and translating raw Landsat data into information that is useful, useable, and used by end users in particular social-environmental contexts. Both the role of Big Data and associated technologies are discussed as they relate to the ultimate use of Landsat-derived information products to guide decision-making, and key data ecosystem characteristics that shape the likelihood of these products’ use are highlighted.

Frontiers in Environmental Science↗

USGS2019

Scientific integrity issues in environmental toxicology and chemistry: Improving research transparency, reproducibility, and credibility

High‐profile reports of detrimental scientific practices leading to retractions in the scientific literature contribute to lack of trust in scientific experts. Although the bulk of these have been in the literature of other disciplines, environmental toxicology and chemistry are not free from problems. While we believe that egregious misconduct such as fraud, fabrication of data, or plagiarism is rare, scientific integrity is much broader than the absence of misconduct. We are more concerned with more commonly encountered and nuanced issues such as poor reliability and bias. We review a range of topics including conflicts of interests, competing interests, some particularly challenging situations, reproducibility, bias, and other attributes of ecotoxicological studies that enhance or detract from scientific credibility. Our vision of scientific integrity encourages a self‐correcting culture that promotes scientific rigor, relevant reproducible research, transparency in competing interests, methods and results, and education.

Integrated Environmental Assessment and Management↗

USGS2016

Scripting MODFLOW model development using Python and FloPy

Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy.

Groundwater↗

USGS2022

Science mission requirements for a globally ranging, riserless drilling vessel for U.S. Scientific Ocean Drilling

Through the collection and analysis of shallow and deep subseafloor sediments, rocks, fluids, and life, scientific ocean drilling has enriched our understanding of the complex Earth system. Among other achievements, scientific ocean drilling has documented the history of Earth’s climate, the waxing and waning of polar ice sheets, the past changes in ocean and atmospheric circulation, the existence and function of microbial life in the subseafloor, the compositional variations in Earth’s crust and underlying mantle, and the physical and chemical processes acting at subduction zones, including those associated with tsunamigenic earthquakes. Over the decades, more than 12,000 articles that depend on analyses of scientific ocean drilling samples and geophysical data have been published, many detailing breakthrough contributions to global knowledge about the Earth system. Approximately 45% of these publications were led by U.S.-affiliated authors (International Ocean Discovery Program Publication Services, 2021). Since the mid-1980s, the workhorse of this multidisciplinary, international research effort has been the riserless D/V JOIDES Resolution, operated by Texas A&M University with funding from the U.S. National Science Foundation (NSF). D/V JOIDES Resolution has conducted the vast majority of scientific ocean drilling expeditions and collected most of the scientific cores over that period, including 82% of the expeditions and 93% of the cores in the last decade alone, despite being one of three platforms that is operated within the International Ocean Discovery Program. However, D/V JOIDES Resolution is approaching the end of its useful life. With a strong commitment to continue scientific ocean drilling beyond the end of the current phase, the community developed a document outlining the research frontiers that should be pursued. Exploring Earth by Scientific Ocean Drilling: 2050 Science Framework (Koppers and Coggon, 2020) describes seven scientific strategic objectives that focus on understanding interconnections within the Earth system and five flagship initiatives that integrate these objectives into long-term research efforts that address issues facing society. Additional elements in the 2050 Science Framework, including STEM education, workforce development, technology development, and innovative applications of data analytics, will advance the goals of scientific ocean drilling. Addressing the 2050 Science Framework also requires building partnerships with allied U.S. and international science programs and strengthening existing ones. To implement a significant portion of the 2050 Science Framework, the U.S. scientific community seeks to lease or acquire a newly built, globally ranging, state-of-the art, riserless drilling vessel. The many and varied technical and human resources requirements for successful accomplishment of scientific and educational goals summarized in this document and described in detail in the 2050 Science Framework require broad community input and careful consideration. Following receipt of NSF’s formal Request for Assistance to the United States Science Support Program (USSSP), the U.S. scientific ocean drilling community conducted a one-year exercise to identify its national scientific needs and priorities in order to determine the Science Mission Requirements (SMRs) presented here. This community effort included: (1) a U.S. community-wide survey to identify the specific operational and technical capabilities critical to addressing science in the 2050 Science Framework; (2) a series of online workshops focusing on critical capabilities identified by the survey; and (3) a large in-person workshop to synthesize the results of the survey and the virtual workshops (Appendix 1). The approach was designed to reach as many participants as possible. Overall, 278 survey responses were received from U.S. community members, representing 104 unique institutions from 39 states and the District of Columbia, and 137 unique individuals participated in the workshops (Appendix 2). The results of this effort comprise two classes of SMRs: Foundational Science Mission Requirements and Primary Science Mission Requirements. Foundational SMRs define minimum criteria for a new riserless drilling vessel that can address significant portions of the 2050 Science Framework. Primary SMRs build upon the Foundational SMRs and will create more robust science opportunities and data collection capabilities, will increase progress in addressing the 2050 Science Framework objectives, and will provide more real-time ship-to-shore interaction to improve science productivity, engagement, and outreach. Modern safety and environmental standards, including meeting standards to access protected waters such as exclusive economic zones, extended continental shelves, or high latitudes, while being cognizant of the vessel’s environmental footprint. Safe and efficient operations in global locations and in water depths from 70 m to 6000+ m, with total drill string length of at least 7000 m. High-quality core and data collection from a range of key subseafloor environments. Advanced heave compensation, dynamic positioning, and drill pipe stability. Modern mud and cement/casing systems. Critical onboard measurements for safety, operational decision-making, documentation of ephemeral properties, mission-specific science, and long-term science goals that extend beyond a single expedition. Designated and appropriate space for sample and data preservation. Highly skilled onboard personnel, including technical staff for curation and core handling; support for safety, time-sensitive, and critical shipboard measurements; computer support; equipment and instrument repair; application support; and data assurance. Primary Science Mission Requirements include: Flexible shipboard space for laboratories and on deck to ensure safe, successful implementation of diverse science objectives and operations. Minimizing contamination of recovered samples. Over-the-side capabilities for science-supporting technology (e.g., remotely operated vehicles, water- column sampling, sediment-water interface sampling). Downhole logging and measurements. Expanded borehole observatory capabilities. Reliable and consistent ship-to-shore communications. NSF’s investment in a new globally ranging, riserless drilling vessel will have a powerful economic multiplier effect, including the infusion of additional science support funds in the United States for training and research, the development of new technologies and tools, and the associated scientific and technical workforce development. The skills and knowledge gained through scientific ocean drilling are translatable to careers in fields such as sustainable energy development (e.g., geothermal and offshore wind), carbon sequestration, data management and cyberinfrastructure, biotechnology, communications, science education, policy, hazard mitigation, and environmental management. The United States is a leader in a well-established and internationally collaborative scientific ocean drilling community. A modern, globally ranging, riserless drilling vessel will allow the United States to expand its leadership position, address broad scientific questions that current capabilities preclude, and cultivate equitable international, multidisciplinary collaborations that will ensure scientific ocean drilling’s future success.

Report↗