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At least 235 records · Page 13Linked to original sources

Post-disaster supply chain interdependent critical infrastructure system restoration: A review of data necessary and available for modeling

The majority of restoration strategies in the wake of large-scale disasters have focused on short-term emergency response solutions. Few consider medium- to long-term restoration strategies to reconnect urban areas to national supply chain interdependent critical infrastructure systems (SCICI). These SCICI promote the effective flow of goods, services, and information vital to the economic vitality of an urban environment. To re-establish the connectivity that has been broken during a disaster between the different SCICI, relationships between these systems must be identified, formulated, and added to a common framework to form a system-level restoration plan. To accomplish this goal, a considerable collection of SCICI data is necessary. The aim of this paper is to review what data are required for model construction, the accessibility of these data, and their integration with each other. While a review of publicly available data reveals a dearth of real-time data to assist modeling long-term recovery following an extreme event, a significant amount of static data does exist and these data can be used to model the complex interdependencies needed. For the sake of illustration, a particular SCICI (transportation) is used to highlight the challenges of determining the interdependencies and creating models capable of describing the complexity of an urban environment with the data publicly available. Integration of such data as is derived from public domain sources is readily achieved in a geospatial environment, after all geospatial infrastructure data are the most abundant data source and while significant quantities of data can be acquired through public sources, a significant effort is still required to gather, develop, and integrate these data from multiple sources to build a complete model. Therefore, while continued availability of high quality, public information is essential for modeling efforts in academic as well as government communities, a more streamlined approach to a real-time acquisition and integration of these data is essential.

Data Science Journal↗

Developing criteria to establish Trusted Digital Repositories

This paper details the drivers, methods, and outcomes of the U.S. Geological Survey’s quest to establish criteria by which to judge its own digital preservation resources as Trusted Digital Repositories. Drivers included recent U.S. legislation focused on data and asset management conducted by federal agencies spending $100M USD or more annually on research activities. The methods entailed seeking existing evaluation criteria from national and international organizations such as International Standards Organization (ISO), U.S. Library of Congress, and Data Seal of Approval upon which to model USGS repository evaluations. Certification, complexity, cost, and usability of existing evaluation models were key considerations. The selected evaluation method was derived to allow the repository evaluation process to be transparent, understandable, and defensible; factors that are critical for judging competing, internal units. Implementing the chosen evaluation criteria involved establishing a cross-agency, multi-disciplinary team that interfaced across the organization.

Data Science Journal↗

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↗

Estimating disease prevalence from preferentially sampled, pooled data

After the onset of the COVID-19 pandemic, scientific interest in coronaviruses endemic in animal populations has increased dramatically. However, investigating the prevalence of disease in animal populations across the landscape, which requires finding and capturing animals can be difficult. Spatial random sampling over a grid could be extremely inefficient because animals can be hard to locate, and the total number of samples may be small. Alternatively, preferential sampling, using existing knowledge to inform sample location, can guarantee larger numbers of samples, but estimates derived from this sampling scheme may exhibit bias if there is a relationship between higher probability sampling locations and the disease prevalence. Sample specimens are commonly grouped and tested in pools which can also be an added challenge when combined with preferential sampling. Here we present a Bayesian method for estimating disease prevalence with preferential sampling in pooled presence-absence data motivated by estimating factors related to coronavirus infection among Mexican free-tailed bats ( Tadarida brasiliensis ) in California. We demonstrate the efficacy of our approach in a simulation study, where a naive model, not accounting for preferential sampling, returns biased estimates of parameter values; however, our model returns unbiased results regardless of the degree of preferential sampling. Our model framework is then applied to data from California to estimate factors related to coronavirus prevalence. After accounting for preferential sampling impacts, our model suggests small prevalence differences between male and female bats.

California↗

Multi-scale clustering of functional data with application to hydraulic gradients in wetlands

A new set of methods are developed to perform cluster analysis of functions, motivated by a data set consisting of hydraulic gradients at several locations distributed across a wetland complex. The methods build on previous work on clustering of functions, such as Tarpey and Kinateder (2003) and Hitchcock et al. (2007), but explore functions generated from an additive model decomposition (Wood, 2006) of the original time se- ries. Our decomposition targets two aspects of the series, using an adaptive smoother for the trend and circular spline for the diurnal variation in the series. Different measures for comparing locations are discussed, including a method for efficiently clustering time series that are of different lengths using a functional data approach. The complicated nature of these wetlands are highlighted by the shifting group memberships depending on which scale of variation and year of the study are considered.

Journal of Data Science↗

The National Ocean Biodiversity Strategy

President Biden has been clear that the ocean is central to life on Earth. As he has proclaimed, “the ocean powers millions of jobs; feeds and sustains us; and is a rejuvenating source of inspiration, exploration, and recreation.” The Biden-Harris Administration has worked hard to fulfill the President’s goal to protect and conserve at least 30% of U.S. waters by 2030. The ocean faces increased threats from warming, overfishing, increased acidity, and loss of biodiversity. It is now more important than ever to sustain the many benefits that the ocean, coasts, and Great Lakes provide, including food, a favorable climate, recreation, physical and mental health, and for many, a sense of cultural identity. Ocean life represents an irreplaceable heritage, the foundation of a habitable planet, and a vast trove of resources. Keeping our ocean healthy requires reliable information on the changing status of these living organisms, the drivers of biodiversity change, and options for effectively addressing those drivers. Over 2 million species are estimated to live in the ocean, yet only about 240,000 species have been described by scientists. Most of the ocean’s benefits result from those diverse species interacting with one another and the environment they create. To protect and conserve the ocean, we as a nation need to make better use of existing knowledge and prioritize acquiring new biodiversity knowledge to enable better policy and management decisions. The ability to monitor ocean species and habitats has expanded dramatically over the past decade, with innovations in technology, genomics, taxonomy, big data management and sharing, artificial intelligence, and machine learning. Yet large fractions of the U.S. ocean remain almost unknown. The National Ocean Biodiversity Strategy (strategy) reflects the urgent need to leverage these advances. The goals of this strategy must be guided by the nation’s diverse voices and ways of knowing, in order to maximize effective and equitable stewardship of the ocean’s diverse life and its benefits to people. The strategy is intended as a guiding document for government to advance three overarching goals: ● Goal 1: Drive delivery of ocean biodiversity knowledge at the national scale. Objectives include developing an Implementation Plan for achieving the strategy’s three goals; establishing a coordination mechanism to manage the implementation; and documenting gaps in biodiversity knowledge and the benefits of ocean biodiversity to people and economies. ● Goal 2: Strengthen tools and institutions to deliver ocean biodiversity knowledge. Objectives include establishing a robust information pipeline to support indicators and dynamic maps of ocean biodiversity, from the coasts to the deep sea. This pipeline should include expanded observing systems and comprehensive data management; science and technology solutions to accelerate the availability of biodiversity information; and plans to leverage previous investments to rebuild and expand the nation’s human capital and infrastructure to sustain foundational taxonomy and biodiversity science. ● Goal 3: Protect, conserve, restore, and sustainably use ocean biodiversity. Objectives include expanding the collection, delivery, and use of biodiversity knowledge to inform actions that advance ocean protection, conservation, restoration, and sustainable development. Government should lead in establishing and incentivizing diverse partnerships across scales and sectors to implement those actions and should educate and involve the public to discover and value the nation’s diverse ocean life. Achieving these goals will require commitments across society: new federal and private investments, coordination across sectors to address climate and equity challenges, and engagement of Indigenous Knowledge holders and frontline communities as full partners throughout planning and implementation. The Subcommittee on Ocean Science and Technology (SOST) IWG-Biodiversity will begin developing an Implementation Plan to describe and direct specific actions to implement the strategy. Successful implementation of the strategy will harmonize and expand collection and delivery of timely knowledge on ocean life to all of society. The strategy will also enable evidence-based management and protection of the ocean. Advancing the strategy will build human and institutional capital and partnerships that support both existing mandates and new needs to rebuild and sustain biodiversity, achieve healthy ocean ecosystems, and manage living resources. Implementing the strategy will deliver knowledge for monitoring, modeling, forecasting, and assessments that support food security, public health, and cultural values, and that more effectively protect, conserve, and restore nature.

Report↗

Self calibration of small and medium format digital cameras

The knowledge of a camera’s interior orientation parameters are a prerequisite for the camera to be used in any precision photogrammetric project. Historically, the interior orientation parameters have been determined by analyzing the measured ground 3D coordinates of photo-identifiable targets, and their 2D (image) coordinates from multiple images of these targets. Camera self calibration, on the other hand, uses targets on a scene that have not been measured before. In this research, we will briefly discuss existing self calibration techniques, and present two methods for camera self calibration that are being used at the U.S. Geological Survey’s Earth Resources Observation and Science (EROS) Data Center. The first method, developed by Pictometry (augmented by Dr C.S. Fraser), uses a series of coded targets on a cage. The coded targets form different patterns that are imaged from nine different locations with differing camera orientations. A free network solution using collinearity equations is used to determine the calibration parameters. The coded targets are placed on the cage in three different planes, which allows for a robust calibration procedure. The USGS/EROS has developed an inexpensive method for calibration, particularly for calibrating short focal length cameras. In this case, the coded targets are pasted on a small prototype box and imaged from different locations and camera orientations. The design of the box is discussed, and the results of the box and the cage calibrations are compared and analyzed.

Conference Paper↗

Water resources data, Arizona, water year 2004

The USGS Arizona Water Science Center water data report includes records on both surface water and ground water in the State for water year 2004. Specifically, it contains: (1) Discharge records for 206 streamflow-gaging stations and 21 crest-stage, partial-record streamflow stations; (2) stage and (or) content records for 8 lakes and reservoirs; (3) water-quality records for 20 streamflow-gaging stations; (4) ground-water levels and compaction values for 14 stations; and (5) water levels for 18 wells.

Arizona↗

Use of USGS earth science products by city planning agencies in the San Francisco Bay region, California

An inventory of the use of USGS products in selected planning studies, plans, plan implementation devices, and other planning-related activities was completed for the ninety-one cities in the nine-county San Francisco Bay region. This inventory was designed to determine and document the use of the 85 earth science products prepared as a part of the San Francisco Bay Region Environment and Resources Planning Study (SFBRS). This inventory showed that: (1) three-fourths of the cities had planning staffs who were familiar with SFBRS products, or had made use of such products; (2) over half of the cities had prepared planning documents which contained references to SFBRS products; (3) the types of planning applications most often indicated were: geologic hazards studies; seismic safety, public safety, conservation, and open-space plan elements; general reference; and the preparation and review of environmental impact reports and statements; (4) almost 90 percent of all 85 SFBRS products were used at least once for a city planning activity, and one product was used at least 67 times for various city planning activities; and (5) at least forty-five other other USGS products were also used for various city planning activities. All of the seven SFBRS products that were used 30 or more times for city planning activities were small-scale, large-areal-coverage, hazard-type products. Each product is interpretative and contains additional data which makes it more relevant or more interesting. The planning staffs of each city were also interviewed and asked to indicate any problems in the use of the SFBRS products, to recommend improvements, and to identify any needed or desired earth science data. The responses showed that: (1) the map scales commonly used by cities were much larger than 1:12,000; (2) few cities had planning staffs with training or experience in the earth sciences or engineering; (3) less than one-fourth of the cities failed to use SFBRS products-primarily because their staffs were unaware of the SFBRS, unfamiliar with its products, or lacked adequate capability; (4) almost two-thirds of the cities expressed some problems in using the products-primarily scale and detail; (5) over two-thirds of the cities expressed an interest in continuing to use, or planning to use, the SFBRS products in the future, and a need or desire for additional earth science, engineering or other data; and (6) over one-half of the cities suggested improvements-primarily larger scale or more detail and less technical or more interpretative products. From the inventory and responses to the interviews, it is concluded that the cities in the Bay region have considerable familiarity with, and have made substantial use of, SFBRS products. This use was made by many cities despite their small size, limited staff capability, and the design of the products which was intended primarily for regional planning at a regional scale. Suggestions are made to ensure more familiarity with, and more effective use of, earth science data in the future. These suggestions include: (1) providing engineering interpretations and land-use capability ratings to make earth science data more readily usable; (2) monitoring and analyzing new state laws and regulations to better anticipate and respond to local earth science data needs; (3) including technical assistance with any earth science data designed for planners and decision-makers; (4) providing larger scale and greater detail earth science data on a demonstration basis; (5) giving priority to urban and urbanizing areas so as to conserve limited staff resources; and (6) ensuring product distribution to all potential users.

California↗

Earth science looks to outer space

Satellite data are revolutionizing coastal science. A study revealing how the El Niño/Southern Oscillation impacts coastal erosion around the Pacific Rim shows what is possible.

Nature Geoscience↗

Recent data and information system initiatives for remotely sensed measurements of the land surface

As part of the International Satellite Land Satellite Climatology Program (ISLSCP) Workshop on Remote Sensing of the Land Surface for Studies of Global Change, five invited presentations were given on recent data initiatives relevant to the ISLSCP community. The presentations are summarized in this paper along with some observations by the authors on data systems for the land sciences community. The invited presentations are by no means all inclusive but were selected as examples of current data activities, representing a range of topics associated with data for land sciences including: the generation of global and local scale data sets, the reworking of historical data sets, new data initiatives and some programmatic aspects of land data base development. This paper serves to provide information on these data initiatives and to air some of the issues concerning land science data systems that were raised at the meeting.

Remote Sensing of Environment↗

U.S. Geological Survey Community for Data Integration 2017 Workshop Proceedings

Executive Summary The U.S. Geological Survey (USGS) Community for Data Integration (CDI) Workshop was held May 16–19, 2017 at the Denver Federal Center. There were 183 in-person attendees and 35 virtual attendees over four days. The theme of the workshop was “Enabling Integrated Science,” with the purpose of bringing together the community to discuss current topics, shared challenges, and steps forward to advance integrated science at the USGS. The CDI welcomed several keynote speakers, including Bill Werkheiser, USGS Acting Director; Kevin T. Gallagher, USGS Associate Director of the Core Science Systems Mission Area; Bruce Caron, Earth Science Information Partners Community Architect; and Tim Quinn, Chief of the USGS Office of Enterprise Information. Their presentations focused on the importance of collaborative, cross-disciplinary, and open science and the role of the CDI in identifying and supporting new opportunities in these areas for the USGS and its partners. In addition to the stated theme, the workshop agenda was driven by the needs of the CDI, with topics highlighting current resources and technologies that could help attendees in their daily work. Topical sessions were proposed by CDI members and included subjects such as data citation, information technology architecture, legacy data, real-time data, and many more. Plenary speakers from the community talked about USGS activities in data science, elevation and hydrography data integration, advanced scientific computing solutions, cloud computing, data-management training, and data-sharing agreements. Two panels addressed the role of the CDI in enabling integrated science and examples of CDI-supported projects in action. Breakout discussions focused on the workshop theme of “Enabling Integrated Science” and covered five topics: Data and Data Integration, Modeling, Computing Capacity, Science Data Integration, and User Needs and Experience. Sessions on each topic identified actions that could bring the USGS and the broader Earth science community closer to the goal of making integrated science commonplace. The breakouts produced recommendations with the broad themes of improving communication and connections across the USGS, reducing duplication and increasing knowledge transfer, increasing training and testbed opportunities to learn and experiment, and creating community-supported standards to enable better integration and interoperability. The DataBlast poster and live demonstration session showcased 36 projects from around the CDI and included recent CDI-funded projects as well as other USGS and partner initiatives that were related to data and software integration and discovery. Importantly, the CDI workshop provided a forum for scientists, technologists, data and resource managers, program managers, and others to convene face to face to discuss common methods, interests, challenges, and solutions related to scientific data and technologies. As a result of this rare convergence, new connections were made across disciplines, backgrounds, and geographical locations, seeding future activities and collaborations. Sharing of ideas from all attendees was encouraged through the use of a mobile application to collect real-time questions and feedback from the audience The primary outcomes of the workshop are the recommendations from the breakout sessions titled “Roadmap Discussions on Enabling Integrated Science” and from the topical sessions detailed in these proceedings. These sessions, as well as the plenary discussions, identified new areas of collaboration and learning that the CDI will facilitate, such as data science, software development, scientific modeling practices, and user needs and experience. The CDI will build on the results of the workshop to guide its future topics, events, and funding opportunities to support an integrated science capacity for the USGS.

Open-File Report↗

Hurricane Sandy science plan: coastal topographic and bathymetric data to support hurricane impact assessment and response

Hurricane Sandy devastated some of the most heavily populated eastern coastal areas of the Nation. With a storm surge peaking at more than 19 feet, the powerful landscape-altering destruction of Hurricane Sandy is a stark reminder of why the Nation must become more resilient to coastal hazards. In response to this natural disaster, the U.S. Geological Survey (USGS) received a total of $41.2 million in supplemental appropriations from the Department of the Interior (DOI) to support response, recovery, and rebuilding efforts. These funds support a science plan that will provide critical scientific information necessary to inform management decisions for recovery of coastal communities, and aid in preparation for future natural hazards. This science plan is designed to coordinate continuing USGS activities with stakeholders and other agencies to improve data collection and analysis that will guide recovery and restoration efforts. The science plan is split into five distinct themes: • Coastal topography and bathymetry • Impacts to coastal beaches and barriers • Impacts of storm surge, including disturbed estuarine and bay hydrology • Impacts on environmental quality and persisting contaminant exposures • Impacts to coastal ecosystems, habitats, and fish and wildlife This fact sheet focuses on coastal topography and bathymetry. This fact sheet focuses on coastal topography and bathymetry.

Gulf Coast region↗

Using genetic data to advance stream fish reintroduction science: A case study in brook trout

Widespread extirpation of native fish populations has led to a rise in species reintroduction efforts worldwide. Most efforts have relied on demographic data alone to guide project design and evaluate success. However, the genetic characteristics of many imperiled fish populations including low diversity, local adaptation, and hatchery introgression emphasize the importance of genetic data in the design and monitoring of reintroduction efforts. Focusing on a case study of brook trout ( Salvelinus fontinalis ) in North Carolina, USA, we show how the combined use of genetic and demographic data can support reintroduction efforts by improving source population selection and providing opportunities to evaluate genetic viability and adaptive potential in restored populations. Using this combined approach, we reintroduced brook trout into a restored stream from two source populations and monitored changes in genetic diversity and population size in source and recipient populations. Three years after the initial translocation, the reintroduced population had comparable density, but higher genetic diversity, than either source population. This study demonstrates the utility of genetic and demographic data for reintroduction efforts, particularly when extant populations are genetically depauperate and maintaining adaptive potential is a primary restoration goal. However, we emphasize the value of continued monitoring at longer temporal and spatial scales to determine the effects of stochastic process on the long-term adaptive capacity and persistence of reintroduced populations. Overall, inclusion of genetic data in reintroduction efforts offers increased ability to meet project goals while simultaneously conserving critical sources of adaptive variation that exist across the landscape.

North Carolina↗

Asking nicely: Best practices for requesting data

Compiling disparate datasets into publicly available composite databases helps natural resource communities explore ecological trends and effectively manage across spatiotemporal scales. Though some studies have reported on the database construction phase, fewer have evaluated the data acquisition and distribution process. To facilitate future data sharing collaborations, Louisiana State University surveyed data providers and requestors to understand the characteristics of effective data requests and sharing. Data providers were largely U.S. natural resource agency personnel, and they reported that unclear data requests, privacy issues, and rigid timelines and formats were the greatest barriers toward providing data, but that they were motivated by improving science and collaboration. Data requestors identified challenges such as evolving needs, standardization issues, and insufficient resources (time and funding) as barriers to compiling data for these types of efforts. In a time of big data, open access, and collaboration, significant scientific advances can be made with effective requests and inclusion of data sets into larger and more powerful databases.

Ecological Indicators↗

PaCTS 1.0: A crowdsourced reporting standard for paleoclimate data

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on that data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the re-use value of paleoclimate datasets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, this standard elicitation process involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new vs. legacy datasets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate datasets. Since such goals are at odds with present practices, we discuss a transparent path towards implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches.

Paleoceanography and Paleoclimatology↗

Description and testing of the Geo Data Portal: Data integration framework and Web processing services for environmental science collaboration

Interest in sharing interdisciplinary environmental modeling results and related data is increasing among scientists. The U.S. Geological Survey Geo Data Portal project enables data sharing by assembling open-standard Web services into an integrated data retrieval and analysis Web application design methodology that streamlines time-consuming and resource-intensive data management tasks. Data-serving Web services allow Web-based processing services to access Internet-available data sources. The Web processing services developed for the project create commonly needed derivatives of data in numerous formats. Coordinate reference system manipulation and spatial statistics calculation components implemented for the Web processing services were confirmed using ArcGIS 9.3.1, a geographic information science software package. Outcomes of the Geo Data Portal project support the rapid development of user interfaces for accessing and manipulating environmental data.

Open-File Report↗

Seven recommendations to make your invasive alien species data more useful

Science-based strategies to tackle biological invasions depend on recent, accurate, well-documented, standardized and openly accessible information on alien species. Currently and historically, biodiversity data are scattered in numerous disconnected data silos that lack interoperability. The situation is no different for alien species data, and this obstructs efficient retrieval, combination, and use of these kinds of information for research and policy-making. Standardization and interoperability are particularly important as many alien species related research and policy activities require pooling data. We describe seven ways that data on alien species can be made more accessible and useful, based on the results of a European Cooperation in Science and Technology (COST) workshop: (1) Create data management plans; (2) Increase interoperability of information sources; (3) Document data through metadata; (4) Format data using existing standards; (5) Adopt controlled vocabularies; (6) Increase data availability; and (7) Ensure long-term data preservation. We identify four properties specific and integral to alien species data (species status, introduction pathway, degree of establishment, and impact mechanism) that are either missing from existing data standards or lack a recommended controlled vocabulary. Improved access to accurate, real-time and historical data will repay the long-term investment in data management infrastructure, by providing more accurate, timely and realistic assessments and analyses. If we improve core biodiversity data standards by developing their relevance to alien species, it will allow the automation of common activities regarding data processing in support of environmental policy. Furthermore, we call for considerable effort to maintain, update, standardize, archive, and aggregate datasets, to ensure proper valorization of alien species data and information before they become obsolete or lost.

Frontiers in Applied Mathematics and Statistics↗