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This metadata record describes the materials contained in stake folder 696. Stake 696 is located at latitude 36.39889, longitude -112.63056. This location was photographed in the following years: 1872, 1968 and 1972. The materials associated with this item include original best quality images from each repeat date (preserved as digitized film images or in some cases digitized print photographs, depending on availability), scanned film envelopes with camera metadata, records of repeat photography sheets, and all field notes and/or camera notes associated with this stake. All attachments follow the following naming convention: stake_date_material_type_Kanab. Some stakes will have multiple materials from one repeat...
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This metadata record describes the materials contained in stake folder 713. Stake 713 is located at latitude 36.42478, longitude -112.63036. This location was photographed in the following years: 1872 and 1968. The materials associated with this item include original best quality images from each repeat date (preserved as digitized film images or in some cases digitized print photographs, depending on availability), scanned film envelopes with camera metadata, records of repeat photography sheets, and all field notes and/or camera notes associated with this stake. All attachments follow the following naming convention: stake_date_material_type_Kanab. Some stakes will have multiple materials from one repeat date...
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This metadata record describes the materials contained in stake folder 2595. Stake 2595 is located at latitude 36.392, longitude -112.629. This location was photographed in the following years: 1942 and 1993. The materials associated with this item include original best quality images from each repeat date (preserved as digitized film images or in some cases digitized print photographs, depending on availability), scanned film envelopes with camera metadata, records of repeat photography sheets, and all field notes and/or camera notes associated with this stake. All attachments follow the following naming convention: stake_date_material_type_Kanab. Some stakes will have multiple materials from one repeat date (e.g.,...
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This metadata record describes the materials contained in stake folder 1506. Stake 1506 is located at latitude 36.38585, longitude -112.63963. This location was photographed in the following years: 1909 (no physical image) and 1990. The materials associated with this item include original best quality images from each repeat date (preserved as digitized film images or in some cases digitized print photographs, depending on availability), scanned film envelopes with camera metadata, records of repeat photography sheets, and all field notes and/or camera notes associated with this stake. All attachments follow the following naming convention: stake_date_material_type_Kanab. Some stakes will have multiple materials...
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This metadata record describes the materials contained in stake folder 2411. Stake 2411 is located at latitude 36.426, longitude -112.639. This location was photographed in the following years: 1872, 1968 and 1995. The materials associated with this item include original best quality images from each repeat date (preserved as digitized film images or in some cases digitized print photographs, depending on availability), scanned film envelopes with camera metadata, records of repeat photography sheets, and all field notes and/or camera notes associated with this stake. All attachments follow the following naming convention: stake_date_material_type_Kanab. Some stakes will have multiple materials from one repeat date...
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The original time series and cross power data were stored in Binary format on 3.5" disks until further conversion was needed. To convert the time series and cross power data to a format that can be used for modeling, the original binary files were converted to ASCII format using Basic 4.0 code and associated subroutines (see Magnetotelluric_Original-Code_Binary-to-Ascii.txt and Magnetotelluric_Original-Code_Binary-to-Ascii-Subroutines.txt attached to the binary data ScienceBase item). The DaR project used these converted ASCII format files to create the EDI format files included in this data release. The binary data are considered the original data for the magnetotelluric survey, therefore, they are provided with...
This folder contains information on projects supported by the Community for Data Integration (CDI) in FY2015. Learn more about CDI and our proposals process on our website.
This folder contains information on projects supported by the Community for Data Integration (CDI) in FY2017. Learn more about CDI and our proposals process on our website.
Case Study Type: Science Center Inventory Related LDIRS Collection: Great Lakes Historical Water Temperature Profile Data - Bathythermograph Data Rescue (content no longer available) The Data at Risk (DaR) project set goals to inventory two different partnering science centers in order to 1) investigate the best methods to approach inventorying a USGS science center and 2) continue to expand the USGS legacy data inventory through the online Legacy Data Inventory Reporting System (LDIRS) tool. The investigation at the Great Lakes Science Center (GLSC) tested two different inventory methods and uncovered the benefits and drawbacks of each. The Great Lakes Science Center (GLSC), headquartered in Ann Arbor,...
ScienceCache was originally developed as a mobile device data collection application for a citizen science project. ScienceCache communicates with a centralized database that facilitates near-real-time use of collected data that enhances efficiency of data collection in the field. We improved ScienceCache by creating a flexible, reliable platform that reduces effort required to set up a survey and manage incoming data. Now, ScienceCache can be easily adapted for citizen science projects as well as restricted to specific users for private internal research. We improved scEdit, a web application interface, to allow for creation of more-complex data collection forms and survey routes to support scientific studies....
Categories: Publication; Types: Document
This module is a product of the 2012 CDI-funded project Python port of Geo Data Portal (GDP) client tools (WPS) with hooks for ArcGIS Toolbox. The purpose of the module is to increase the functionality of the USGS Geo Data Portal (GDP). The GDP, developed by USGS’s Center for Integrated Data Analytics, provides a powerful functionality to process climate and other large remote gridded data, returning summary statistics and areal tabulations over user specified areas. Currently the user interface is an interactive web form, returning a CSV table. This work allows users to access the functionality directly via a GDP Python module. Benefits: Enables scientists to bring subsets of climate models and other GDP...
This project aimed to advance the long-standing need for a more formalized approach to data management planning at the science center (program) level in USGS. The study used two different science centers as test cases. Improved planning for data management and data integration is identified in the Bureau science strategy goals (U.S. Geological Survey, 2007; Burkett and others, 2011) with the need for consistent and unified data management to allow for accessible and high confidence data and information from the USGS science community. Principal Investigator : Thomas E Burley, Stan Smith Benefits Two data management models for other science centers to use Data management framework tested by use case scenario ...
This project created a mobile application to collect nationally consistent data of fish passage barriers in the United States to meet needs for hydrologic and ecological assessments and conservation planning decisions. Principal Investigator : David R Maltby, Andrea Ostroff Benefits Meets high priority need for hydrological and ecological assessments Data available to conservation planners Expand USGS scientific and technical support to the National Fish Habitat Action Plan Deliverables Presentation given at CDI-hosted Webinar (September 2012) Available to both iPhone (iOS6) and Android (3.0 or higher). Uses the geo-locational services provides with HTML5 to correlate location with an online data entry form...
CDI helped fund development of the USGS Geo Data Portal in 2010. In 2012, CDI funded two projects to increase the functionality of the Geo Data Portal. The Resources section below contains links to the Geo Data Portal website and deliverables from the 2012 projects. Principal Investigator : David L Blodgett Description of the Geo Data Portal from the Geo Data Portal documentation home : The USGS Geo Data Portal (GDP) project provides scientists and environmental resource managers access to downscaled climate projections and other data resources that are otherwise difficult to access and manipulate. This user interface demonstrates an example implementation of the GDP project web-service software and standards-based...
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FAIR is an international set of principles for improving the findability, accessibility, interoperability, and reusability of research data and other digital products. The PIs for this CDI project planned and hosted a workshop of USGS data stakeholders, data professionals, and managers of USGS data systems from across the Bureau’s Mission Areas. Workshop participants shared case studies that fostered collaborative discussions, resulting in recommended actions and goals to make USGS research data more FAIR. Project PIs are using the workshop results to produce a roadmap for adopting FAIR principles in USGS. The FAIR Roadmap will be foundational to FY2021 CDI activities to ensure the persistence and usability of...
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Recent open data policies of the Office of Science and Technology Policy (OSTP) and Office of Management and Budget (OMB), which were fully enforceable on October 1, 2016, require that federally funded information products (publications, etc.) be made freely available to the public, and that the underlying data on which the conclusions are based must be released. A key and relevant aspect of these policies is that data collected by USGS programs must be shared with the public, and that these data are subject to the review requirements of Fundamental Science Practices (FSP). These new policies add a substantial burden to USGS scientists and science centers; however, the upside of working towards compliance with...
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Over the last few years, the ISO 19115 family of metadata standards has become the predominantly accepted worldwide standard for sharing information about the availability and usability of scientific datasets among researchers. The U.S. interests in the ISO standard have also been growing as global-scale science demands participation with the broader international community; however, adoption has been slow because of the complexity and rigor of the ISO metadata standards. In addition, support for the standard in current implementations has been minimal. Principal Investigator : Stan Smith, Joshua Bradley Cooperator/Partner : Chis Turner In 2009, the Alaska Data Integration Working Group members (ADIwg) mobilized...
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Inventories of landslides and liquefaction triggered by major earthquakes are key research tools that can be used to develop and test hazard models. To eliminate redundant effort, we created a centralized and interactive repository of ground failure inventories that currently hosts 32 inventories generated by USGS and non-USGS authors and designed a pipeline for adding more as they become available. The repository consists of (1) a ScienceBase community page where the data are available for download and (2) an accompanying web application that allows users to browse and visualize the available datasets. We anticipate that easier access to these key datasets will accelerate progress in earthquake-triggered ground...
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Deep learning is a computer analysis technique inspired by the human brain’s ability to learn. It involves several layers of artificial neural networks to learn and subsequently recognize patterns in data, forming the basis of many state-of-the-art applications from self-driving cars to drug discovery and cancer detection. Deep neural networks are capable of learning many levels of abstraction, and thus outperform many other types of automated classification algorithms. This project developed software tools, resources, and two training workshops that will allow USGS scientists to apply deep learning to remotely sensed imagery and to better understand natural hazards and habitats across the Nation. The tools and...
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We are working to incorporate environmental DNA (eDNA) data into the Nonindigenous Aquatic Species (NAS) database, which houses over 570,000 records of nonindigenous species nationally, and already is used by a broad user-base of managers and researchers regularly for invasive species monitoring. eDNA studies have allowed for the identification and biosurveillance of numerous invasive and threatened species in managed ecosystems. Managers need such information for their decision-making efforts, and therefore require that such data be produced and reported in a standardized fashion to improve confidence in the results. As we work to gain community consensus on such standards, we are finalizing the process for submitting...
map background search result map search result map USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 1506 USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 2411 USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 2595 USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 0696 USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 0713 Magnetotelluric Data from the San Andreas Fault, Parkfield CA, 1990: Binary Data USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 1506 USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 2411 USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 2595 USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 0696 USGS Southwest Repeat Photography Collection: Kanab Creek, southern Utah and northern Arizona, 1872-2010: Stake 0713 Magnetotelluric Data from the San Andreas Fault, Parkfield CA, 1990: Binary Data