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Data and Information Assets

CDI Projects tagged with Data and Information Assets. Data and information assets include persistent archives, data registries, catalogs, data, metadata, derived information products, knowledge bases, and vocabularies/ontologies.

Filter Total Items: 91

Communicating stream fish vulnerability to climate change

We will develop a vulnerability assessment R Shiny web application and present to stakeholders. The stakeholder feedback will be summarized into a one page ‘lessons learned’ document that will assist researchers in designing effective climate change visualizations and an R markdown ‘quick start’ guide on R Shiny applications.
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Communicating stream fish vulnerability to climate change

We will develop a vulnerability assessment R Shiny web application and present to stakeholders. The stakeholder feedback will be summarized into a one page ‘lessons learned’ document that will assist researchers in designing effective climate change visualizations and an R markdown ‘quick start’ guide on R Shiny applications.
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Automated accuracy and quality assessment tools (AQAT = “a cat”) for generalized geospatial data

This project develops an open-source toolkit for the consistent, automated assessment of accuracy and cartographic quality of generalized geospatial data. The toolkit will aid USGS and other stakeholders with the development and use of multiscale data and with associated decision-making.
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Automated accuracy and quality assessment tools (AQAT = “a cat”) for generalized geospatial data

This project develops an open-source toolkit for the consistent, automated assessment of accuracy and cartographic quality of generalized geospatial data. The toolkit will aid USGS and other stakeholders with the development and use of multiscale data and with associated decision-making.
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Linking orphaned oil & gas wells with groundwater quality

This project will combine the 117,000 orphaned oil and gas wells in the USGS Orphaned Well Dataset with groundwater quality data from the USGS National Water Information System (NWIS) to create a data product that can be used to analyze the interactions between orphaned wells, groundwater, and hazards to the environment.
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Linking orphaned oil & gas wells with groundwater quality

This project will combine the 117,000 orphaned oil and gas wells in the USGS Orphaned Well Dataset with groundwater quality data from the USGS National Water Information System (NWIS) to create a data product that can be used to analyze the interactions between orphaned wells, groundwater, and hazards to the environment.
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Availability, documentation, & community support for an open-source machine learning tool

We will make cutting-edge spectral analysis and machine learning algorithms available to remote sensing and chemical quantification communities, regardless of the user’s programming skills, by releasing, documenting, presenting, and developing tutorials for the Python Hyperspectral Analysis Tool.
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Availability, documentation, & community support for an open-source machine learning tool

We will make cutting-edge spectral analysis and machine learning algorithms available to remote sensing and chemical quantification communities, regardless of the user’s programming skills, by releasing, documenting, presenting, and developing tutorials for the Python Hyperspectral Analysis Tool.
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ZenRiver game concept: accelerating creation of machine learning imagery training datasets using citizen science

We aim to develop a web-based game where players use human-assisted image segmentation to produce annotated “meditation drawing” images of surface water sites to accelerate the creation of machine learning imagery training datasets. The game will also public education and outreach opportunities.
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ZenRiver game concept: accelerating creation of machine learning imagery training datasets using citizen science

We aim to develop a web-based game where players use human-assisted image segmentation to produce annotated “meditation drawing” images of surface water sites to accelerate the creation of machine learning imagery training datasets. The game will also public education and outreach opportunities.
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Evaluation and recommendation of practices for publication of reproducible data and software releases in the USGS

In practice, e.g., in model applications, data are rarely complete without workflow code and workflows are often treated as software that include data. This project aims to understand current practice and recommend future practices that better fit the needs of reproducible workflows and models.
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Evaluation and recommendation of practices for publication of reproducible data and software releases in the USGS

In practice, e.g., in model applications, data are rarely complete without workflow code and workflows are often treated as software that include data. This project aims to understand current practice and recommend future practices that better fit the needs of reproducible workflows and models.
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Increasing data accessibility by adding existing datasets and capabilities to a cutting-edge visualization app to enable cross-community use

We will collate and publish existing datasets from collaborators and ingest them into a visualization app to help researchers with machine learning model-building and hypothesis-making. These data collation and app development methods could help other researchers increase their data accessibility.
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Increasing data accessibility by adding existing datasets and capabilities to a cutting-edge visualization app to enable cross-community use

We will collate and publish existing datasets from collaborators and ingest them into a visualization app to help researchers with machine learning model-building and hypothesis-making. These data collation and app development methods could help other researchers increase their data accessibility.
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Leveraging Existing USGS Streamgage Data to Map Flood-Prone Areas

We will develop reproducible workflows in R and Python to combine already existing and underutilized field data collected as part of the USGS streamgage network with remotely sensed data to map flood-prone areas for various recurrence intervals in both gaged and ungaged stream reaches.
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Leveraging Existing USGS Streamgage Data to Map Flood-Prone Areas

We will develop reproducible workflows in R and Python to combine already existing and underutilized field data collected as part of the USGS streamgage network with remotely sensed data to map flood-prone areas for various recurrence intervals in both gaged and ungaged stream reaches.
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Seg2Map: New Tools for ML-based Segmentation of Geospatial Imagery

This proposal would fund the development of Seg2Map, a new open-source, browser-accessible software deployed on the cloud that will apply Machine Learning to imagery and image time-series, to make highly customizable to study Earth’s changing surface for a range of scientific purposes.
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Seg2Map: New Tools for ML-based Segmentation of Geospatial Imagery

This proposal would fund the development of Seg2Map, a new open-source, browser-accessible software deployed on the cloud that will apply Machine Learning to imagery and image time-series, to make highly customizable to study Earth’s changing surface for a range of scientific purposes.
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Enhancing usability of 3DEP data and web services with Jupyter notebooks

We propose to develop a suite of Jupyter notebooks that leverage existing APIs, cloud storage, and open source tools to make it easier for users to efficiently access USGS 3DEP data and to produce data processing and visualization workflows. These notebooks will enhance data utilization, stimulate creative applications, and generate significant return on investment for 3DEP.
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Enhancing usability of 3DEP data and web services with Jupyter notebooks

We propose to develop a suite of Jupyter notebooks that leverage existing APIs, cloud storage, and open source tools to make it easier for users to efficiently access USGS 3DEP data and to produce data processing and visualization workflows. These notebooks will enhance data utilization, stimulate creative applications, and generate significant return on investment for 3DEP.
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CorVis: A lidar point cloud tool for visualization and analysis of corridors such as hydrologic, energy, and transportation networks

An open-source tool for 3D visualization of lidar point cloud data along a vector line network and output of related lidar metrics. This tool will make available the valuable attribute data of point clouds to enable research such as riparian zone and migration corridor vegetation structure analysis or characterizing the related built environment.
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CorVis: A lidar point cloud tool for visualization and analysis of corridors such as hydrologic, energy, and transportation networks

An open-source tool for 3D visualization of lidar point cloud data along a vector line network and output of related lidar metrics. This tool will make available the valuable attribute data of point clouds to enable research such as riparian zone and migration corridor vegetation structure analysis or characterizing the related built environment.
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Circle Round the River: A Summit for Collaborative Sharing of Flood Knowledge with Tribal Colleges and Tribal Environmental Professionals

We propose a summit for USGS and Tribal nation partners to share critical knowledge of past and future flooding. The summit will build on USGS research investigating changing flood conditions, improve access to flood information, and aid in building climate resilient communities.
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Circle Round the River: A Summit for Collaborative Sharing of Flood Knowledge with Tribal Colleges and Tribal Environmental Professionals

We propose a summit for USGS and Tribal nation partners to share critical knowledge of past and future flooding. The summit will build on USGS research investigating changing flood conditions, improve access to flood information, and aid in building climate resilient communities.
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