This dataset contains data for the Healthcare Payments Data (HPD) Snapshot visualization. The Enrollment data file contains counts of claims and encounter data collected for California's statewide HPD Program. It includes counts of enrollment records, service records from medical and pharmacy claims, and the number of individuals represented across these records. Aggregate counts are grouped by payer type (Commercial, Medi-Cal, or Medicare), product type, and year. The Medical data file contains counts of medical procedures from medical claims and encounter data in HPD. Procedures are categorized using claim line procedure codes and grouped by year, type of setting (e.g., outpatient, laboratory, ambulance), and payer type. The Pharmacy data file contains counts of drug prescriptions from pharmacy claims and encounter data in HPD. Prescriptions are categorized by name and drug class using the reported National Drug Code (NDC) and grouped by year, payer type, and whether the drug dispensed is branded or a generic.

This dataset contains compositional data on 17 produced water samples from hydraulically fractured unconventional oil wells completed in the Middle Bakken and Three Forks Formations. The oil wells are located in five different wellfields across the Williston Basin. Specific gravity, conductivity, temperature, pH and oxidation-reduction potential for each sample was measured in the field. Ions (B, Li, Cl, Na, Br), biomarkers (Pristane /n-C17 and Phytane /n-C18), glycol ether compounds, major ions, as well as radium (Ra-228/Ra-226), boron (δ11B), oxygen (δ18O) and hydrogen (δ2H) isotopic ratios were analyzed in the lab. Well profiles are provided to increase understanding of the produced waters compositions in the context of the depth of the well, age of the well, the time since hydraulic fracturing, the amounts of water injected and produced since hydraulic fracturing, the hydraulic fracturing treatment fluid types injected.

MY NASA DATA (MND) is a tool that allows anyone to make use of satellite data that was previously unavailable.Through the use of MND’s Live Access Server (LAS) a multitude of charts, plots and graphs can be generated using a wide variety of constraints. This site provides a large number of lesson plans with a wide variety of topics, all with the students in mind. Not only can you use our lesson plans, you can use the LAS to improve the ones that you are currently implementing in your classroom.

The Maine Geological Survey and the USGS coordinate the colletction of snow measurements each winter for the Maine River Flow Advisory Commission's flood prediction report. These measurements are sent to MGS monthly in January and February and weekly in March, April and May as long as there is snow on the ground. The dataset contains all the raw snow survey measurements (depth (inches), water content (inches), and density), their locations, data quality, and other qualitative comments or observations. These measurements are used to create the snow survey statewide maps.

The Moran electromagnetic, magnetic, and radiometric airborne geophysical survey is located in interior Alaska in the Melozitna and Hot Springs mining districts, about 225 kilometers southeast of Fairbanks. Frequency domain electromagnetic, magnetic, and radiometric data were collected with the DIGHEMV system from July to August 2009. A total of 4685.9 line kilometers were collected covering 1691.3 square kilometers. Line spacing was 400 meters (m). Data were collected 30 m above the ground surface from a helicopter towed sensor platform ('bird') on a 30 m long line. The surevey was conducted by Fugro Airborne Surveys Corp. and Stevens Exploration Management Corp. and administered by the Alaska Geological & Geophysical Surveys (DGGS). The data, as well as additional metadata, are available from the DGGS website: http://doi.org/10.14509/30201.

The BOREAS TF-10 team collected tower flux and meteorological data at two sites, a fen and a young jack pine forest, near Thompson, Manitoba, Canada, as part of BOREAS. A preliminary data set was assembled in August 1993 while field testing the instrument packages, and at both sites data were collected from 15-Aug to 31-Aug. The main experimental period was in 1994, when continuous data were collected from 08-Apr to 23-Sept at the fen site. A very limited experiment was run in the spring/summer of 1995, when the fen site tower was operated from 08-Apr to 14-Jun in support of a hydrology experiment in an adjoining, feeder basin. Upon examination of the 1994 data set, it became clear that the behavior of the heat, water, and carbon dioxide fluxes throughout the whole growing season was an important scientific question, and that the 1994 data record was not sufficiently long to capture the character of the seasonal behavior of the fluxes. Thus, the fen site was operated in 1996 in order to collect data from spring melt to autumn freeze-up. Data were collected from 29-Apr to 05-Nov at the fen site. All variables are presented as 30-minute averages.

The dataset consists of closed cases that resulted in penalty assessments by EBSA since 2000. This data provides information on EBSA's enforcement programs to enforce ERISA's Form 5500 Annual Return/Report filing requirement focusing on deficient filers, late filers and non-filers.

Dataset tables listing: EBSA Data Dictionary, EBSA Metadata and EBSA OCATS.

Link to the Open Data site for the United States Census Bureau.

mlfoundations-cua-dev/eval-grounding-data dataset hosted on Hugging Face and contributed by the HF Datasets community

This dataset provides 10-minute fire emissions within 0.1-degree regularly spaced intervals across Indonesia from July 2015 to December 2020. The dataset was produced with a top-down approach based on fire radiative energy (FRE) and smoke aerosol emission coefficients (Ce) derived from multiple new-generation satellite observations. Specifically, the Ce values of peatland, tropical forest, cropland, or savanna and grassland were derived from fire radiative power (FRP) and emission rates of smoke aerosols based on Visible Infrared Imaging Radiometer Suite (VIIRS) active fire and aerosol products. FRE for each 0.1-degree interval was calculated from the diurnal FRP cycle that was reconstructed by fusing cloud-corrected FRP retrievals from the high temporal-resolution (10 mins) Himawari-8 Advanced Himawari Imager (AHI) with those from high spatial-resolution (375 m) VIIRS. This new dataset was named the Fused AHI-VIIRS based fire Emissions (FAVE). Fire emissions data are provided in comma-separated values (CSV) format with one file per month from July 2015 to December 2020. Each file includes variables of fire observation time, fire geographic location, classification, fire radiative energy, various fire emissions and related standard deviations.

This data set consists of Conductivity, Temperature, Depth (CTD) data in MATLAB Format from the 2002 Polar Star Mooring Cruise (AWS-02-I). These data are provided in a single mat-file (MATLAB) for the entire cruise.

List and description of datasets available on Open Data for Fairfax County, Virginia

This dataset globally (excluding frigid/polar zones) quantifies the different facets of variability in surface soil (0 – 30 cm) salinity and sodicity for the period between 1980 and 2018. This is realised by developing 4-D predictive models of Electrical Conductivity of saturated soil Extract (ECe) and soil Exchangeable Sodium Percentage (ESP) as indicators of soil salinity and sodicity. These machine learning-based models make predictions for ECe and ESP at different times, locations, and depths and by extracting meaningful statistics form those predictions, different facets of variability in the surface soil salinity and sodicity are quantified. The dataset includes 10 maps documenting different aspects of soil salinity and sodicity variations, and auxiliary data required for generation of those maps. Users are referred to the corresponding "READ_ME" file for more information about this dataset.

Note: data is continuously updated・ PG&E provides non-confidential, aggregated usage data that are available to the public and updated on a quarterly basis. These public datasets consist of monthly consumption aggregated by ZIP code and by customer segment: Residential, Commercial, Industrial and Agricultural. The public datasets must meet the standards for aggregating and anonymizing customer data pursuant to CPUC Decision 14-05-016, as follows: a minimum of 100 Residential customers; a minimum of 15 Non-Residential customers, with no single Non-Residential customer in each sector accounting for more than 15% of the total consumption. If the aggregation standard is not met, the consumption will be combined with a neighboring ZIP code until the aggregation requirements are met.

The Site Averaged AMS Data: 1988 (Betts) Data Set contains the site averaged product of the Portable Automatic Meteorological Station (AMS) data acquired during the 1987-1989 FIFE experiment. Data are in 30 minute time intervals in 1988.

Test Depeca Data

## Overview

Test Depeca Data is a dataset for object detection tasks - it contains Polyps annotations for 460 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Statewide AEM Surveys Project Overview

The Department of Water Resources’ (DWR’s) Statewide Airborne Electromagnetic (AEM) Surveys Project is funded through California’s Proposition 68 and the General Fund. The goal of the project is to improve the understanding of groundwater aquifer structure to support the state and local goal of sustainable groundwater management and the implementation of the Sustainable Groundwater Management Act (SGMA).

During an AEM survey, a helicopter tows electronic equipment that sends signals into the ground which bounce back. The data collected are used to create continuous images showing the distribution of electrical resistivity values of the subsurface materials that can be interpreted for lithologic properties. The resulting information will provide a standardized, statewide dataset that improves the understanding of large-scale aquifer structures and supports the development or refinement of hydrogeologic conceptual models and can help identify areas for recharging groundwater.

DWR collected AEM data in all of California’s high- and medium-priority groundwater basins, where data collection is feasible. Data were collected in a coarsely spaced grid, with a line spacing of approximately 2-miles by 8-miles. AEM data collection started in 2021 and was completed in 2023. Additional information about the project can be found on the Statewide AEM Survey website. See the publication below for an overview of the project and a preliminary analysis of the AEM data.

California’s Statewide Airborne Electromagnetic Surveys and Preliminary Hydrogeologic Interpretations

Survey Areas

AEM data are being collected in groups of groundwater basins, defined as a Survey Area. See Survey Area Map for groundwater subbasins within a Survey Area:

• Survey Area 1: 180/400 Foot Aquifer (partial), East Side (partial), Upper Valley, Forebay Aquifer, Paso Robles, Atascadero (limited), Adelaida (limited), Cuyama Valley.
• Survey Area 2: Scott River Valley, Shasta Valley, Butte Valley, Tulelake, Fall River Valley (limited), Big Valley (Modoc/Lassen County).
• Survey Area 3: Big Valley (Lake County), Ukiah Valley, Santa Rosa Plain, Petaluma Valley, Sonoma Valley.
• Survey Area 4: White Wolf, Kern County, Tulare Lake, Tule, Kaweah.
• Survey Area 5: Pleasant Valley, Westside, Kings, Madera, Chowchilla, Merced, Turlock, Modesto, Delta-Mendota
• Survey Area 6: Cosumnes, Tracy, Eastern San Joaquin, East Contra Costa, Solano, Livermore, South American, North American, Yolo, Sutter, South Yuba, North Yuba
• Survey Area 7: Colusa, Butte, Wyandotte Creek, Vina, Los Molinos, Corning, Red Bluff, Antelope, Bowman, Bend, Millville, South Battle Creek, Anderson, Enterprise, Eel River, Sierra Valley
• Survey Area 8: Seaside, Monterey, 180/400 (partially surveyed Summer 2021), Eastside (partially surveyed Summer 2021), Langley, Pajaro, Santa Cruz Mid-County, Santa Margarita, San Benito, and Llagas (partial).
• Survey Area 9: Basin Characterization Pilot Study 1 - Madera and Kings.
• Survey Area 10: San Antonio Creek Valley, Arroyo Grande, Santa Maria, San Luis Obispo, Los Osos Area, Warden Creek, Chorro Valley (limited), Morro Valley (limited)
• Survey Area 11: Indian Wells Valley, Rose Valley, Owens Valley, Fish Slough, Indio, Mission Creek, West Salton Sea (limited), East Salton Sea (limited), Ocotillo-Clark Valley (limited), Imperial Valley (limited),Chocolate Valley (limited), Borrego Springs, and San Jacinto

Data Reports

Data reports detail the AEM data collection, processing, inversion, interpretation, and uncertainty analyses methods and procedures. Data reports also describe additional datasets used to support the AEM surveys, including digitized lithology and geophysical logs. Multiple data reports may be provided for a single Survey Area, depending on the Survey Area coverage.

Data Availability and Types

All data collected as a part of the Statewide AEM Surveys will be made publicly available, by survey area, approximately six to twelve months after individual surveys are complete (depending on survey area size). Datasets that will be publicly available include:

AEM Datasets

• Raw AEM Data
• Processed AEM Data
• Inverted AEM Data
• Inverted AEM Data Uncertainty Analysis
• Interpreted AEM Data (for coarse fraction)
• Interpreted AEM Data Uncertainty Analysis

Supporting Datasets

• Flown Survey Lines
• Digitized Lithology and Geophysical Logs

NEW! Revisions to digitized lithology and geophysical logs

AEM Data Viewers

DWR has developed AEM Data Viewers to provides a quick and easy way to visualize the AEM electrical resistivity data and the AEM data interpretations (as texture) in a three-dimensional space. The most recent data available are shown, which my be the provisional data for some areas that are not yet finalized. The Data Viewers can be accessed by direct link, below, or from the Data Viewer Landing Page.

• AEM 3D Viewer (Beta) (computer only)

• AEM Profile Viewer

• SGMA Data Viewer (Basin Characterization tab)

AEM Depth Slice and Shallow Subsurface Average Maps

As a part of DWR’s upcoming Basin Characterization Program, DWR will be publishing a series of maps and tools to support advanced data analyses. The first of these maps have now been published and provide analyses of the Statewide AEM Survey data to support the identification of potential recharge areas. The maps are located on the SGMA Data Viewer (under the Hydrogeologic Conceptual Model tab) and show the AEM electrical resistivity and AEM-derived texture data as the following:

• Shallow Subsurface Average: Maps showing the average electrical resistivity and AEM-derived texture in the shallow subsurface (the top approximately 50 feet below ground surface). These maps support identification of potential recharge areas, where the top 50 feet is dominated by high resistivity or coarse-grained materials.

• Depth Slices: Depth slice automations showing changes in electrical resistivity and AEM-derived texture with depth. These maps aid in delineating the geometry of large-scale features (for example, incised valley fills).

Shapefiles for the formatted AEM electrical resistivity data and AEM derived texture data as depth slices and the shallow subsurface average can be downloaded here:

• Electrical Resistivity Depth Slices and Shallow Subsurface Average Maps

• Texture Interpretation (Coarse Fraction) Depth Slices and Shallow Subsurface Average Maps

Technical Memos

Technical memos are developed by DWR's consultant team (Ramboll Consulting) to describe research related to AEM survey planning or data collection. Research described in the technical memos may also be formally published in a journal publication.

• AEM Test Flights to Evaluate the Bias Signal Caused by Vineyard Trellises Containing Metal

• SkyTEM Instrument Comparison for Airborne EM

2018-2020 AEM Pilot Studies

Three AEM pilot studies were conducted in California from 2018-2020 to support the development of the Statewide AEM Survey Project. The AEM Pilot Studies were conducted in the Sacramento Valley in Colusa and Butte county groundwater basins, the Salinas Valley in Paso Robles groundwater basin, and in the Indian Wells Valley groundwater basin.

Provisional Statement

Data Reports and datasets labeled as provisional may be incomplete and are subject to revision until they have been thoroughly reviewed and received final approval. Provisional data and reports may be inaccurate and subsequent review may result in revisions to the data and reports. Data users are cautioned to consider carefully the provisional nature of the information before using it for decisions that concern personal or public safety or the conduct of business that involves substantial monetary or operational consequences.

Catalog of source data for tsunami inundation modeling in Alaska, Digital Data Series 21, provides tsunami source models developed for tsunami hazard assessments of at-risk coastal communities throughout Alaska. Tsunami sources include great (M8 or more) earthquakes in Alaska and around the Pacific Ocean Basin, as well as submarine and subaerial landslides, and include slip distributions and seafloor deformations and landslide volumes, respectively, as georeferenced TIFF files. Alaska Division of Geological & Geophysical Surveys and the University of Alaska, Alaska Earthquake Center staff initiated the tsunami hazard assessment program in the late 1990s as a component of the NOAA/NWS-funded National Tsunami Hazard Mitigation Program (NTHMP). This resource and supporting data repository provide a comprehensive, public-facing, searchable catalog of all tsunami sources used in decades of Alaska tsunami hazard studies to promote transparency, facilitate scientific reproducibility, and satisfy NTHMP archival requirements. Seismic and non-seismic digital tsunami sources from future hazard studies will be appended to this database as appropriate. The files are and indexed by the community names and the publications in which they are utilized. Please see the linked accompanying reports for a more detailed description of the development and use of individual tsunami source models. This data collection is released with an open end-user license. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/30953).

This dataset contains the initial and boundary conditions in GRIB format files to be used as input to the models. SALLJEX was funded by NOAA/OGP, NSF(ATM0106776) and funding agencies from Brazil FAPESP Grant 01/13816-1) and Argentina (ANPCYT PICT 07-06671, UBACyT 055)

These data show how different types of rocks resist the flow of electrical currents across Ireland. The rock types can then be mapped. The data were collected between 2005 and 2021.Several surveys were merged to create this dataset. (1) Tellus Northern Ireland 2005-2006(2) Cavan-Monaghan, 2006(3) Tellus Border, 2011-2012(4) Tellus North Midlands, 2014-2015(5) Block A1, 2015(6) Block A2, 2016(7) Waterford, 2016(8) Block A3, 2017(9) Block A4, 2017(10) Block A5, 2018-2019(11) Block A6, 2018-2019(12) Block A7, 2019(13) Block A8 2020-2021(14) Block A9 2021The data were collected using an airplane. The airplane flies at 60 m flight height along lines that are 200 m apart. Electromagnetic data are recorded at around 6 m intervals along the flight lines. The electromagnetic system mounted on the airplane sends an electromagnetic signal (at different frequencies) into the ground and records the response of the ground returning to the system receiver. The response changes depending on the type of rock or soil that the electromagnetic signal meets. For example, graphite has a high response value (meaning it is a low resistivity rock) while limestone has a low response value (it is a high resistivity rock).The data are collected as points in XYZ format. X and Y are the airplane coordinates. Z is the different recorded data, which include electromagnetic responses and aircraft flight height. The XYZ data for each line contains thousands of points. The data from separate lines are merged to create a resistivity grid for each survey block. All the survey blocks are then merged to create a final resistivity grid for Ireland.Colours are used to show resistivity ranges. Resistivity values are defined in ohm-metre units. Pinks and reds show the highest values. Greens and blues show lower values.This is a raster dataset. Raster data stores information in a cell-based manner and consists of a matrix of cells (or pixels) arranged into rows and columns. The format of the raster is a grid. The grid cell size is 50 m by 50 m. This means that each cell (pixel) represents an area on the ground of 50 metres squared. Each cell has a colour showing the resistivity value of the rocks.The Tellus project is a national survey which collects geochemical and geophysical data across Ireland. It allows us to study the chemical and physical properties of our soil, rocks and water. It is managed by the Geological Survey Ireland.