AndreaBozzo/ceres-open-data-index huggingface dataset:
Vegetation - Manzanar National Historic Site [ds3129]

<div style='text-align:Left;'><div><div><p style='margin:0 0 11 0;'><span><span>The NPS Vegetation Inventory Program goals are, among others, to consistently map and document the vegetation of all National Park Service units with a resource component, thereby creating a baseline vegetation inventory. Based on these decisions the final vegetation inventory project boundary covered 330-hectares (814-acres) consisting of the MANZ boundary as it existed in 2005. All plant community data that could be interpreted from the 2010 NAIP Ortho Photography for Inyo County, California - Manzanar Quadrangle were digitized in accordance with the minimum mapping unit (MMU) of 1/2 hectare. This included selected features that fell into the National Vegetation Classification and the Anderson Level II land use classification. Some classes below the MMU were included, especially water and wetland features, weed patches, and those at the edge of the study area (i.e. cut off by other features and borders). Managed roads (to visible right-of-way or fence line) and streams/drainages wider than 10 meters were digitized as polygons and attributed accordingly.  Polygons were checked in the field and attributed accordingly. The final MANZ spatial database and map layer was produced by CTI from 2010 imagery using 21 map units that were directly cross-walked or matched to their corresponding rUSNVC plant association/alliance or land cover types (FGDC 2008). Maps and other spatial data products for parks in the Continental United States are normally produced in Universal Transverse Mercator (UTM) projection, North America 1983 (NAD 83) datum, use meters for map and distance units, and have a nominal 1:24,000-scale with a minimum mapping unit (MMU) of 0.5 hectare (1.2 acres). The vegetation maps must meet the National Map Accuracy Standards for positional accuracy (TNC and ESRI 1994a &amp; Lea and Curtis 2010), and the recently revised minimum map class accuracy goal across all vegetation and land cover classes of 60% percent at the finest scale (formerly 80%, NPS 2009).The final map layer was assessed for thematic accuracy by creating contingency tables and the final overall accuracy of the map layer was determined to be 96% with a Kappa value of 95%. </span></span></p><p><p style='margin:0 0 11 0;'><span><span>More information can be found in the project report, which is bundled with the vegetation map published for BIOS here: </span></span><a href='https://filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/3100_3199/ds3129.zip' style='text-decoration:underline;' rel='nofollow ugc'><span style='text-decoration:underline;'><span>https://filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/3100_3199/ds3129.zip</span></span></a></p><p><span /></p></div></div></div></p>
Urban Water Data - Drought Planning and Management

This data package aims to pilot an approach for providing usable data for analyses related to drought planning and management for urban water suppliers--ultimately contributing to improvements in communication around drought. This project was convened by the California Water Data Consortium in partnership with the Department of Water Resources (DWR) and the State Water Resources and Control Board (SWB) and is one of two use cases of this working group that aim to improve data submitted by urban water suppliers in terms of accessibility and useability. The datasets from DWR and the SWB are compiled in a standard format to allow interested parties to synthesize and analyze these data into a cohesive message. This package includes a data management plan describing its development and maintenance. All code related to preparing this data package can be found on [GitHub](https://github.com/FlowWest/urban-water-drought-data). Please note that the "org_id" (DWR's Organization ID) and the "pwsid" (SWB's Public Water System ID) can be used to connect to the various data tables in this package.

We acknowledge that data quality issues may exist. Making these data available in a usable format will help identify and address data quality issues. If you identify any data quality issues, please contact the data steward (see contact information). We plan to iteratively update this data package to incorporate new data and to update existing data with quality fixes. The purpose of this project is to demonstrate how data from two agencies, when made publicly available, can be used in relevant analyses; if you found this data package useful, please contact the data steward (see contact information) to share your experience.
Mule Deer Migration Lines - Modoc Interstate CA and OR - 1999-2001, 2017-2020 [ds2893]

<div style='text-align:Left;'><div><div><p style='margin:0 0 11 0;'><span><span>The project leads for the collection of this data were Julie Garcia and Richard Shinn. Female mule deer were captured in February 2017 and equipped with satellite collars manufactured by Lotek, which collected GPS data to June 2020. Additional GPS data was collected from deer in 1999-2001 and included in the analysis to supplement the small sample size of the 2017-2020 dataset. The data was collected from deer throughout Modoc County with a priority to ascertain general distributions, survival, and home range and not to model migration routes, hence the low sample sizes in specific winter ranges. The Modoc Interstate deer herd migrates from a winter range near Clear Lake Reservoir in Modoc County, California north into Oregon in Klamath and Lake counties for the summer. GPS locations were fixed at 12-hour intervals in the 2017-2020 dataset and 8-hour intervals in the 1999-2001 dataset. </span></span></p><p style='margin:0 0 11 0;'><span><span>Migration lines as symbolized connect GPS data points per deer per seasonal migration. GPS points were extracted only during migrations using net-squared displacement graphs. Sixteen migration sequences from 12 deer, with an average migration time of 23.89 days and an average migration distance of 69.71 km, were obtained from the 1999-2001 dataset. Thirty-six migration sequences from 9 deer, with an average migration time of 19.53 days and an average migration distance of 87.57 km, were obtained from the 2017-2020 dataset. </span></span></p></div></div></div>
Amphibian Restoration - High Mountain Lakes [ds103]

<div style='text-align:Left;'><div><div><p><span>This data provides an overview of native amphibian restoration sites in the Sierra Nevada. Following High Mountain Lakes surveys, fish were manually removed at some high elevation lake sites. Removals of non-native trout were done at sites with mountain yellow-legged frogs or with frogs nearby. Fish removal is done without the use of chemicals, using monofilament gill nets and electrofishing. Gill nets catch adult and juvenile fish. Electrofishing is used primarily as a way to remove fish from small tributary streams and fry (less than 70mm) from shallow areas. Current literature has shown that mountain yellow-legged frog populations can rebound quickly after trout removal. Frog population counts at CDFW sites support this finding. The restoration data, along with the related high mountain lakes amphibian, fish and fisheries project data sets represent biological surveys conducted at a series of lakes in the Sierra Nevada ranging from Plumas County in the north to Tulare County in the south. During High Mountain Lake (HML) surveys, Sierra Nevada lentic waters were surveyed for fish, frogs, habitats, stream barriers to fish movement and presence of fairy shrimp. Lakes with fish were surveyed using monofilament gill nets. Amphibians were detected and documented based on direct observation. Contact Sarah Mussulman (916) 358-2838 for additional survey protocol detail and a description of methods. As part of the development of the biological data sets, researchers created a detailed coverage of lakes for (ostensibly) all known lentic water bodies in California above 5000’ elevation. Lake features were digitized from USGS 1:24000 quadrangles and assigned a unique identifying number. High Mountain Lakes (HML) surveys were performed in the Sierra Nevada starting in 2001 and use these unique ID numbers to reference waterbodies. WHAT EACH RECORD REPRESENTS: Each record represents a lake where CDFW has begun removing fish to benefit a population of mountain yellow-legged frogs. The majority of lakes in this dataset are currently fishless; a handful are active fish removal sites.</span></p></div></div></div>
Utility Solar Generation by Type and County: 2024

<p>Solar electrical generation data is reported for commercial power plants that<br />have a nameplate capacity of 1 MW or more. San Bernardino and Riverside<br />county had solar thermal in addition to solar photovoltaic electric generation.<br />Data originates from the California Energy Commission, and is classified using<br />the Jenk’s Natural Break’s method. Projection: NAD 1983 California (Teale)<br />Albers. Data is for 2024 and is current as of June 20, 2025. For more<br />information, contact John Hingtgen at john.hingtgen@energy.ca.gov.</p>
Vegetation - Santa Clara and Santa Cruz Counties [ds3116]

<div style='text-align:Left;'><div><div><p><span>Under contract to the Santa Cruz Mountains Stewardship Network with support from the Golden Gate National Parks Conservancy, and staffed by personnel from Tukman Geospatial, Aerial Information Systems (AIS), and Kass Green and Associates, Tukman Geospatial and Aerial Information Systems created a fine-scale vegetation map of portions of Santa Cruz and Santa Clara Counties. CDFW’s Vegetation Classification and Mapping Program (VegCAMP) provided in-kind service to allocate and score the AA. </span></p><p><span>The mapping study area, consists of approximately 1,133,106.8 acres, of Santa Clara and Santa Cruz counties. Work was performed on the project between 2020 and 2023. The Santa Cruz and Santa Clara fine-scale vegetation map was designed for a broad audience for use at many floristic and spatial scales and is useful to managers interested in specific information about vegetation composition and forest health. </span></p><p><span>CNPS under separate contract and in collaboration with CDFW VegCAMP developed the floristic vegetation classification used for the project. The floristic classification follows protocols compliant with the Federal Geographic Data Committee (FGDC) and National Vegetation Classification Standards (NVCS). </span></p><p><span>The vegetation map was produced with countywide vegetation survey data and combined with surveys from CNPS. Trimble® Ecognition® followed by manual image interpretation that was used to map lifeforms. Fine-scale segmentation was conducted using Trimble Ecognition® and relies on summer 2020 4-band NAIP, the 2020 lidar-derived canopy height model, and a suite of spectral indices derived from the NAIP. They utilized a type of algorithmic data modeling known as machine learning to automate the classification of fine-scale segments into one of Santa Cruz and Santa Clara Counties 121 fine-scale map classes.  The minimum mapping unit (MMU) is set by feature type. For agricultural classes, the MMU is 1/4 acre, for woody upland classes is 1/2 acre, woody riparian is 1/4 acre, upland herbaceous is 1/2 acre, wetland herbaceous is 1/4 acre. Bare land is 1/2 acre, impervious features is 1000 square feet, while developed is 1/5 acre and water is 400 square feet. </span></p><p><span>Field reconnaissance and accuracy assessment enhanced map quality. There was a total of 121 mapping classes. The overall Fuzzy Accuracy Assessment rating for the final vegetation map, map at the Alliance and Group levels, is 92 percent. More information can be found in the project report, which is bundled with the vegetation map published for BIOS here: </span><a href='https://filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/3100_3199/ds3116.zip' target='_blank' style='text-decoration:underline;' rel='nofollow ugc noopener noreferrer'><span>https://filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/3100_3199/ds3116.zip</span></a><span>.</span></p></div></div></div>
California Grants Portal Grant Awards 2022-2023

Per AB132 grantmakers are required to submit data about each awardee for grants that close on or after July 1, 2022. Visit the Glossary on https://www.grants.ca.gov/glossary to review post award data elements. You can view post award data at the bottom of the grant details page. Note that grantmakers may take up to one year to submit post award data. This grant award data is only for Fiscal Year 2022-2023.
CDEC Water Year Type Dataset

URL: https://data.cnra.ca.gov/dataset/8f7c9792-652a-4f5e-95ad-707961dfc3f5/resource/da64051a-7751-48e1-ab59-39c73a3ea52d/download/cdec-water-year-type-nov-2023.xlsx

Chronological Reconstructed Sacramento and San Joaquin Valley Water Year Hydrologic Classification Indices Based on measured unimpaired runoff (in million acre-feet), subject to revision.

For further description, see [https://cdec.water.ca.gov/reportapp/javareports?name=WSIHIST](https://cdec.water.ca.gov/reportapp/javareports?name=WSIHIST)
Environmental Monitoring Program: Discrete Water Quality Data

The Interagency Ecological Program’s (IEP) Environmental Monitoring Program (EMP) was initiated in compliance with the Water Right Decision D-1379 (now mandated by Water Right Decision D-1641) and has monitored discrete water quality and nutrients in the upper San Francisco Estuary since 1975. The objectives of the EMP are to obtain consistent and accurate monthly data at established monitoring stations, provide and document information necessary to achieve compliance with salinity, flow, and dissolved oxygen standards, and to report this information for the purpose of management and conservation of the upper San Francisco Estuary. While the EMP also collects biological data, this dataset only includes the discrete water quality and nutrient data collected by the EMP from 1975-2021. Links to other EMP datasets can be found [here](https://emp-dwr.github.io/emp-website/qmd-files/website/general/data-links.html).

Data is also accessible via the [Environmental Data Initiative](https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=458&revision=12).
2023 Crash Data on State Highway System

The Crash Data On California State Highways Report is produced annually by the California Department of Transportation (Caltrans) to provide high level summaries of road miles, travel, crashes and crash rates on the California State Highway System.

This table lists statewide vehicle travel expressed in Million Vehicle Miles (MVM), road miles, and one and three year crash rates and fatality rates based on lane types and population codes.

While crash rates for total crash and fatal + injury crashes are calculated per MVM, fatality rates are expressed per 100 MVM.
Chronic Wasting Disease Lined Landfills for Deer Carcass Disposal - CDFW [ds3156]

<div style='text-align:Left;'><div><div><p><span>This compilation of layers provides a comprehensive view of CWD-related activities, facilitating informed decision-making and strategic planning for wildlife management and disease prevention efforts. To date, there has not yet been any cases of CWD detected in California and surveillance data will be updated regularly. </span></p><p><span>This data is associated with the following layers: </span></p><ul><li><p><span>Chronic Wasting Disease Sampling Stations - 2025 - CDFW [ds3154] (</span><a href='https://apps.wildlife.ca.gov/bios6/?al=3154' target='_blank' style='text-decoration:underline;' rel='nofollow ugc noopener noreferrer'><span>https://apps.wildlife.ca.gov/bios6/?al=3154</span></a><span>), </span></p></li><li><p><span>Participating Meat Processors and Taxidermists - 2025 - CDFW [ds3155] (</span><a href='https://apps.wildlife.ca.gov/bios6/?al=3155' target='_blank' style='text-decoration:underline;' rel='nofollow ugc noopener noreferrer'><span>https://apps.wildlife.ca.gov/bios6/?al=315</span><span>5</span></a><span>),</span></p></li><li><p><span>Chronic Wasting Disease Sampling Stations - 2023-2024 - CDFW [ds3182] (</span><a href='https://apps.wildlife.ca.gov/bios6/?al=3182' target='_blank' style='text-decoration:underline;' rel='nofollow ugc noopener noreferrer'><span>https://apps.wildlife.ca.gov/bios6/?al=31</span><span>82</span></a><span>), </span></p></li><li><p><span>Participating Meat Processors and Taxidermists - 2023-2024 - CDFW [ds3188] (</span><a href='https://apps.wildlife.ca.gov/bios6/?al=3188' target='_blank' style='text-decoration:underline;' rel='nofollow ugc noopener noreferrer'><span>https://apps.wildlife.ca.gov/bios6/?al=31</span><span>88</span></a><span>), </span></p></li><li><p><span>Chronic Wasting Disease Surveillance - CDFW [ds3157] (</span><a href='https://apps.wildlife.ca.gov/bios6/?al=3157' target='_blank' style='text-decoration:underline;' rel='nofollow ugc noopener noreferrer'><span>https://apps.wildlife.ca.gov/bios6/?al=31</span><span>57</span></a><span>). </span></p></li></ul><p><span>These layers include CWD Testing Sites, Participating Meat Processors and Taxidermists (MPT), Carcass Disposal Sites, and comprehensive data on CWD surveillance spanning from 1999 to 2025. This compilation of layers provides a comprehensive view of CWD-related activities, facilitating informed decision-making and strategic planning for wildlife management and disease prevention efforts. For the latest information, please visit </span><a href='https://wildlife.ca.gov:443/CWD' style='text-decoration:underline;' rel='nofollow ugc'><span>https://wildlife.ca.gov/CWD</span></a><span>. </span></p></div></div></div>
California Electric Transmission Lines

<div><div>The California Energy Commission (CEC) Electric Transmission Line geospatial data layer has been created to illustrate electric transmission in California. When used in association with the other energy related geospatial data layers, viewers can analyze the geographic relationships with the electric transmission across the state.

The transmission line data is used to:<br /></div></div><div><br /></div><div>1. Support the CEC Transmission Planning; </div><div>2. Support the CEC electric system analysis in California;<br /></div><div>3. Enhance electric transmission communication among California electric stakeholders ;<br /></div><div>4. Support CEC's illustrations of electric infrastructure<br /></div><div><br /></div><div>Data Dictionary:</div><div><ul><li>Object ID: a unique, not null integer field used to uniquely identify rows in tables in a geodatabase.</li><li>Name: abbreviated transmission line owner and transmission line capacity in kilovolts (kV).</li><li>kV: transmission line capacity in kilovolts (kV), data structure is a text string.</li><li>kV (Sort): transmission line capacity in kilovolts (kV), data structure is a numeric double.</li><li>Owner: abbreviated transmission line owner name.</li><li>Status - last reported operational, proposed, closed, or unknown status of the transmission line.</li><li>Circuit - notes if the transmission line segment is a Single, double, or triple circuit. Null values are unknown. </li><li>Type - OH is overhead transmission lines, UG is underground, UW is underwater, null values are unknown.</li><li>Legend - a summarized categories of transmission line owner and transmission capacity value in kilowatts (kV) for map legend purposes.</li><li>Length (Mile) - the length of the transmission line segment in miles.</li><li>Length (Feet) - the length of the transmission line segment in feet.</li><li>TLine Name - the name of the transmission line segment reported to the California Energy Commission</li><li>Source - the data source used by California Energy Commission.</li><li>Comments</li><li>Creator</li><li>Creator Date</li><li>Last Editor</li><li>Last Editor Date</li><li>GlobalID</li><li>Shape__Length</li><li>Shape</li></ul></div><div><br /></div>
Chronic Wasting Disease Participating Meat Processors and Taxidermists - 2025 - CDFW [ds3155]

<div style='text-align:Left;'><div><div><p><span>This data is associated with the following layers: </span></p><ul><li><p><span>Chronic Wasting Disease Sampling Stations - 2025 - CDFW [ds3154] (</span><a href='https://apps.wildlife.ca.gov/bios6/?al=3154' target='_blank' style='text-decoration:underline;' rel='nofollow ugc noopener noreferrer'><span>https://apps.wildlife.ca.gov/bios6/?al=3154</span></a><span>), </span></p></li><li><p><span>Chronic Wasting Disease Sampling Stations - 2023-2024 - CDFW [ds3182] (</span><a href='https://apps.wildlife.ca.gov/bios6/?al=3182' target='_blank' style='text-decoration:underline;' rel='nofollow ugc noopener noreferrer'><span>https://apps.wildlife.ca.gov/bios6/?al=31</span><span>82</span></a><span>), </span></p></li><li><p><span>Participating Meat Processors and Taxidermists - 2023-2024 - CDFW [ds3188] (</span><a href='https://apps.wildlife.ca.gov/bios6/?al=3188' target='_blank' style='text-decoration:underline;' rel='nofollow ugc noopener noreferrer'><span>https://apps.wildlife.ca.gov/bios6/?al=31</span><span>88</span></a><span>), </span></p></li><li><p><span>Approved Deer Carcass Disposal Sites - CDFW [ds3156] (</span><a href='https://apps.wildlife.ca.gov:443/bios6/?al=3156' style='text-decoration:underline;' rel='nofollow ugc'><span>https://apps.wildlife.ca.gov/bios6/?al=3156</span></a><span>), </span></p></li><li><p><span>Chronic Wasting Disease Surveys - CDFW [ds3157] (</span><a href='https://apps.wildlife.ca.gov:443/bios6/?al=3157' style='text-decoration:underline;' rel='nofollow ugc'><span>https://apps.wildlife.ca.gov/bios6/?al=3157</span></a><span>). </span></p></li></ul><p><span>These layers include CWD Testing Sites, Participating Meat Processors and Taxidermists (MPT), Carcass Disposal Sites, and comprehensive data on CWD surveillance spanning from 1999 to 2025. This compilation of layers provides a comprehensive view of CWD-related activities, facilitating informed decision-making and strategic planning for wildlife management and disease prevention efforts. For the latest information, please visit </span><a href='https://wildlife.ca.gov:443/CWD' style='text-decoration:underline;' rel='nofollow ugc'><span>https://wildlife.ca.gov/CWD</span></a><span>. </span></p></div></div></div>
Occupational Employment and Wage Statistics (OEWS)

The Occupational Employment and Wage Statistics (OEWS) Survey is a federal-state cooperative program between the Bureau of Labor Statistics (BLS) and State Workforce Agencies (SWAs). The BLS provides the procedures and technical support, draws the sample, and produces the survey materials, while the SWAs collect the data. SWAs from all fifty states, plus the District of Columbia, Puerto Rico, Guam, and the Virgin Islands participate in the survey. Occupational employment and wage rate estimates at the national level are produced by BLS using data from the fifty states and the District of Columbia. Employers who respond to states' requests to participate in the OEWS survey make these estimates possible.

The OEWS survey collects data from a sample of establishments and calculates employment and wage estimates by occupation, industry, and geographic area. The semiannual survey covers all non-farm industries. Data are collected by the Employment Development Department in cooperation with the Bureau of Labor Statistics, US Department of Labor. The OEWS Program estimates employment and wages for approximately 830 occupations. It also produces employment and wage estimates for statewide, Metropolitan Statistical Areas (MSAs), and Balance of State areas. Estimates are a snapshot in time and should not be used as a time series.

The OEWS estimates are published annually.

__SOURCE: https://www.bls.gov/oes/oes_emp.htm__