AndreaBozzo/ceres-open-data-index huggingface dataset:
Workforce Framework for Cybersecurity (NICE Framework) Components

NICE Framework components comprises Work Role Categories, Work Roles, Competency Areas, and Task, Knowledge, and Skill (TKS) statements as well as the relationships between those elements. The JSON file for the NICE Framework is a machine-readable format that can be used to transmit structured data from system to system.

Tags: competency, cybersecurity, cyberspace, education, knowledge, role, security, skill, task, team, training, work-role, workforce
Organization: National Institute of Standards and Technology
Model output associated with "Inter-comparison of Atmospheric Trace Gas Dispersion Models: Barnett Shale Case Study", Atmospheric Chemistry and Physics, 2019.

Please refer to the publication, particularly the information in the Supplementary Information, for details on the model configuration.Footprint files:Footprints generated every 30 seconds along flight paths using different models are archived as netCDF files.  Each tar.gz file contains all the netCDF footprints for a particular flight and model combination, and is named after the model combination and flight date (YYYYMMDD). For example the WRF-HYSPLIT combination for the flight on 10/19/2013 referenced in the paper is in:WRF-HYSPLIT/WRFHYS_Footprints_20131019.tar.gzMost flight footprints were run for 24 hours back in time but there are a few exceptions, so the files must be opened to see how far back the footprints go.  A few flights use shorter times, and on 10/28/2013 WRF-HYSPLIT was run for 36 hours.  The HYSPLIT footprint files are numbered consecutively in order of time.  The location and time of the receptor is in the NetCDF file itself, not in the filename.  The STILT filenames have location and time information but only to the nearest minute, so the numerical order in the filename indicates their time order, because there are two footprints each minute.  STILT and HYSPLIT footprints all also contain particle trajectories.  The receptor location and time is in the NetCDF file as origutctime, origlat, origlong, etc.The files include footprints from basic model runs referenced in Figures 4 and 7, that is NAMS-HYSPLIT, WRF-HYSPLIT, and WRF-STILT.  WRF-STILT for flights on 3/25, 3/27, 3/30 and 10/16 uses instantaneous wind output; WRF-STILT for 10/19, 10/20, 10/25, and 10/28 flights uses averaged wind fields (see the SI in the manuscript for details).  For WRF2-Flexpart footprints, please contact Wayne.Angevine@noaa.gov.  For CarbonTracker Lagrange WRF-STILT footprints, contact Arlyn.Andrews@noaa.gov. For WRF-LPDM footprints, contact Thomas Lauvaux (thomas.lauvaux@lsce.ipsl.fr).WRF-Chem output files:WRF-Chem output for 4 flights in October 2013 is also included here, both in native NetCDF format and in ARL format.  These contain 3-km resolution, hourly WRF-Chem output.  ARL files can be used to run HYSPLIT or STILT.  The NetCDF formatted files include the tracer variables for CH4 from both the EPA inventory (tracer_1 variable) and the EDF inventory used in the paper (tracer_2 variable).  The third tracer (tracer_3) is using the EPA inventory but masked so that emissions outside the domain of the EDF inventory are zero (so that they can be directly compared).  Only tracer_2 is used in the manuscript.  The NetCDF output files are combined into tar.gz files.  Please contact Thomas Lauvaux (thomas.lauvaux@lsce.ipsl.fr) for details regarding WRF-Chem.Observations:Observations from the Barnett flight campaign are made available by NOAA/ESRL, please contact Colm.Sweeney@noaa.gov.

Tags: barnett, dispersion, greenhouse-gas, hysplit, methane, wrf-chem
Organization: National Institute of Standards and Technology
2023 Cartographic Boundary File (KML), County Subdivision for Louisiana, 1:500,000

The 2023 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files.

County subdivisions are the primary divisions of counties and their equivalent entities for the reporting of Census Bureau data. They include legally-recognized minor civil divisions (MCDs) and statistical census county divisions (CCDs), and unorganized territories. In MCD states where no MCD exists or no MCD is defined, the Census Bureau creates statistical unorganized territories to complete coverage. The entire area of the United States, Puerto Rico, and the Island Areas are covered by county subdivisions.  

The generalized boundaries of legal MCDs are based on those as of January 1, 2023, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The generalized boundaries of all CCDs, delineated in 21 states, are based on those as reported as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

Tags: 2023, cartographic boundary, county, county subdivision, generalized, kml, la, louisiana
Organization: U.S. Census Bureau, Department of Commerce
CA Geographic Boundaries

<p>This dataset contains shapefile boundaries for CA State, counties and places from the US Census Bureau's 2023 MAF/TIGER database. Current geography in the 2023 TIGER/Line Shapefiles generally reflects the boundaries of governmental units in effect as of January 1, 2023.</p>

Tags: boundaries, boundary, california, counties, county, geography, geospatial, gis, map, maps, places, spatial, state
Organization: State of California
Water Quality - Effluent - Electronic Self-Monitoring Report (eSMR) Data

Wastewater discharges are regulated by the Water Board. Those regulated are generally required to submit Self-Monitoring Reports to the State or Regional Water Board. Some dischargers submit their reports through the electronic Self-Monitoring Report (eSMR) module of the California Integrated Water Quality System (CIWQS). Generally these are for discharges into surface waters regulated by an individual National Pollutant Discharge Elimination System (NPDES) permit, though other dischargers may be included in this dataset as well. This dataset are the monitoring results that have been submitted as data points after the submitters have been approved for electronic submittals (i.e. after the "all electronic date").

Note that this dataset does not include records where the sampling date falls outside of the years shown below. The excluded records include: records where the sampling date is missing, records where the sampling date is invalid (e.g., records with sampling dates in the future or unreasonably far in the past), and records for samples taken prior to year 2006. The excluded records represent approximately 0.1% of all records in the complete eSMR dataset.

Tags: effluent-data, monitoring-data, regulatory, self-monitoring-reports, water
Organization: State of California
2023 Cartographic Boundary File (KML), 118th Congressional Districts for West Virginia, 1:500,000

The 2023 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files.

Congressional districts are the 435 areas from which people are elected to the U.S. House of Representatives. After the apportionment of congressional seats among the states based on census population counts, each state is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The 118th Congress is seated from January 2023 through December 2024. In Connecticut, Illinois, and New Hampshire, the Redistricting Data Program (RDP) participant did not define the CDs to cover all of the state or state equivalent area. In these areas with no CDs defined, the code "ZZ" has been assigned, which is treated as a single CD for purposes of data presentation. The cartographic boundary files for the District of Columbia, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands) each contain a single record for the non-voting delegate district in these areas. The generalzied boundaries of all other congressional districts are based on information provided to the Census Bureau by the states by August 31, 2022.

Tags: 2023, cartographic boundary, congressional district, generalized, kml, west virginia, wv
Organization: U.S. Census Bureau, Department of Commerce
Fish Consumption Advisory Serving Recommendations

Summary of fish advisories that recommend how often you can safely eat fish caught from water bodies in California based on the level of chemical contaminants. Recommendations are provided as the number of servings per week. There are two sets of guidelines, one for women 18 to 49 years and children 1 to 17 years and another set for women 50 years and older and men 18 years and older. One serving is an 8-ounce fish fillet, or 8-ounces of meat, such as with shucked shellfish or multiple small fish, measured prior to cooking, which is roughly the size and thickness of your hand.

Tags: contaminant, ddts, dieldrin, fish, fish-advisory, mercury, oehha, pbdes, pcbs, pollutant, safe-eating-guidelines, selenium
Organization: State of California
COVID-19 Wastewater Surveillance Data. California

The California Department of Public Health (CDPH) and the California State Water Resources Control Board (SWRCB) together are coordinating with several wastewater utilities, local health departments, universities, and laboratories in California on wastewater surveillance for SARS-CoV-2, the virus causing COVID-19. Data collected from this network of participants, called the California Surveillance of Wastewater Systems (Cal-SuWers) Network, are submitted to the U.S. Centers for Disease Control and Prevention (CDC) National Wastewater Surveillance System (NWSS).

During the COVID-19 pandemic, it has been used for the detection and quantification of SARS-CoV-2 virus shed into wastewater via feces of infected persons. Wastewater surveillance tracks ""pooled samples"" that reflect the overall disease activity for a community serviced by the wastewater treatment plant (an area known as a ""sewershed""), rather than tracking samples from individual people. Notably, while SARS-CoV-2 virus is shed fecally by infected persons, COVID-19 is spread primarily through the respiratory route, and there is no evidence to date that exposure to treated or untreated wastewater has led to infection with COVID-19.   

Collecting and analyzing wastewater samples for the overall amount of SARS-CoV-2 viral particles present can help inform public health about the level of viral transmission within a community. Data from wastewater testing are not intended to replace existing COVID-19 surveillance systems, but are meant to complement them. While wastewater surveillance cannot determine the exact number of infected persons in the area being monitored, it can provide the overall trend of virus concentration within that community. With our local partners, the SWRCB and CDPH are currently monitoring and quantifying levels of SARS-CoV-2  at the headworks or ""influent"" of 21 wastewater treatment plants representing approximately 48% of California's population."

Tags: covid-19-wastewater-surveillance, national-wastewater-surveillance-data, sars-cov-2-wastewater-measurements, sewershed-surveillance-for-covid-19
Organization: State of California
Surplus Land Act Notices of Availability Received

Notices of Availability of surplus locally owned land and description of each site/parcel. Notices are submitted to HCD by local public agencies (includes cities, counties, special districts, and certain other entities) disposing of land as per AB1486, pursuant to Government Code Section 54221. Data is self-reported by the local public agency. HCD does not independently verify information reported by agencies in their Notices of Availability.

Tags: ab1486, affordable-housing-development, notices-of-availability, public-land, surplus-land, surplus-land-act
Organization: State of California
Surface Water - Freshwater Harmful Algal Blooms

Freshwater harmful algal bloom (HAB) data from the Freshwater Harmful Algal Bloom (FHAB) data system. The FHAB data system is the California State Water Resources Control Board's data system for data and information voluntarily reported to the agency. Bloom reports are voluntary reports submitted by the public or organization to identify a POTENTIAL HAB for evaluation. Bloom Reports may or may not include a report that is confirmed to be a HAB, regardless, all bloom reports are published. Due to the voluntary basis of information and data included in the database, data and information may include: waterbody name and location, potential algal bloom location and observed characteristics, observed field observations and/or analytical sampling results, waterbody and/or land management, general information, recommended advisory status (if any), and updates regarding bloom status. Refer to Data Dictionary and Data Disclaimer for additional information about this dataset. Please visit the Water Boards FHABS web site for more information and data visualizations https://mywaterquality.ca.gov/habs/index.html.

Tags: cyanobacteria, cyanotoxin, fhab, harmful-algal-bloom, impaired-waters
Organization: State of California
NAAG Tobacco Settlement Payments

1999-2024. National Association of Attorneys General (NAAG). Policy—Tobacco Settlement Payments. The National Association of Attorneys General (NAAG) provides Tobacco Settlement Revenue data for 46 states participating in the Master Settlement Agreement (MSA) with the four largest tobacco companies in the United States.  Data are reported on an annual basis.  Four states (Florida, Minnesota, Mississippi, and Texas) provide the STATE System their Tobacco Settlement Revenue data independently.

Tags: office-on-smoking-and-health, osh, policy, state-system, tobacco, tobacco-settlement-payments
Organization: U.S. Department of Health & Human Services
Data Description for Risk of Dementia Due to Co-Exposure to Air Pollution and Neighborhood Disadvantage

This dataset contains information on air pollution exposure, social determinants of health, dementia outcomes, and related confounders from the National Health and Aging Trends Study. This dataset is not publicly accessible because: This data was not produced by the EPA and is not owned by the EPA. It can be accessed through the following means: The data can be accessed by contacting the corresponding author listed in the manuscript. Format: The data is in tabular format with rows corresponding to observations and columns corresponding to outcomes, confounders, and exposures. 

This dataset is associated with the following publication:
Frndak, S., Z. Deng, C. Ward-Caviness, I. Gorski-Steiner, R. Thorpe, and A. Dickerson. Risk of Dementia Due to Co-Exposure to Air Pollution and Neighborhood Disadvantage.   ENVIRONMENTAL RESEARCH. Elsevier B.V., Amsterdam,  NETHERLANDS, 251(Part 2): 118709, (2024).

Tags: aging, air-pollution, dementia
Organization: U.S. Environmental Protection Agency
Smoot et al_Burn pit developmental data

Raw data for Smoot et al Burn pit manuscript. 

This dataset is associated with the following publication:
Smoot, J., S. Padilla, Y.H. Kim, D. Hunter, A. Tennant, B. Hill, M. Lowery, B. Knapp, W. Oshiro, M. Hazari, M. Hays, W. Preston, i. Jaspers, M. Gilmour, and A. Farraj. Burn pit-related smoke causes developmental and behavioral toxicity in zebrafish: Influence of material type and emissions chemistry.   Heliyon. Elsevier B.V., Amsterdam,  NETHERLANDS, 10(8): e29675, (2024).

Tags: air-pollution, behavior, burn-pit-smoke, developmental-toxicity, malformations, particulate-matter, wildland-fires, zebrafish
Organization: U.S. Environmental Protection Agency
Data for manuscript Neutralization of Ricin Toxin on Building Interior Surfaces Using Liquid Decontaminants

These are the raw data underlying the data presented in the manuscript. 

This dataset is associated with the following publication:
Richter, W., B. Weston, M. Sunderman, Z. Willenberg, K. Ratliff, and J. Wood. Neutralization of Ricin Toxin on Building Interior Surfaces using Liquid Decontaminants.   PLOS ONE. Public Library of Science, San Francisco, CA, USA, 19(5): e0302967, (2024).

Tags: contaminated-sites, decontamination, emergency-response, homeland-security, ricin
Organization: U.S. Environmental Protection Agency
FKastury JHazMat XAS and SEM data

Includes all data collected by the US EPA; X-ray absorption spectroscopy (XAS) data on the Lead L3-edge and the Arsenic K-edge and Scanning Electron Microscopy with paired energy dispersive X-ray spectroscopy (EDS) at select spots. 

This dataset is associated with the following publication:
Kastury, F., J. Basedin, A.R. Betts, R. Asamoah, C. Herde, P. Netherway, J. Tully, K.G. Scheckel, and A.L. Juhasz. Arsenic, cadmium, lead, antimony bioaccessibility and relative bioavailability in legacy gold mining waste.   JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 469: 133948, (2024).

Tags: arsenic-speciation, bioaccessibility, bioavailability, gold-mining, lead-speciation, relative-bioavailability, synchrotron-speciation
Organization: U.S. Environmental Protection Agency
A comparison of machine learning approaches for predicting hepatotoxicity potential using chemical structure and targeted transcriptomic data

Supplementary data for "Tia Tate, Grace Patlewicz, Imran Shah,
A comparison of machine learning approaches for predicting hepatotoxicity potential using chemical structure and targeted transcriptomic data, Computational Toxicology, Volume 29,  2024, 100301, ISSN 2468-1113, https://doi.org/10.1016/j.comtox.2024.100301.". 

This dataset is associated with the following publication:
Tate, T., G. Patlewicz, and I. Shah. A comparison of machine learning approaches for predicting hepatotoxicity potential using chemical structure and targeted transcriptomic data.   Computational Toxicology. Elsevier B.V., Amsterdam,  NETHERLANDS, 29: 100301, (2024).

Tags: genra, httr, machine-learning, toxrefdb
Organization: U.S. Environmental Protection Agency
EPA Dynamically Downscaled Ensemble (EDDE), Version 1

The EPA Dynamically Downscaled Ensemble (EDDE) datasets were prepared by EPA/ORD staff and by contract staff who worked under the technical guidance of EPA/ORD staff. The dataset here represents a subset of data that were dynamically downscaled by EPA from the fifth Coupled Model Intercomparison Project (CMIP5) using the Weather Research and Forecasting (WRF) model using the EPA High-End Scientific Computing platforms. Scenarios were downscaled from the Community Earth System Model (CESM) and the Geophysical Fluid Dynamics Laboratory (GFDL) Coupled Model version 3 (CM3). Simulations followed the historical periods 1975-2005 (CESM only) and 1995-2005 (both CESM and CM3), and Representative Concentration Pathways (RCP) 4.5 for 2025-2100 (CESM only), RCP6.0 for 2025-2055 (CESM only), and RCP8.5 for 2025-2100 (both CESM and CM3). The original downscaling was conducted during 2013-2018. Subsets of the original dataset were prepared using postprocessing software developed by EPA/ORD staff. This dataset is not publicly accessible because: Dataset is too large to be hosted in ScienceHub. It is ~5 terabytes. It can be accessed through the following means: Ideally, this dataset will be publicly accessible from the Cloud. Negotiations are underway to support that hosting venue. Format: Data are in Network Common Data Form (netCDF; https://unidata.ucar.edu/software/netcdf) version 4, which is commonly used and consumed by practitioners in the atmospheric modeling community. The EDDE data in netCDF are further written to adhere to principles of Climate and Forecasting System (CF) Compliance, as outlined at https://cfconventions.org. The files to be hosted are self-describing with metadata included in the netCDF header.

Tags: climate-change, dynamical-downscaling, extreme-weather, regional-climate, wrf
Organization: U.S. Environmental Protection Agency
Effects of Age and Exposure Duration on the Sensitivity of Early Life Stage Fathead Minnow (Pimephales promelas) to Waterborne Propranolol Exposure

Given that larval fish stages provide opportunities for development of stressor-selective screening level tests, this work aimed to investigate the optimal age of fathead minnow larva and duration of exposure for the pharmaceutical, propranolol, found in the environment. Differentially expressed genes were studied as well as gene set enrichment analysis. 

This dataset is associated with the following publication:
Biales, A., D. Bencic, R. Flick, and G. Toth. Effects of Age and Exposure Duration on the Sensitivity of Early Life Stage Fathead Minnow (Pimephales promelas) to Waterborne Propranolol Exposure.   ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 43(4): 807-820, (2024).

Tags: chemical-risk, development, fathead-minnow, gene-expression, propranolol
Organization: U.S. Environmental Protection Agency
Soybean microbiome response to CeO2 nanoparticles

16S amplicon sequencing data used to determine the changes in the soybean root-associated microbiome in response to cerium oxide nanoparticles (CeNPs) in a natural soil. Samples include low (1 ppm) and high (100 ppm) concentrations of CeNPs, as well as pristine and aged CeNP treatments. These treatments were designed to assess how environmentally relevant concentrations of CeNPs affect soybean growth, and whether aging CeNPs changes the biological response. The 60 total samples are comprised of 4 experimental replicates from each of the 5 treatments, with 3 spatial compartments (of varying proximity to the root surface). 

This dataset is associated with the following publication:
Reichman, J., M.R. Slattery, M.G. Johnson, C. Andersen, and S.L. Harper. CeO2 nanoparticle dose and exposure modulate soybean development and plant-mediated responses in root-associated bacterial communities.   Scientific Reports. Nature Publishing Group, London,  UK, 14: 10231, (2024).

Tags: ammonium-nitrate, engineered-nanomaterials-enms, intergenerational-effects, isotope, isotopic-discrimination, nitrogen
Organization: U.S. Environmental Protection Agency