AndreaBozzo/ceres-open-data-index huggingface dataset:
2000 National and State Estimations Civil Rights Data Collection

These files are state and national projections for the Civil Rights Data Collection. 
            The 2000 projections are based on the 14,716 public school districts and 88,882 schools 
            in these school districts that responded to the 2000 survey of all the nation's school 
            districts.  The state and national estimations were prepared for OCR in accordance with 
            statistical methodology for the Civil Rights data collection. Documentation is available
            from OCR which describes the procedures used for the estimations, including weighting 
            of the sample, imputation for item non-response, standard errors, and quality control 
            procedures. In addition, documentation is available from OCR for estimations that 
            should be used with caution due to large statistical uncertainty in the estimate, 
            including factors which contributed to the extent of this statistical uncertainty 
            for the Civil Rights Data Collection. This hardcopy documentation, available upon 
            request, is contained in " Civil Rights Data Collection (CRDC) Estimations and 
            Documentation."

Tags: advanced-placement, advanced-placement-enrollment, disability-discrimination, discrimination, education-of-children-with-disabilities, elementary, elementary-and-secondary-education, enrollment-demographics, minority, ocr, schools, special-education, special-education-services
Organization: Department of Education
2004 National and State Estimations Civil Rights Data Collection

These files are state and national estimations for the  Civil Rights Data Collection. 
            The 2004 estimations are based on a rolling stratified sample of approximately 6,000 districts 
            and 60,000 schools, and on reported data from those districts that responded to the survey. 
            Documentation is available from OCR which describes the procedures used for the estimations, 
            including weighting of the sample, imputation for item non-response, standard errors, and 
            quality control procedures. In addition, documentation is available from OCR for estimations 
            that should be used with caution due to large statistical uncertainty in the estimate, including 
            factors which contributed to the extent of this statistical uncertainty for the Civil Rights Data 
            Collection. This hardcopy documentation, available upon request, is contained in "Civil Rights 
            Data Collection (CRDC) Estimations and Documentation."

Tags: advanced-placement-enrollment, civil-rights, crdc, discrimination, education-of-students-with-disabilities, enrollment-demographics, gifted-and-talented-programs, ocr, school-counselors, sex-discrimination, special-education, student-discipline, students
Organization: Department of Education
2009-10 National and State Estimations Civil Rights Data Collection

These files are state and national estimations for the Civil Rights Data Collection. The 2009-10 estimations are based 
            on a rolling stratified sample of approximately 7,000 districts and 72,000 schools, and on reported data from those 
            districts that responded to the survey.

Tags: civil-rights, crdc, ocr
Organization: Department of Education
2006 National and State Estimations Civil Rights Data Collection

These files are state and national estimations for the Civil Rights Data Collection. 
            The 2006 estimations are based on a rolling stratified sample of approximately 6,000 districts 
            and 60,000 schools, and on reported data from those districts that responded to the survey. 
            Documentation is available from OCR which describes the procedures used for the estimations, 
            including weighting of the sample, imputation for item non-response, standard errors, and 
            quality control procedures. In addition, documentation is available from OCR for estimations 
            that should be used with caution due to large statistical uncertainty in the estimate, 
            including factors which contributed to the extent of this statistical uncertainty for the 
            Civil Rights Data Collection. This hardcopy documentation, available upon request, is 
            contained in "Civil Rights Data Collection (CRDC) Estimations and Documentation."

Tags: civil-rights, crdc, ocr
Organization: Department of Education
ESEA Title I LEA allocations - FY 2003

Tables (in PDF and EXCEL formats) showing FY 2003 ESEA Title I LEA Allocations, as well as estimated amounts available for choice-related transportation and supplemental educational services.

Tags: compensatory-education, federal-aid, federal-legislation, federal-programs, ofo, parental-choice, school-districts, state-departments-of-education, supplemental-educational-serices
Organization: Department of Education
Wind and Structural Loads on Parabolic Trough Solar Collectors at Nevada Solar One

Wind loading is a main contributor to structural design costs of Concentrating Solar Power (CSP) collectors, such as heliostats and parabolic troughs. These structures must resist the mechanical forces generated by turbulent wind. At the same time, the reflector surfaces must exhibit the necessary rigidity to maintain their optimal optical performance in windy conditions. 

Over two years, NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One (NSO) plant. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, we commissioned a lidar scanning the horizontal plane over the trough field.

This data set catalogs the high-resolution data set characterizing the complex flow field and resulting structural loads on parabolic trough collectors. By providing this first-of-its-kind data set to the CSP community, we aim to enhance the community's understanding of wind-loading experienced by CSP collector structures. This data set will also help design next-generation solar collectors and photovoltaic trackers.

Tags: concentrated-solar, csp, data, energy, flow-field, nevada-solar-one, optimal-optical-performance, parabolic-trough, power, processed-data, solar, solar-collector, solar-power, structural-design, structural-load, structural-loading, wind, wind-conditions, wind-impact, wind-load
Organization: Department of Energy
Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets

This dataset contains turbine- and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in Steady State (FLORIS) model, version 2.3.0. The 252,500 cases include 500 unique wind plants generated randomly by a specialized Plant Layout Generator (PLayGen) that samples randomized realizations of wind plant layouts from one of four canonical configurations: (i) cluster, (ii) single string, (iii) multiple string, (iv) parallel string. Other wind plant layout parameters were also randomly sampled, including the number of turbines (25-200) and the mean turbine spacing (3D-10D, where D denotes the turbine rotor diameter). For each layout, 500 different sets of atmospheric conditions were randomly sampled. These include wind speed in 0-25 m/s, wind direction in 0 deg.-360 deg., and turbulence intensity chosen from low (6%), medium (8%), and high (10%). For each atmospheric inflow scenario, the individual turbine yaw angles were randomly sampled from a one-sided truncated Gaussian on the interval 0 deg.-30 deg. oriented relative to wind inflow direction. 

This random data is supplemented with a collection of yaw-optimized samples where FLORIS was used to determine turbine yaw angles that maximize power production for the entire plant. To generate this data, a subset of cases were selected (50 atmospheric conditions from 50 layouts each for a total of additional 2,500 cases) for which FLORIS was re-run with wake steering control optimization. The IEA onshore reference turbine, which has a 130 m rotor diameter, a 110 m hub height, and a rated power capacity of 3.4 MW was used as the turbine for all simulations.

The simulations were performed using NREL's Eagle high performance computing system in February 2021 as part of the Spatial Analysis for Wind Technology Development project funded by the U.S. Department of Energy Wind Energy Technologies Office. The data was collected, reformatted, and preprocessed for this OEDI submission in May 2023 under the Foundational AI for Wind Energy project funded by the U.S. Department of Energy Wind Energy Technologies Office. This dataset is intended to serve as a benchmark against which new artificial intelligence (AI) or machine learning (ML) tools may be tested. Baseline AI/ML methods for analyzing this dataset have been implemented, and a link to their repository containing those models has been provided.

The .h5 data file structure can be found in the GitHub repository under explore_wind_plant_data_h5.ipynb.

Tags: ai, artificial-intelligence, benchmark, code, data, energy, floris, flow-redirection-and-induction-in-steady-state, gaussian-wake-model, machine-learning, ml, model, optimization, plant-level, power, power-production, processed-data, python, simulation, turbine-level, wake-steering, wakes, wind, wind-energy, wind-plant, wind-plant-layout, wind-power, wind-turbine, yaw-angle
Organization: Department of Energy
2022 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

These data provide the 2022 update of the Electricity Annual Technology Baseline (ATB). Starting in 2015 NREL has presented the ATB, consisting of detailed cost and performance data, both current and projected, for electricity generation and storage technologies. The ATB products now include data (Excel workbook, Tableau workbooks, and structured summary csv files), as well as documentation and user engagement via a website, presentation, and webinar. Starting in 2021, the data are cloud optimized and provided in the OEDI data lake. The data for 2015 - 2020 are can be found on the NREL Data Search Page. The website documentation can be found on the ATB Website.

Tags: battery-storage, capacity-factor, capital-expenditures, cost, csp-concentrating-solar-power, data, energy, fossil-energy, geothermal, hydropower, lcoe, levelized-cost-of-energy, operations-and-maintenance, overnight-capital-cost, performance, projection, pumped-storage-hydropower, pv-photovoltaic, renewable-energy, solar, technologies, united-states, wind
Organization: Department of Energy
BUTTER - Empirical Deep Learning Dataset

The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four learning rates, six minibatch sizes, four levels of label noise, and fourteen levels of L1 and L2 regularization each. Multiple repetitions (typically 30, sometimes 10) of each combination of hyperparameters were preformed, and statistics including training and test loss (using a 80% / 20% shuffled train-test split) are recorded at the end of each training epoch. In total, this dataset covers 178 thousand distinct hyperparameter settings ("experiments"), 3.55 million individual training runs (an average of 20 repetitions of each experiments), and a total of 13.3 billion training epochs (three thousand epochs were covered by most runs). Accumulating this dataset consumed 5,448.4 CPU core-years, 17.8 GPU-years, and 111.2 node-years.

Tags: batch-size, benchmark, deep-learning, depth, empirical, empirical-deep-learning, empirical-machine-learning, epoch, label-noise, learning-rate, machine-learning, minibatch-size, network-shape, network-topology, neural-architecture-search, neural-networks, regularization, shape, topology, training, training-epoch
Organization: Department of Energy
Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)

This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api and through PyPI (pip install NREL-dsgrid-legacy-efs-api). The data format is HDF5. The API is written in Python.

This initial dsgrid data set, whose description was originally published in 2018, covers electricity demand in the contiguous United States (CONUS) for the historical year of 2012. It is a proof-of-concept demonstrating the feasibility of reconciling bottom-up demand modeling results with top-down information about electricity demand to create a more detailed description than is possible with either type of data source on its own. The result is demand data that is more highly resolved along geographic, temporal, sectoral, and end-use dimensions as may be helpful for conducting electricity sector-wide "what-if" analysis of, e.g., energy efficiency, electrification, and/or demand flexibility. 

Although we conducted bottom-up versus top-down validation, the final residuals were significant, especially at higher geographic and temporal resolution. Please see the Executive Summary and/or Section 3 of the report to obtain an understanding of the data set limitations before deciding whether these data are suitable for any particular use case. 

New dsgrid datasets are under development. Please visit https://www.nrel.gov/analysis/dsgrid.html for the latest information which is also linked in the data resources.

Tags: analysis, contiguous-united-states, data, demand, demand-flexibility, demand-side, dsgrid, electrical, electricity, electricity-demand, electrification, electrification-futures-study, energy, grid, high-resolution, historial-year, load, model, modeled-data, power, processed-data, pypl, python, validation
Organization: Department of Energy
2021 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies

Starting in 2015 NREL has presented the Annual Technology Baseline (ATB) in an Excel workbook that contains detailed cost and performance data, both current and projected, for renewable and conventional technologies. The workbook includes a spreadsheet for each technology. This version of the workbook provides the final updates to data for the 2021 ATB. In 2019 and 2020, NREL has also provided selected data in Tableau workbooks and structured summary csv files. The data for 2015 - 2020 is located on https://data.nrel.gov. In 2021 and going forward, the data is cloud optimized and provided in the OEDI data lake. A website documents this and future data at https://atb.nrel.gov.

Tags: battery-storage, capacity-factor, capital-expenditures, cost, csp-concentrating-solar-power, data, energy, fossil-energy, geothermal, hydropower, lcoe, levelized-cost-of-energy, operations-and-maintenance, overnight-capital-cost, performance, projection, pumped-storage-hydropower, pv-photovoltaic-solar, renewable-energy, technologies, united-states, wind
Organization: Department of Energy
SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS

The SMART-DS datasets (Synthetic Models for Advanced, Realistic Testing: Distribution systems and Scenarios) are realistic large-scale U.S. electrical distribution models for testing advanced grid algorithms and technology analysis. This document provides a user guide for the datasets.

This dataset contains synthetic detailed electrical distribution network models, and connected timeseries loads for the greater San Francisco (SFO), Greensboro, and Austin areas. It is intended to provide researchers with very realistic and complete models that can be used for extensive powerflow simulations under a variety of scenarios. The data is synthetic, but has been validated against thousands of utility feeders to ensure statistical and operational similarity to electrical distribution networks in the US. 

The OpenDSS data is partitioned into several regions (each zipped separately). After unzipping these files, each region has a folder for each substation, and subsequent folders for each feeder within the substation. This allows users to simulate smaller sections of the full dataset. Each of these folders (region, substation and feeder) has a folder titled "analysis" which contains CSV files listing voltages and overloads throughout the network for the peak loading time in the year. It also contains .png files showing the loading of residential and commercial loads on the network for every day of the year, and daily breakdowns of loads for commercial building categories. Time series data is provided in the "profiles" folder including real and reactive power at 15 minute resolution along with parquet files in the "endues" folder with breakdowns of building end-uses. 

Tags: aus, big-data, distribution, distribution-system, electrical, electrical-network, energy, energy-systems-integration, grid, grid-modernization, gso, load-timeseries, opendss, parquet, power, powerflow, realistic, scenario, sfo, smart-ds, solar, solar-power, synthetic, system, testing
Organization: Department of Energy
AlphaBuilding - Synthetic Buildings Operation Dataset

This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years' historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants' diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls.

Tags: alphabuilding, building, efficiency, energy, energy-consumption, environmental, hvac, lighting, mel, miscellaneous-electric-loads, occupancy, simulation, synthetic, synthetic-data
Organization: Department of Energy
Housing and Segregation Study - Income Segregation (Gini Index)

Section 62 of Public Act 21-2, June Special Session, as modified by Section 71 of Public Act 23-204, required the Office of Policy and Management (OPM) to conduct a “Housing and Segregation Study”. This dataset is one of the products of the Housing and Segregation Study.

This dataset shows "Income Segregation (Gini Index)" for various Connecticut geographies.

Tags: gini-index, housing-and-segregation-study, income-segregation
Organization: State of Connecticut
Housing and Segregation Study - Race/Ethnicity Indices

Section 62 of Public Act 21-2, June Special Session, as modified by Section 71 of Public Act 23-204, required the Office of Policy and Management (OPM) to conduct a “Housing and Segregation Study”. This dataset is one of the products of the Housing and Segregation Study. 

This dataset shows "Matrices of Segregation" calculated for various Connecticut geographies (https://www.census.gov/topics/housing/housing-patterns/guidance/appendix-b.html)

Tags: census-matrices-of-segregation, ethnicity, housing-and-segregation-study, race, race-ethnicity
Organization: State of Connecticut
NOAA/WDS Paleoclimatology - Schweingruber - Khandiga River - PCOB - ITRDB RUSS057

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Russia, Eastern Europe. The time period coverage is from 221 to -41 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Tags: biological records, climate indicators, continent, density, doc/noaa/nesdis/ncei, earth science, eastern europe, europe, khandiga river, land records, latitude 62.47, longitude 137.75, material: null, national centers for environmental information, nesdis, noaa, norway spruce, paleoclimate, paleoclimate indicators, pcob, picea obovata ledeb. = picea abies (l.) h. karst. subsp. obovata (ledeb.) hultã©n, russia, siberian spruce, tree ring, tree rings, tree-ring, u.s. department of commerce, what: age, what: earlywood density, what: earlywood width, what: latewood density, what: latewood width, what: maximum density, what: minimum density, what: number of samples, what: tracheid diameter, what: tree ring standardized growth index, width
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
NOAA/WDS Paleoclimatology - Harley - Lilly-Dickey Woods - CYOV - ITRDB IN017

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Indiana, United States Of America. The time period coverage is from 74 to -63 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Tags: biological records, carya ovata (mill.) k. koch, climate indicators, continent, cyov, doc/noaa/nesdis/ncei, earth science, indiana, land records, latitude 39.2361, lilly-dickey woods, longitude -86.2204, material: null, national centers for environmental information, nesdis, noaa, north america, paleoclimate, paleoclimate indicators, shagbark hickory, tree ring, tree rings, tree-ring, u.s. department of commerce, united states of america, what: age, what: total ring width, width
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
NOAA/WDS Paleoclimatology - Fritts - Itasca State Park - PIRE - ITRDB MN019

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Minnesota, United States Of America. The time period coverage is from 278 to -21 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Tags: biological records, climate indicators, continent, doc/noaa/nesdis/ncei, earth science, itasca state park, land records, latitude 47.18, longitude -95.23, material: null, minnesota, national centers for environmental information, nesdis, noaa, north america, paleoclimate, paleoclimate indicators, pinus resinosa aiton, pire, red pine, tree ring, tree rings, tree-ring, u.s. department of commerce, united states of america, what: age, what: number of samples, what: total ring width, what: tree ring standardized growth index, width
Organization: National Oceanic and Atmospheric Administration, Department of Commerce