cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14914471
title: Global Data Center Water Use and Scarcity Analysis

description:  

Repository Structure

 

Data Organization

Inputs



2_energy_and_water_use/: Contains reference data for energy and water calculations



Power plant databases: Data is from the WRI global power plant database version 1.30 (Byers et al., 2018; download [here]

Electricity grid maps: Power grid geojson from here

Climate zone data: Köppen climate zone 1991-2020 tif from Beck et al., 2023

Power plant water intensity: Based off of Jin et al., 2019

PUE and WUE scenario definitions: Derived from Lei & Masanet, 2022



3_water_scarcity: PCR-GLOBWB model outputs for water scarcity analysis, from Barbarossa et al., 2021





*Note*: inputs are not included in downloads due to their size (30 GB). The processed files are included in outputs/3_water_scarcity which can be used to run the water scarcity analysis



4_figures: Basin data for visualization, based on Pfafstetter watershed sub-basin level 5, from HydroBASINS

common: Country boundaries from Natural Earth Data


Outputs


0_webscraping: Raw data collected from data center directories


1_data_etl: Processed and cleaned data center information



Geocoded data center locations

Pre- and post-manual editing versions

Fuzzy matching results

Merging data sources

Multiple imputation scenarios (min, max, average, baseline) for Big Tech companies



2_energy_and_water_use: Calculated energy and water use of data centers globally



Imputed power capacity from floor area

Assigned power and water use efficiencies per data center 

Direct impact assessments

Assigned power grids to data centers

Indirect water use of data centers



3_water_scarcity: Water scarcity analysis results



Data center water extraction location mappings

PCR-GLOBWB extracted values for discharge and abstraction

Water scarcity summaries for different climate scenarios (1.5°C, 2.0°C, 3.2°C) at data center locations

Water scarcity increases from data-center-driven water use
DOI: 10.5281/zenodo.14914472
title: Global Data Center Water Use and Scarcity Analysis

description:  

Repository Structure

 

Data Organization

Inputs



2_energy_and_water_use/: Contains reference data for energy and water calculations



Power plant databases: Data is from the WRI global power plant database version 1.30 (Byers et al., 2018; download [here]

Electricity grid maps: Power grid geojson from here

Climate zone data: Köppen climate zone 1991-2020 tif from Beck et al., 2023

Power plant water intensity: Based off of Jin et al., 2019

PUE and WUE scenario definitions: Derived from Lei & Masanet, 2022



3_water_scarcity: PCR-GLOBWB model outputs for water scarcity analysis, from Barbarossa et al., 2021





*Note*: inputs are not included in downloads due to their size (30 GB). The processed files are included in outputs/3_water_scarcity which can be used to run the water scarcity analysis



4_figures: Basin data for visualization, based on Pfafstetter watershed sub-basin level 5, from HydroBASINS

common: Country boundaries from Natural Earth Data


Outputs


0_webscraping: Raw data collected from data center directories


1_data_etl: Processed and cleaned data center information



Geocoded data center locations

Pre- and post-manual editing versions

Fuzzy matching results

Merging data sources

Multiple imputation scenarios (min, max, average, baseline) for Big Tech companies



2_energy_and_water_use: Calculated energy and water use of data centers globally



Imputed power capacity from floor area

Assigned power and water use efficiencies per data center 

Direct impact assessments

Assigned power grids to data centers

Indirect water use of data centers



3_water_scarcity: Water scarcity analysis results



Data center water extraction location mappings

PCR-GLOBWB extracted values for discharge and abstraction

Water scarcity summaries for different climate scenarios (1.5°C, 2.0°C, 3.2°C) at data center locations

Water scarcity increases from data-center-driven water use
DOI: 10.5281/zenodo.14901302
title: Synth It Like KITTI: a CARLA Generated Dataset for the KITTI 3D Object Detection Benchmark
DOI: 10.5281/zenodo.14901303
title: Synth It Like KITTI: a CARLA Generated Dataset for the KITTI 3D Object Detection Benchmark
DOI: 10.34740/kaggle/dsv/10834806
title: BOS Kemdikbud
DOI: 10.15468/dl.dxjbyc
title: Occurrence Download

description: A dataset containing 810 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Notoryctes typhlops (Stirling, 1889)"
 ]
}

 The dataset includes 810 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002336-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w7ahb4
title: Occurrence Download

description: A dataset containing 342 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pteris vittata L."
 ]
}

 The dataset includes 342 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002337-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7fsrm9
title: Occurrence Download

description: A dataset containing 88569 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Canis latrans Say, 1823"
 ]
}

 The dataset includes 88569 records from 228 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002338-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pyf7w8
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Gentiana kirilowii Turcz."
 ]
}

 The dataset includes 16 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002339-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hshyck
title: Occurrence Download

description: A dataset containing 219937 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Belgium",
 "TaxonKey is one of (Aponogeton distachyos L.f., Arthurdendyus triangulatus (Dendy, 1895), Cabomba caroliniana A.Gray, Callosciurus finlaysonii (Horsfield, 1823), Cherax destructor Clark, 1936, Corvus splendens Vieillot, 1817, Crassula helmsii (Kirk) Cockayne, Elodea densa (Planch.) Casp., Eriocheir sinensis H.Milne Edwards, 1853, Erythranthe guttata (DC.) G.L.Nesom, Faxonius immunis (Hagen, 1870), Faxonius juvenilis (Hagen, 1870), Faxonius rusticus (Girard, 1852), Faxonius virilis (Hagen, 1870), Gambusia affinis (Baird & Girard, 1853), Heracleum mantegazzianum Sommier & Levier, Heracleum persicum Desf. ex Fisch., C.A.Mey. & Avé-Lall., Heracleum pubescens (Hoffm.) M.Bieb., Houttuynia cordata Thunb., Hydrocotyle ranunculoides L.f., Impatiens glandulifera Royle, Koenigia polystachya (Wall. ex Meisn.) T.M.Schust. & Reveal, Lagarosiphon major (Ridl.) Moss, Lepomis gibbosus (Linnaeus, 1758), Limnoperna fortunei (Dunker, 1857), Ludwigia grandiflora (Michx.) Greuter & Burdet, Ludwigia peploides (Kunth) P.H.Raven, Lysichiton americanus Hultén & H.St.John, Morone americana (Gmelin, 1789), Muntiacus reevesi (Ogilby, 1839), Myriophyllum aquaticum (Vell.) Verdc., Myriophyllum heterophyllum Michx., Pacifastacus leniusculus (Dana, 1852), Petasites japonicus (Siebold & Zucc.) Maxim., Pontederia cordata L., Procambarus acutus (Girard, 1852), Procambarus clarkii (Girard, 1852), Procambarus virginalis Lyko, 2017, Pseudorasbora parva (Temminck & Schlegel, 1846), Pycnonotus cafer (Linnaeus, 1766), Saururus cernuus L., Sciurus carolinensis Gmelin, 1788, Sciurus niger Linnaeus, 1758, Solenopsis invicta Buren, 1972, Solenopsis richteri Forel, 1909, Threskiornis aethiopicus (Latham, 1790), Vespa velutina Lepeletier, 1836, Zizania latifolia (Griseb.) Hance ex F.Muell.)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 219937 records from 82 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002334-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3jx729
title: Occurrence Download

description: A dataset containing 1095965 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Belgium, Germany, Netherlands)",
 "TaxonKey is one of (Ondatra zibethicus (Linnaeus, 1766), Myocastor coypus (Molina, 1782))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1095965 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002333-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28378643
title: Database: ''Daytime Sleepiness, Sleep Quality, and Sarcopenia in Elderly Individuals: Relationships with Falls"

description: The objective of this study was to analyze the correlation between excessive daytime sleepiness, sleep quality, handgrip strength, and falls in older adults with and without a risk for sarcopenia.
DOI: 10.15468/dl.t5a5pj
title: Occurrence Download

description: A dataset containing 345 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eleothreptus candicans (Pelzeln, 1867)"
 ]
}

 The dataset includes 345 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002340-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8g7pv9
title: Occurrence Download

description: A dataset containing 2295 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cebus capucinus (Linnaeus, 1758)"
 ]
}

 The dataset includes 2295 records from 117 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002341-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22002/p2tjg-kne66
title: Supplemental data to "Imaging Underwater Faults and Tracking Whales with Optical Fiber Sensing"

description: Noise correlations
Numpy array dimension = (250000 x 25001), where 250000 = 500 subarrays x 500 virtual sources, and 25001 = (-500, 500)s in 25Hz
DOI: 10.15468/dl.7zdpuf
title: Occurrence Download

description: A dataset containing 118 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Pakistan, India, Nepal)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Gentiana tianschanica Rupr., 1869"
 ]
}

 The dataset includes 118 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002342-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28466525.v1
title: Summary of key limitations of included studies

description: A summary of study-specific limitations and MMAT results (Hong et al., 2018) of the included studies from the Scoping review: "Interventions for burnout and well-being in homelessness staff: A systematic scoping review".This is also included in the Supporting Information of the original manuscript (S2 Table).
DOI: 10.6084/m9.figshare.28466525
title: Summary of key limitations of included studies

description: A summary of study-specific limitations and MMAT results (Hong et al., 2018) of the included studies from the Scoping review: "Interventions for burnout and well-being in homelessness staff: A systematic scoping review".This is also included in the Supporting Information of the original manuscript (S2 Table).
DOI: 10.6084/m9.figshare.28466519
title: MMAT quality appraisal results of included studies

description: Results of the quality assessment of the included studies from the scoping review, using the Mixed Methods Appraisal Tool (Hong et al., 2018). This file is also in the Supporting Information of the manuscript titled "S1 Table".<br>The full scoping review manuscript is titled: "Interventions for burnout and well-being in homelessness staff: A systematic scoping review".
DOI: 10.6084/m9.figshare.28466516.v2
title: Extracted data from included studies (Tables 3-5 in manuscript)

description: Tables 3 to 5, containing all the extracted data used in the scoping review: "Interventions for burnout and well-being in homelessness staff: A systematic scoping review"
DOI: 10.6084/m9.figshare.28466516.v1
title: Extracted data from included studies (Tables 3-5)

description: Tables 3 to 5, containing all the extracted data used in the scoping review: "Interventions for burnout and well-being in homelessness staff: A systematic scoping review"
DOI: 10.6084/m9.figshare.28466516
title: Extracted data from included studies (Tables 3-5 in manuscript)

description: Tables 3 to 5, containing all the extracted data used in the scoping review: "Interventions for burnout and well-being in homelessness staff: A systematic scoping review"
DOI: 10.5281/zenodo.14914863
title: Sea ice perturbations in aquaplanet simulations: Isolating the physical climate responses from model interventions

description: These files were used to force the icy-aquaplanet configuration of CESM2. If you use this model configuration, please cite the following paper: England, M. R., N. Feldl, and I. Eisenman (2024), Sea ice perturbations in aquaplanet simulations: Isolating the physical climate responses from model interventions, Environmental Research: Climate, doi:10.1088/2752-5295/ad9b45.

Follow detailed instructions at https://github.com/nfeldl/CESM-icy-aquaplanet
DOI: 10.5281/zenodo.14914864
title: Sea ice perturbations in aquaplanet simulations: Isolating the physical climate responses from model interventions

description: These files were used to force the icy-aquaplanet configuration of CESM2. If you use this model configuration, please cite the following paper: England, M. R., N. Feldl, and I. Eisenman (2024), Sea ice perturbations in aquaplanet simulations: Isolating the physical climate responses from model interventions, Environmental Research: Climate, doi:10.1088/2752-5295/ad9b45.

Follow detailed instructions at https://github.com/nfeldl/CESM-icy-aquaplanet
DOI: 10.5281/zenodo.14914934
title: GPT-4 Performance Analysis

description: Comprehensive performance metrics for GPT-4 model evaluation
DOI: 10.5281/zenodo.14914935
title: GPT-4 Performance Analysis

description: Comprehensive performance metrics for GPT-4 model evaluation
DOI: 10.15468/dl.9tb3fn
title: Occurrence Download

description: A dataset containing 160366 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Achillea millefolium L.",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 160366 records from 545 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002343-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3v6zvy
title: Occurrence Download

description: A dataset containing 41216 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Agrostis canina L.",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 41216 records from 200 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002345-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e220401
title: Trends in International Mathematics and Science Study (TIMSS) and Progress in International Reading Literacy Study (PIRLS)

description: Trends in International Mathematics and Science Study (TIMSS) from the National Center for Education Statistics and Progress in International Reading Literacy Study (PIRLS) from the National Center for Education Statistics (NCES). Includes all data formats available.<br><br>"Since 1995, TIMSS has monitored trends in mathematics and science achievement every four years, at the fourth and eighth grades. TIMSS 2023 is the eighth such assessment, providing nearly three decades of trend data. TIMSS 2023 completes the transition to a fully digital administration, concluding a process that began in TIMSS 2019, and features new and interactive item formats.TIMSS Advanced studies achievement in advanced mathematics and physics for students in their final year of secondary school. TIMSS Advanced was conducted in 1995, 2008, and 2015." <br><br>"PIRLS has monitored trends in reading achievement at the fourth grade every five years since 2001. PIRLS 2026, the sixth assessment cycle of PIRLS, will provide policymakers and researchers with data on 25 years of trends in student achievement in reading literacy.PIRLS 2026 completes the transition to a fully digital assessment, concluding a process that began with PIRLS 2021. ePIRLS, an innovative assessment of online informational reading, was introduced in 2016 as an optional component and is now integrated into the digital assessment."<br><br>
DOI: 10.3886/e220401v1
title: Trends in International Mathematics and Science Study (TIMSS) and Progress in International Reading Literacy Study (PIRLS)

description: Trends in International Mathematics and Science Study (TIMSS) from the National Center for Education Statistics and Progress in International Reading Literacy Study (PIRLS) from the National Center for Education Statistics (NCES). Includes all data formats available.<br><br>"Since 1995, TIMSS has monitored trends in mathematics and science achievement every four years, at the fourth and eighth grades. TIMSS 2023 is the eighth such assessment, providing nearly three decades of trend data. TIMSS 2023 completes the transition to a fully digital administration, concluding a process that began in TIMSS 2019, and features new and interactive item formats.TIMSS Advanced studies achievement in advanced mathematics and physics for students in their final year of secondary school. TIMSS Advanced was conducted in 1995, 2008, and 2015." <br><br>"PIRLS has monitored trends in reading achievement at the fourth grade every five years since 2001. PIRLS 2026, the sixth assessment cycle of PIRLS, will provide policymakers and researchers with data on 25 years of trends in student achievement in reading literacy.PIRLS 2026 completes the transition to a fully digital assessment, concluding a process that began with PIRLS 2021. ePIRLS, an innovative assessment of online informational reading, was introduced in 2016 as an optional component and is now integrated into the digital assessment."<br><br>
DOI: 10.5281/zenodo.14913166
title: Supplementary Soil Dataset for Enhancing River Flow Predictions in MOHID-Land Through Integration of Gridded Soil Data and Hydraulic Parameters Using the MOHID Soil Tool

description: This dataset contains raster data of key soil properties - clay, silt, sand, and bulk density - provided by the Brazilian Agricultural Research Corporation (EMBRAPA). Additionally, the dataset includes shapefiles representing soil types from EMBRAPA and a shapefile of the Pedro do Rio watershed boundary, specifically applied in the study. These data serve as input for the MOHID Soil Tool (MST), which automates the integration of these soil properties into the Rosetta model. The Rosetta model then calculates the hydraulic parameters of the Van Genuchten-Mualem model for each soil type and layer present in the watershed, enabling hydrological modeling with the MOHID-Land model.

The dataset is primally linked to the article: "Enhancing River Flow Predictions in MOHID-Land Through Integration of Gridded Soil Data and Hydraulic Parameters Using the MOHID Soil Tool". The MST input data are: "clay, silt, sand, and bulk density raster" for all depths; "EMBRAPA_Rio de Janeiro_High resolution_Soil type map"; "Pedro do Rio_Watershed delineation"; and "MOHID-Land_Topography". The result file include all results generated by MST based on article is also available.

Other papers related to the dataset include: "Enhancing Hydrological Modeling Accuracy: Integrating EMBRAPA Soil Texture Data with ROSETTA Model Input Parameters Using the MOHID Soil Tool", "Sensitivity Analysis of Soil Hydraulic Parameters for Improved Flow Predictions in an Atlantic Forest Watershed Using the MOHID-Land Platform", and "Assessing the Impact of Anisotropic Hydraulic Conductivity on Lateral Flow for Streamflow Predictions in a Representative Atlantic Forest Watershed".

The rasters in this dataset represent the spatial distributions of the aforementioned soil properties across Brazil, while the shapefiles define soil types and the boundaries of the Pedro do Rio watershed.

While this dataset includes specific shapefiles for the Pedro do Rio watershed, any other shapefile of soil types or watershed boundaries within Brazil can be used in conjunction with MST. The dataset is ideal for researchers involved in hydrological modeling, particularly those focused on the Brazilian context. However, the MST is also applicable to global studies utilizing raster-based soil datasets from other sources.

For more information on how to use this dataset and integrate it into the MOHID Soil Tool, refer to the https://github.com/dhiegosales/MOHID-SOIL-TOOL