cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30759005
title: Prediction files for mace-osaka24-large (Matbench Discovery)

description: This dataset contains the prediction files for the <b>mace-osaka24-large</b> model submitted to Matbench Discovery.<br>Included files:Phonon κ_103 prediction fileIS2RE-SR geometry optimization prediction files (symprec=1e-2, 1e-5)Discovery task prediction fileThese files are used solely for benchmark reproducibility.License: MIT<br>Model repository: https://github.com/qiqb-osaka/mace-osaka24
DOI: 10.6084/m9.figshare.30759005.v1
title: Prediction files for mace-osaka24-large (Matbench Discovery)

description: This dataset contains the prediction files for the <b>mace-osaka24-large</b> model submitted to Matbench Discovery.<br>Included files:Phonon κ_103 prediction fileIS2RE-SR geometry optimization prediction files (symprec=1e-2, 1e-5)Discovery task prediction fileThese files are used solely for benchmark reproducibility.License: MIT<br>Model repository: https://github.com/qiqb-osaka/mace-osaka24
DOI: 10.5281/zenodo.17785101
title: Reconstructed proton charge structure via selective flattening: Insights from Patterson function analysis

description: This dataset contains reconstructed proton charge structure data derived from Patterson function analysis. It includes processed form factors and charge density distributions based on selective flattening second image. The files support findings presented in the associated preprint and are intended for use in nuclear physics research
DOI: 10.15468/dl.dmfn9z
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Astragalus arpilobus"
 ]
}

 The dataset includes 26 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021576-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k2j4t5
title: Occurrence Download

description: A dataset containing 3027 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Haiti",
 "OccurrenceStatus is Present",
 "TaxonKey is Asteraceae"
 ]
}

 The dataset includes 3027 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021577-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2vgdu5
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material sample)",
 "OccurrenceStatus is Present",
 "TaxonKey is Micrurus steindachneri"
 ]
}

 The dataset includes 43 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021579-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4jje9u
title: Occurrence Download

description: A dataset containing 11478 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation)",
 "Continent is Asia",
 "Country is China",
 "OccurrenceStatus is Present",
 "StateProvince is Shanxi",
 "TaxonKey is Animalia",
 "Year 2012-2023"
 ]
}

 The dataset includes 11478 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021578-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17785024
title: Geomorphic zoning data of Zhongba County

description: Geomorphic zoning data of Zhongba County
DOI: 10.5281/zenodo.17785025
title: Geomorphic zoning data of Zhongba County

description: Geomorphic zoning data of Zhongba County
DOI: 10.15468/dl.5y3z9w
title: Occurrence Download

description: A dataset containing 5442 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-74.80782 9.88356,-74.87786 9.86216,-74.86035 9.78822,-74.84284 9.74445,-74.81074 9.63938,-74.79323 9.58879,-74.83895 9.53918,-74.80685 9.48372,-74.83895 9.438,-74.64244 9.47205,-74.57531 9.57225,-74.61617 9.7892,-74.80782 9.88356))",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 5442 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021580-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17775273
title: Dataset Used in the ARDL Analysis of China's FDI in Brazil's Energy Sector (2005–2024)

description: This dataset contains the quarterly time-series variables used in the study “China’s FDI in the Energy Sector of Brazil and Economic Growth: ARDL Analysis” between 2005 and 2024. It includes GDP growth computed as the quarterly percentage change in Brazil’s real GDP index (non-seasonally adjusted). FDI denotes inflows from China to Brazil’s energy sector expressed as a percentage of nominal GDP. Gross capital formation (GCF) is measured as the ratio of nominal GCF to nominal GDP. Inflation (INF) is captured by the consumer price index (CPI). Labor (L) refers to the economically active population aged above 15 years, encompassing employed and unemployed persons actively engaged in or seeking productive activity. The data for GDP, gross capital formation, and inflation were obtained from the Institute for Applied Economic Research (IPEA) and the Brazilian Institute of Geography and Statistics (IBGE). Chinese FDI data were sourced from the China Global Investment Tracker (AEI). The exchange rate was collected from the International Monetary Fund (IMF), and labor data was obtained from the World Bank’s World Development Indicators. All variables were cleaned, harmonized, and transformed to ensure consistency for econometric analysis. This dataset supports reproducibility of the ARDL bounds testing and ECM-based Granger causality results reported in the associated manuscript.
DOI: 10.5281/zenodo.17775274
title: Dataset Used in the ARDL Analysis of China's FDI in Brazil's Energy Sector (2005–2024)

description: This dataset contains the quarterly time-series variables used in the study “China’s FDI in the Energy Sector of Brazil and Economic Growth: ARDL Analysis” between 2005 and 2024. It includes GDP growth computed as the quarterly percentage change in Brazil’s real GDP index (non-seasonally adjusted). FDI denotes inflows from China to Brazil’s energy sector expressed as a percentage of nominal GDP. Gross capital formation (GCF) is measured as the ratio of nominal GCF to nominal GDP. Inflation (INF) is captured by the consumer price index (CPI). Labor (L) refers to the economically active population aged above 15 years, encompassing employed and unemployed persons actively engaged in or seeking productive activity. The data for GDP, gross capital formation, and inflation were obtained from the Institute for Applied Economic Research (IPEA) and the Brazilian Institute of Geography and Statistics (IBGE). Chinese FDI data were sourced from the China Global Investment Tracker (AEI). The exchange rate was collected from the International Monetary Fund (IMF), and labor data was obtained from the World Bank’s World Development Indicators. All variables were cleaned, harmonized, and transformed to ensure consistency for econometric analysis. This dataset supports reproducibility of the ARDL bounds testing and ECM-based Granger causality results reported in the associated manuscript.
DOI: 10.15468/dl.6pubu9
title: Occurrence Download

description: A dataset containing 2349 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is adaeb73b-8f3b-433c-ab2e-a8ca68a7c7ea",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 2349 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021581-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pxqkvg
title: Occurrence Download

description: A dataset containing 816527 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "not" : {
 "PublishingCountry" : [
 "is Norway"
 ]
 }
 },
 "Country is Svalbard and Jan Mayen",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is null",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
 },
 {
 "not" : {
 "DatasetKey" : [
 "is EBCC Atlas of European Breeding Birds"
 ]
 }
 },
 {
 "not" : {
 "DatasetKey" : [
 "is (Table 3) Relative abundance of Azolla spp., peridinoid dinocysts, gonyaulacoid dinocysts, non-saccate pollen, bisaccate pollen and spores from the Lomonosov Ridge during different Arctic coring expeditions"
 ]
 }
 }
 ]
}

 The dataset includes 816527 records from 834 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021559-251120083545085/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.13147324
title: QMOF Database

description: This repository hosts the Quantum MOF (QMOF) Database. See the corresponding documentation for information on how to download other files and data.If you use or wish to cite the QMOF Database, please refer to the following publications. Both should be cited if you are using the dataset with 20k+ structures.A.S. Rosen, S.M. Iyer, D. Ray, Z. Yao, A. Aspuru-Guzik, L. Gagliardi, J.M. Notestein, R.Q. Snurr. "Machine Learning the Quantum-Chemical Properties of Metal–Organic Frameworks for Accelerated Materials Discovery", <i>Matter</i>, <b>4</b>, 1578-1597 (2021).A.S. Rosen, V. Fung, P. Huck, C.T. O'Donnell, M.K. Horton, D.G. Truhlar, K.A. Persson, J.M. Notestein, R.Q. Snurr. "High-Throughput Predictions of Metal–Organic Framework Electronic Properties: Theoretical Challenges, Graph Neural Networks, and Data Exploration," <i>npj Comput. Mat.</i>, <b>8</b>, 195 (2022).<br>
DOI: 10.6084/m9.figshare.13147324.v18
title: QMOF Database

description: This repository hosts the Quantum MOF (QMOF) Database. See the corresponding documentation for information on how to download other files and data.If you use or wish to cite the QMOF Database, please refer to the following publications. Both should be cited if you are using the dataset with 20k+ structures.A.S. Rosen, S.M. Iyer, D. Ray, Z. Yao, A. Aspuru-Guzik, L. Gagliardi, J.M. Notestein, R.Q. Snurr. "Machine Learning the Quantum-Chemical Properties of Metal–Organic Frameworks for Accelerated Materials Discovery", <i>Matter</i>, <b>4</b>, 1578-1597 (2021).A.S. Rosen, V. Fung, P. Huck, C.T. O'Donnell, M.K. Horton, D.G. Truhlar, K.A. Persson, J.M. Notestein, R.Q. Snurr. "High-Throughput Predictions of Metal–Organic Framework Electronic Properties: Theoretical Challenges, Graph Neural Networks, and Data Exploration," <i>npj Comput. Mat.</i>, <b>8</b>, 195 (2022).<br>
DOI: 10.6084/m9.figshare.13147324.v17
title: QMOF Database

description: This repository hosts the Quantum MOF (QMOF) database. See the corresponding documentation for information on how to download other files and data.If you use or wish to cite the QMOF Database, please refer to the following publications:A.S. Rosen, S.M. Iyer, D. Ray, Z. Yao, A. Aspuru-Guzik, L. Gagliardi, J.M. Notestein, R.Q. Snurr. "Machine Learning the Quantum-Chemical Properties of Metal–Organic Frameworks for Accelerated Materials Discovery", <i>Matter</i>, <b>4</b>, 1578-1597 (2021). DOI: <sub>10.1016/j.matt.2021.02.015</sub>.A.S. Rosen, V. Fung, P. Huck, C.T. O'Donnell, M.K. Horton, D.G. Truhlar, K.A. Persson, J.M. Notestein, R.Q. Snurr. "High-Throughput Predictions of Metal–Organic Framework Electronic Properties: Theoretical Challenges, Graph Neural Networks, and Data Exploration," <i>npj Comput. Mat.</i> (2022). DOI: <sub>10.1038/s41524-022-00796-6</sub>.
DOI: 10.6084/m9.figshare.30487016.v2
title: Extracted RNA quantity, quality and RIN value

description: Extracted blue, sky-blue and white <i>Clitoria ternatea </i>flower RNA quality, quantity and RIN values.
DOI: 10.34740/kaggle/dsv/13953351
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.nzu26z
title: Occurrence Download

description: A dataset containing 213040 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-11-06",
 "EventDate is less than or equal to 2025-12-06",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 },
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 213040 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021574-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qep62s
title: Occurrence Download

description: A dataset containing 278 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Bolitoglossa alberchi"
 ]
}

 The dataset includes 278 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021582-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17605/osf.io/7ef5h
title: 2.1: Systematic scoping review and evidence mapping on reproducibility measures
DOI: 10.15468/dl.aybq7e
title: Occurrence Download

description: A dataset containing 24729 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation)",
 "Continent is Asia",
 "Country is China",
 "OccurrenceStatus is Present",
 "StateProvince is Nei Mongol",
 "TaxonKey is Animalia",
 "Year 2012-2023"
 ]
}

 The dataset includes 24729 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021584-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.6881815
title: Retrieving API knowledge from Tutorials and Stack Overflow based on Natural Language Queries

description: The replication package of PLAN
DOI: 10.15468/dl.p92k2e
title: Occurrence Download

description: A dataset containing 80685607 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Artportalen",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 80685607 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021569-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17785191
title: Neutron powder diffraction data of Butane collected in 5 K steps between 5.3 - 134.5 K

description: Neutron powder diffraction data collected from a condensed sample of butane (C4H10) with the Wombat high-intensity neutron diffraction instrument located at the OPAL reactor, Sydney, Australia.  Data were collected at a wavelength of 2.422 Å.    

The files ending in .nx.hdf are raw data files conforming to the NeXus standard (see nexusformat.org). The files ending in .xye are three-column ASCII reduced data derived from the corresponding raw data NeXus file, with the columns being angle, intensity and standard uncertainty of that intensity. To obtain the reduced data from the raw data each pixel was multiplied by the corresponding value in the efficiency map contained in file ‘eff_2025_06_12.gumtree.hdf’ after which all pixels at each angle were summed vertically and the final values output. As the sample contained a strong incoherent scatterer (hydrogen), additional steps were taken in data collection/reduction to alleviate the high background – known as gain re-refinement.  For each temperature 8 frames of data were collected by stepping the detector by the pixel spacing, 0.125◦, which resulting in multiple measurements of the same signal at each angle after vertical summation. Scale factors for each column of vertical pixels are then refined using the procedure of Ford and Rollett (DOI 10.1107/s0567740868002190).  This has been implemented on the Wombat instrument using the same underlying code described the Echidna instrument (DOI 10.1107/S1600576718014048), which should be referred to for details of the mathematics involved for this gain re-refinement.  The detector/x_pixel_angular_offset raw data file entry gives the angular boundaries of each detector pixel. These values were used to derive pixel centres, which were then added to sample/azimuthal_angle to give the final angular values found in the reduced data file.

Neutron powder diffraction data was collected in targeted 5 K steps, with the sample allowed to equilibrate after each temperature change.  Please note the set temperatures recorded in the file names do not reflect the measured sample temperature – this can be extracted from each raw data file at the sample/tc2/sensor/sensorValueA data entry.  (For instance reduced data file WBT0104338_C4H10_5_K.xye was collected at a measured temperature of 5.3 K)
DOI: 10.5281/zenodo.17785190
title: Neutron powder diffraction data of Butane collected in 5 K steps between 5.3 - 134.5 K

description: Neutron powder diffraction data collected from a condensed sample of butane (C4H10) with the Wombat high-intensity neutron diffraction instrument located at the OPAL reactor, Sydney, Australia.  Data were collected at a wavelength of 2.422 Å.    

The files ending in .nx.hdf are raw data files conforming to the NeXus standard (see nexusformat.org). The files ending in .xye are three-column ASCII reduced data derived from the corresponding raw data NeXus file, with the columns being angle, intensity and standard uncertainty of that intensity. To obtain the reduced data from the raw data each pixel was multiplied by the corresponding value in the efficiency map contained in file ‘eff_2025_06_12.gumtree.hdf’ after which all pixels at each angle were summed vertically and the final values output. As the sample contained a strong incoherent scatterer (hydrogen), additional steps were taken in data collection/reduction to alleviate the high background – known as gain re-refinement.  For each temperature 8 frames of data were collected by stepping the detector by the pixel spacing, 0.125◦, which resulting in multiple measurements of the same signal at each angle after vertical summation. Scale factors for each column of vertical pixels are then refined using the procedure of Ford and Rollett (DOI 10.1107/s0567740868002190).  This has been implemented on the Wombat instrument using the same underlying code described the Echidna instrument (DOI 10.1107/S1600576718014048), which should be referred to for details of the mathematics involved for this gain re-refinement.  The detector/x_pixel_angular_offset raw data file entry gives the angular boundaries of each detector pixel. These values were used to derive pixel centres, which were then added to sample/azimuthal_angle to give the final angular values found in the reduced data file.

Neutron powder diffraction data was collected in targeted 5 K steps, with the sample allowed to equilibrate after each temperature change.  Please note the set temperatures recorded in the file names do not reflect the measured sample temperature – this can be extracted from each raw data file at the sample/tc2/sensor/sensorValueA data entry.  (For instance reduced data file WBT0104338_C4H10_5_K.xye was collected at a measured temperature of 5.3 K)
DOI: 10.15468/dl.5kve58
title: Occurrence Download

description: A dataset containing 49990 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation)",
 "Continent is Asia",
 "Country is China",
 "OccurrenceStatus is Present",
 "StateProvince is Liaoning",
 "TaxonKey is Animalia",
 "Year 2012-2023"
 ]
}

 The dataset includes 49990 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021585-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/examiner-c44-13082
title: Train wreck (Valley Boulevard), 1951

description: 14 images. Train wreck (Valley Boulevard), July 15, 1951. General views, etc.
DOI: 10.25549/examiner-c44-45137
title: Union Oil pumpkin...Halloween decoration, 1952

description: 4 images. Union Oil pumpkin...Halloween decoration, 29 October 1952. Storage tank which holds 80,000 barrels of gasoline painted and decorated for Halloween.
DOI: 10.25549/examiner-c44-45998
title: Sea moss found at surfside, 1955

description: 5 images. Sea moss found at surfside, 19 October 1955. Denise Kroening - 4 years (with 'Sea moss'); Strange sea moss identified as polyzoa and also bryozoa.; Caption slip reads: "Photographer: Emery. Date: 1953-10-19. Reporter: Emery to RW. Assignment: "Moss animals" vs. Surfside. 95: Denise Kroening, 4 years, scoops handful of mysterious 'sea moss' from huge drift left by sea in front of her beach home at 101B Surfside at Surfside Colony, near Seal Beach. 26-27: Closeup of handful of strange 'moss' identified by marine biologists of Dpt. of Fish & Game as Bryozoa, known also as Polyzoa, 'moss animals' of the sea which could build colonies in glass houses. 24: Enlarged closeup of branching colony.44: Budding ends of a colony with pin for comparison."