cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17274163
title: CO2 Rise Directly Impairs Crop Nutritional Quality

description: This repository includes the files created and used in 'CO2 Rise Directly Impairs Crop Nutritional Quality'. Three additional files are uploaded as Supplementary Information and are not included here. They are:



'Data Sources' (pdf), which contains the full citation and DOI of the articles used to create the database (File 3)

'Supplementary Figures' (pdf) created by the python code (File 1).

'Appendix S2' (pdf), which explains how existing databases were used in the creation of File 3 to avoid double-counting.They are also available upon reasonable individual request.


The included files here are:



File 0: README.txt

File 1: CO2_Rise_Crop_Quality_SI_Code.py

File 2: CO2_Rise_Crop_Quality_SI_Code spec-file.txt

File 3: CO2_Rise_Crop_Quality_SI_Data_S1_Database.csv

File 4: CO2_Rise_Crop_Quality_SI_Data_S2_Database_Read Me.txt

File 5: CO2_Rise_Crop_Quality_SI_Data_S3_Results_for publication.csv

File 6: CO2_Rise_Crop_Quality_SI_Data_S4_Results_Read Me.txt


They relate to each other as follows:

File 0 contains a description of the files and how they relate to each other.File 1 is the Python code used to analyze the input database (File 3). It automatically produces all the figures and outputs to the console the numbers used in the manuscript. This code is maintained by 'topersist' on GitHub.Consult File 2 to clone the environment used when creating the script (File 1).File 3 is the input database and is associated with its readme (File 4), which explains the variable names and units.File 5 is the output of File 1 when run using File 3, and contains the results as used in the final figures for publication.File 6 is the associated readme, which explains the variable names and units.

This work has received funding from the European Union's Horizon 2020 Research and Innovation program under grant agreement no. 101003880. The sole responsibility for the content of this dataset lies with the authors.
DOI: 10.5281/zenodo.17274164
title: CO2 Rise Directly Impairs Crop Nutritional Quality

description: This repository includes the files created and used in 'CO2 Rise Directly Impairs Crop Nutritional Quality'. Three additional files are uploaded as Supplementary Information and are not included here. They are:



'Data Sources' (pdf), which contains the full citation and DOI of the articles used to create the database (File 3)

'Supplementary Figures' (pdf) created by the python code (File 1).

'Appendix S2' (pdf), which explains how existing databases were used in the creation of File 3 to avoid double-counting.They are also available upon reasonable individual request.


The included files here are:



File 0: README.txt

File 1: CO2_Rise_Crop_Quality_SI_Code.py

File 2: CO2_Rise_Crop_Quality_SI_Code spec-file.txt

File 3: CO2_Rise_Crop_Quality_SI_Data_S1_Database.csv

File 4: CO2_Rise_Crop_Quality_SI_Data_S2_Database_Read Me.txt

File 5: CO2_Rise_Crop_Quality_SI_Data_S3_Results_for publication.csv

File 6: CO2_Rise_Crop_Quality_SI_Data_S4_Results_Read Me.txt


They relate to each other as follows:

File 0 contains a description of the files and how they relate to each other.File 1 is the Python code used to analyze the input database (File 3). It automatically produces all the figures and outputs to the console the numbers used in the manuscript. This code is maintained by 'topersist' on GitHub.Consult File 2 to clone the environment used when creating the script (File 1).File 3 is the input database and is associated with its readme (File 4), which explains the variable names and units.File 5 is the output of File 1 when run using File 3, and contains the results as used in the final figures for publication.File 6 is the associated readme, which explains the variable names and units.

This work has received funding from the European Union's Horizon 2020 Research and Innovation program under grant agreement no. 101003880. The sole responsibility for the content of this dataset lies with the authors.
DOI: 10.5281/zenodo.17613247
title: "Q = T(L) : Quasar; Time; and Stability. The aspect of galaxy formation

description: This paper outlines the dynamics of Quasars, black holes, and the dynamics involved in Galaxy formation. 

The data used is across multiple black holes, what QGMF Cosmological model, calls: black spheres. 

Enjoy the read !
DOI: 10.5281/zenodo.17613248
title: "Q = T(L) : Quasar; Time; and Stability. The aspect of galaxy formation

description: This paper outlines the dynamics of Quasars, black holes, and the dynamics involved in Galaxy formation. 

The data used is across multiple black holes, what QGMF Cosmological model, calls: black spheres. 

Enjoy the read !
DOI: 10.15468/dl.wd3kzz
title: Occurrence Download

description: A dataset containing 1089 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 {
 "or" : [
 "Year is 2017",
 "Year is 2018",
 "Year is 2019",
 "Year is 2020",
 "Year is 2021",
 "Year is 2022",
 "Year is 2023",
 "Year is 2024",
 "Year is 2016",
 "Year is 2015"
 ]
 },
 "BasisOfRecord is one of (Human Observation, Material sample, Machine Observation)",
 "StateProvince is one of (Cundinamarca, Boyacá, Bogotá, D.C.)",
 "TaxonKey is one of (Dendropsophus molitor [GBIF Backbone Taxonomy])"
 ]
 }
 ]
}

 The dataset includes 1089 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034176-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.392esy
title: Occurrence Download

description: A dataset containing 33972033 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "StateProvince is British Columbia",
 "Year is greater than or equal to 1970",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "SpeciesKey is not null"
 ]
}

 The dataset includes 33972033 records from 535 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034150-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5yrb5s
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-108.2688 22.64913, -108.1188 22.64913, -108.1188 22.79913, -108.2688 22.79913, -108.2688 22.64913))"
 ]
}

 The dataset includes 11 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034177-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tghk2u
title: Occurrence Download

description: A dataset containing 8251 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lontra canadensis",
 "Year 1970-2020"
 ]
}

 The dataset includes 8251 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034178-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2nf6p0
title: CCDC 2455562: Experimental Crystal Structure Determination

description: Related Article: Subhadeep Ghosh, Sumit Biswas, Indrajit Das|2025|Chem.Commun.|61|17448|doi:10.1039/d5cc04237b
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2nfnxp
title: CCDC 2456003: Experimental Crystal Structure Determination

description: Related Article: Asik Hossain, Gregory C. Fu|2025|J.Am.Chem.Soc.|||doi:10.1021/jacs.5c14143
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2nj5x9
title: CCDC 2458421: Experimental Crystal Structure Determination

description: Related Article: Qi Zhang, Haitao Li, Zhenwei Guo, Hongguang Chen, Fang Guo|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c02919
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2nprrw
title: CCDC 2463779: Experimental Crystal Structure Determination

description: Related Article: Tamanna Rana, Amit B. Pawar|2025|J.Org.Chem.|||doi:10.1021/acs.joc.5c01865
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2nydwx
title: CCDC 2471130: Experimental Crystal Structure Determination

description: Related Article: Rong Zeng|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2p2j8l
title: CCDC 2475079: Experimental Crystal Structure Determination

description: Related Article: Jie Tan, Ling Li, Dong Liu, Ji-Yong Zou, Changjiang Xu, Shengyong You, Yu Xie|2026|J.Mol.Struct.|1352||doi:10.1016/j.molstruc.2025.144409
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2p2j9m
title: CCDC 2475080: Experimental Crystal Structure Determination

description: Related Article: Jie Tan, Ling Li, Dong Liu, Ji-Yong Zou, Changjiang Xu, Shengyong You, Yu Xie|2026|J.Mol.Struct.|1352||doi:10.1016/j.molstruc.2025.144409
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.edq8nk
title: Occurrence Download

description: A dataset containing 504 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-34.67162 23.76186,33.17105 23.76186,33.17105 50.92693,-34.67162 50.92693,-34.67162 23.76186))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Rana parvipalmata"
 ]
}

 The dataset includes 504 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034179-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.caz3w8
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-108.1188 22.64913, -107.9688 22.64913, -107.9688 22.79913, -108.1188 22.79913, -108.1188 22.64913))"
 ]
}

 The dataset includes 46 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034180-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17611839
title: Polygon Similarity Benchmark Dataset

description: Dataset Description: Polygon Similarity Benchmark Dataset

Overview

This dataset provides a curated collection of polygonal shapes derived from real-world geographic information system (GIS) layers, specifically Parks, Water Bodies, and Sports categories from the SpatialHadoop GIS dataset.It is intended to support research in polygon representation learning, geometric similarity search, and spatial indexing.

The dataset includes raw polygonal geometries, pre-computed similarity ground truth, and supplementary documentation. For each dataset category, 80% of the polygons were used to build the similarity index, while the remaining 20% were reserved exclusively for evaluation.

Dataset Contents

The distributed ZIP package contains the following files:

1. ShapeToVecResults2.pdf

A supplementary document containing additional experimental results and visualizations referenced in the related publication.

2. poly_data.zip

A collection of polygonal GIS datasets extracted from SpatialHadoop. These represent the input geometries used for similarity computation.

3. Ground Truth Files

These archives contain precomputed shape similarity results for each domain:





parks.tar




water_bodies.tar



Each ground-truth archive consists of multiple text files, where each line represents a similarity query result.

Ground Truth Format

Each line in a ground-truth file encodes:

<input_polygon_id> <similar_polygon_id_1> <similar_polygon_id_2> ... <similar_polygon_id_k>

 







The first value is the ID of the input polygon.




The subsequent values are the IDs of polygons determined to be most similar based on geometric shape similarity.




The list of similar polygons is sorted in decreasing order of similarity, with the most similar polygon appearing first.



These ground-truth lists were generated using geometric similarity metrics for evaluation and benchmarking of vector-based polygon encodings.

Intended Use

This dataset is primarily designed for:





Research on polygon representation learning, embedding models, and shape encoders.




Benchmarking approximate nearest-neighbor (ANN) algorithms on spatial shape data.




Studying spatial indexing, vector search strategies, and geometric similarity measures.




GIS analytics, spatial data mining, and machine learning applications involving polygonal geometries.
DOI: 10.15468/dl.f5dqv2
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-107.9688 22.64913, -107.8188 22.64913, -107.8188 22.79913, -107.9688 22.79913, -107.9688 22.64913))"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034181-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17609657
title: Subhourly meteorological data at reservoirs in the upper Genil basin (Canales, Quentar, Colomera and Bermejales) (TED2021-130744B-C22 STAGES).

description: This dataset includes meterological data from four weather stations installed next to the main reservoirs in the upper Genil basin, in south-eastern Spain, between 2023 and 2025. This table shows the location and elevation of each station, as well as the dates for which data is available:




Station/Reservoir
(Lat/Lon)
(X, Y) UTM ETRS89 30S
Elevation (m)
Data range


Quentar
(37.2075626, -3.4353384) 
(461371, 4117987)
1052
12/Sep/2023-2/Nov/2025


Canales
(37.1598003, -3.4750700)
(457819, 4112705)
948
21/Jun/2023-2/Nov/2025


Colomera 
(37.4001539, -3.7205029)
(436230, 4139508)
801
26/Jul/2023-2/Nov/2025


Bermejales
(37.0008422, -3.8875803)
(421027, 4095334)
863
27/Jul/2023-14/Nov/2025




Weather stations and Sensors:

The data for Quentar, Canales, and Colomera were obtained using a Campbell 350-Cell 215 station equipped with an all-in-one ClimaVUE 50 sensor that reports air temperature, relative humidity, vapour pressure, barometric pressure, wind (speed, gust, and direction), solar radiation, precipitation, and lightning strikes (count and distance). The sensor takes measurements every 10 seconds and stores them every 10 minutes.

The data from Bermejales comes from a HOBO RX3004, equipped with a Silicon Pyranometer S-LIB-M003, a Davis® Wind Speed and Direction Smart Sensor S-WCF-M003, a Temperature/RH Smart Sensor S-THB-M003 and a Smart Barometric Pressure Sensor S-BPB-CM50. The data is stored every 30 minutes.

Files and formats:

The files for Quentar, Canales, and Colomera are presented in Campbell Scientific raw ASCII (.dat) format, with the following variables:



'BattV_Avg': “Average battery voltage”,

“SlrFD_W_Avg”: “Solar flux density W/m2”,

“Rain_mm_Tot”: “Precipitation mm”,

“Strikes_Tot”: “Lightning strike count”,

“Dist_km_Avg”: “Strike distance km average”,

'Dist_km_Min': “Minimum strike distance km”,

“WS_ms_S_WVT”: “Wind speed m/s (from wind vector)”,

“WindDir_D1_WVT”: “Wind direction deg  (from wind vector)”,

“MaxWS_ms_Max”: “Wind speed max. – 10 s gust m/s”,

'AirT_C_Avg': “Air temperature dec_C”,

“VP_mbar_Avg”: “Vapour pressure kPa (converted in program to hPa/mbar)”,

“BP_mbar_Avg”: “Barometric pressure (absolute) kPa (converted in program to hPa/mbar)”,

'RH_Avg': “Relative humidity (0-1) (converted in program to 0-100)”,

“RHT_C”: “Humidity sensor temperature °C”,

“TiltNS_deg”: “Tilt North(+)/South(–) orientation deg”,

'TiltWE_deg': “Tilt West(+)/East(–) orientation degrees”,

“SlrTF_MJ_Tot”: “Solar flux density MJ”,

“CVMeta”: “ClimaVue metadata”,

“Invalid_Wind_Tot”: 'number of invalid wind records in each measurement period'


The Bemejales files are presented in raw ASCII format (.csv) with the following variables:



“Solar Radiation W/m²”

'Wind Speed m/s'

“Gust Speed m/s”

'Wind Direction °'

“Temperature °C”

'RH %' for relative humidity

“Dew Point °C”

'Pressure mbar' for atmospheric pressure
DOI: 10.5281/zenodo.17609658
title: Subhourly meteorological data at reservoirs in the upper Genil basin (Canales, Quentar, Colomera and Bermejales) (TED2021-130744B-C22 STAGES).

description: This dataset includes meterological data from four weather stations installed next to the main reservoirs in the upper Genil basin, in south-eastern Spain, between 2023 and 2025. This table shows the location and elevation of each station, as well as the dates for which data is available:




Station/Reservoir
(Lat/Lon)
(X, Y) UTM ETRS89 30S
Elevation (m)
Data range


Quentar
(37.2075626, -3.4353384) 
(461371, 4117987)
1052
12/Sep/2023-2/Nov/2025


Canales
(37.1598003, -3.4750700)
(457819, 4112705)
948
21/Jun/2023-2/Nov/2025


Colomera 
(37.4001539, -3.7205029)
(436230, 4139508)
801
26/Jul/2023-2/Nov/2025


Bermejales
(37.0008422, -3.8875803)
(421027, 4095334)
863
27/Jul/2023-14/Nov/2025




Weather stations and Sensors:

The data for Quentar, Canales, and Colomera were obtained using a Campbell 350-Cell 215 station equipped with an all-in-one ClimaVUE 50 sensor that reports air temperature, relative humidity, vapour pressure, barometric pressure, wind (speed, gust, and direction), solar radiation, precipitation, and lightning strikes (count and distance). The sensor takes measurements every 10 seconds and stores them every 10 minutes.

The data from Bermejales comes from a HOBO RX3004, equipped with a Silicon Pyranometer S-LIB-M003, a Davis® Wind Speed and Direction Smart Sensor S-WCF-M003, a Temperature/RH Smart Sensor S-THB-M003 and a Smart Barometric Pressure Sensor S-BPB-CM50. The data is stored every 30 minutes.

Files and formats:

The files for Quentar, Canales, and Colomera are presented in Campbell Scientific raw ASCII (.dat) format, with the following variables:



'BattV_Avg': “Average battery voltage”,

“SlrFD_W_Avg”: “Solar flux density W/m2”,

“Rain_mm_Tot”: “Precipitation mm”,

“Strikes_Tot”: “Lightning strike count”,

“Dist_km_Avg”: “Strike distance km average”,

'Dist_km_Min': “Minimum strike distance km”,

“WS_ms_S_WVT”: “Wind speed m/s (from wind vector)”,

“WindDir_D1_WVT”: “Wind direction deg  (from wind vector)”,

“MaxWS_ms_Max”: “Wind speed max. – 10 s gust m/s”,

'AirT_C_Avg': “Air temperature dec_C”,

“VP_mbar_Avg”: “Vapour pressure kPa (converted in program to hPa/mbar)”,

“BP_mbar_Avg”: “Barometric pressure (absolute) kPa (converted in program to hPa/mbar)”,

'RH_Avg': “Relative humidity (0-1) (converted in program to 0-100)”,

“RHT_C”: “Humidity sensor temperature °C”,

“TiltNS_deg”: “Tilt North(+)/South(–) orientation deg”,

'TiltWE_deg': “Tilt West(+)/East(–) orientation degrees”,

“SlrTF_MJ_Tot”: “Solar flux density MJ”,

“CVMeta”: “ClimaVue metadata”,

“Invalid_Wind_Tot”: 'number of invalid wind records in each measurement period'


The Bemejales files are presented in raw ASCII format (.csv) with the following variables:



“Solar Radiation W/m²”

'Wind Speed m/s'

“Gust Speed m/s”

'Wind Direction °'

“Temperature °C”

'RH %' for relative humidity

“Dew Point °C”

'Pressure mbar' for atmospheric pressure
DOI: 10.15468/dl.7gvegt
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 {
 "or" : [
 "Year is 2017",
 "Year is 2018",
 "Year is 2019",
 "Year is 2020",
 "Year is 2021",
 "Year is 2022",
 "Year is 2023",
 "Year is 2024",
 "Year is 2016",
 "Year is 2015"
 ]
 },
 "BasisOfRecord is one of (Human Observation, Material sample, Machine Observation)",
 "TaxonKey is one of (Anas georgica [GBIF Backbone Taxonomy])",
 "StateProvince is one of (Distrito Capital de Bogotá)"
 ]
 }
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034182-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eshj3z
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-107.8188 22.64913, -107.6688 22.64913, -107.6688 22.79913, -107.8188 22.79913, -107.8188 22.64913))"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034183-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.