cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/cc12wz20
title: CCDC 1009982: Experimental Crystal Structure Determination

description: Related Article: Yarabally R. Girish, Kothanahally S. Sharath Kumar, Umashankar Muddegowda, Neartur Krishnappagowda Lokanath, Kanchugarakoppal S. Rangappa, Sheena Shashikanth|2014|RSC Advances|4|55800|doi:10.1039/C4RA09970B
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.cc12wz53
title: CCDC 1009985: Experimental Crystal Structure Determination

description: Related Article: Dawei Wang, Keyan Zhao, Chongying Xu, Hongyan Miao, and Yuqiang Ding|2014|ACS Catalysis|4|3910|doi:10.1021/cs5009909
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.cc12wz64
title: CCDC 1009986: Experimental Crystal Structure Determination

description: Related Article: Dawei Wang, Keyan Zhao, Chongying Xu, Hongyan Miao, and Yuqiang Ding|2014|ACS Catalysis|4|3910|doi:10.1021/cs5009909
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.cc12wz75
title: CCDC 1009987: Experimental Crystal Structure Determination

description: Related Article: James E. Mgaya, Egid B. Mubofu, Quintino A. Mgani,  David B. Cordes, Alexandra M. Z. Slawin, David J. Cole-Hamilton|2015|Eur.J.Lipid Sci. Technol.|117|190|doi:10.1002/ejlt.201400268
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: 10.5281/zenodo.17419426
title: scRNA normalized read-counts for T-cell / CAF co-culture CRISPR screen endpoint signatures
DOI: 10.5517/ccdc.csd.cc12wz86
title: CCDC 1009988: Experimental Crystal Structure Determination

description: Related Article: James E. Mgaya, Egid B. Mubofu, Quintino A. Mgani,  David B. Cordes, Alexandra M. Z. Slawin, David J. Cole-Hamilton|2015|Eur.J.Lipid Sci. Technol.|117|190|doi:10.1002/ejlt.201400268
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.cc12wz97
title: CCDC 1009989: Experimental Crystal Structure Determination

description: Related Article: I. V. Ukrainets, L. A. Grinevich, T. V. Alekseeva|2017|Pharm.Chem.J.|51|56|doi:10.1007/s11094-017-1557-8
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/cc12wylh
title: CCDC 1009967: Experimental Crystal Structure Determination

description: Related Article: S. Jone Kirubavathy, R. Velmurugan, R. Karvembu, N. S. P. Bhuvanesh, K. Parameswari, S. Chitra|2015|Koord.Khim.|41|345|doi:10.1134/S1070328415050048
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/cc125tmp
title: CCDC 988702: Experimental Crystal Structure Determination

description: Related Article: Yu-Hui Luo, Xin-Xin Lu, Hong Zhang|2014|CrystEngComm|16|7865|doi:10.1039/C4CE01123F
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/cc12wzmk
title: CCDC 1009999: Experimental Crystal Structure Determination

description: Related Article: Youwei Chen, Yuxin Li, Li Pan, Jingbo Liu, Yingying Wan, Wei Chen, Lixia Xiong, Na Yang, Haibin Song, Zhengming Li|2014|Bioorg.Med.Chem.|22|6366|doi:10.1016/j.bmc.2014.09.052
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.qvvrmq
title: Occurrence Download

description: A dataset containing 570 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Centruroides exilicauda (Wood, 1863)"
 ]
}

 The dataset includes 570 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010949-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/pxvw56
title: Muestreo de mamíferos terrestres en la Finca La Moraleja, Salta, Argentina.

description: El objetivo general de estos muestreos fue describir los ensambles de mamíferos terrestres de mediano y gran porte que utilizan tanto el bosque continuo, los bosques ribereños, las cortinas forestales, las àreas desmontadas y cultivadas con la idea de armar una línea de base de las especies presentes en la Finca La Moraleja.

Durante los meses de octubre y noviembre del año 2017 instalamos un total de 15 cámaras trampa marca Bushnell HD. De estas, seis cámaras se colocaron en sectores boscosos, seis en áreas desmontadas y tres en áreas cultivadas. Durante los meses de agosto y septiembre del año 2019 instalamos un total de 15 cámaras trampa, seis cámaras se colocaron en sectores boscosos y cuatro en corredores riparios y cinco cortinas forestales. Dentro de cada situación de muestreo las cámaras estuvieron distanciadas entre sí, entre 1 y 1,5 km, para disminuir el conteo repetido del mismo ejemplar. Las cámaras fueron cebadas con una lata de atún y estuvieron programadas durante las 24 hs para disparar tres fotos con un tiempo de demora de cinco minutos entre grupos de fotos.

Para el primero año el esfuerzo de muestreo total fue de 512,03 ±18,80 días/cámaras y para el segundo año el esfuerzo fue de 594,01±10,36 días/cámaras.
DOI: 10.5285/0d28bf02-66f1-4692-97ed-ddfd77c24f8a
title: Phosphate-oxygen stable isotope data from sediment core (LG3A), from Rutland Water Nature Reserve, UK

description: The data set includes stable oxygen isotope data measured on the non-labile (HCl-extractable) phosphorus fraction (δ18O-PO4), extracted from each 1 cm layer of sediment core. This sediment core (LG3A) was dated via correlation with a parallel core (LG3C) using 8 age-depth tie points, for which core chronology was established by analysing 210Pb activity at the British Geological Survey Inorganic Geochemistry Laboratories.
DOI: 10.6084/m9.figshare.28548074
title: Computer-aided drug design for the double-membrane vesicle pore complex inhibitorsagainst SARS-CoV-2--raw data

description: This is the raw data for the article "Computer aided drug design for the double methane vessel pore complex inhibitors against SARS-CoV-2"
DOI: 10.15468/dl.zfjwby
title: Occurrence Download

description: A dataset containing 218779 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Carex acutiformis Ehrh.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 218779 records from 921 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007007-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e8r4cc
title: Occurrence Download

description: A dataset containing 245 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Uncia Gray, 1854"
 ]
}

 The dataset includes 245 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007069-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14982479
title: Object Class Instance Extraction: datasets
DOI: 10.5281/zenodo.14982480
title: Object Class Instance Extraction: datasets
DOI: 10.5281/zenodo.14982477
title: CrystaLLM-Fusion

description: Datasets curated for the CrystaLLM-Fusion experminemt
DOI: 10.5281/zenodo.14982478
title: CrystaLLM-Fusion

description: Datasets curated for the CrystaLLM-Fusion experminemt
DOI: 10.5281/zenodo.10958775
title: Wind Turbine SCADA Data For Early Fault Detection
title: CARE To Compare Data

description: Note: Please check out Version 5 of this dataset since some labels have been corrected.

This dataset is published together with the paper "CARE to Compare: A real-world dataset for anomaly detection in wind turbine data", which explains the dataset in detail and defines the CARE-score that can be used to evaluated anomaly detection algorithms on this dataset. When referring to this dataset, please cite the paper mentioned in the related work section.

The data consists of 95 datasets, containing 89 years of SCADA time series distributed across 36 different wind turbinesfrom the three wind farms A, B and C. The number of features depends on the wind farm; Wind farm A has 86 features, wind farm B has 257 features and wind farm C has 957 features. 

The overall dataset is balanced, as 44 out the 95 datasets contain a labeled anomaly event that leads up to a turbine fault and the other 51 datasets represent normal behavior. Additionally, the quality of training data is ensured by turbine-status-based labels for each data point and further information about some of the given turbine faults are included.

The data for Wind farm A is based on data from the EDP open data platform (https://www.edp.com/en/innovation/open-data/data), and consists of 5 wind turbines of an onshore wind farm in Portugal. It contains SCADA data and information derived by a given fault logbook which defines start timestamps for specified faults. From this data 22 datasets were selected to be included in this data collection. The other two wind farms are offshore wind farms located in Germany. All three datasets were anonymized due to confidentiality reasons for the wind farms B and C.Each dataset is provided in form of a csv-file with columns defining the features and rows representing the data points of the time series. Files

More detailed information can be found in the included README-file and in the publication corresponding to this dataset.
DOI: 10.5281/zenodo.14006163
title: Wind Turbine SCADA Data For Early Fault Detection
title: CARE To Compare Data

description: Note: Please check out Version 5 of this dataset since some labels have been corrected.

Note: In version 2 the timestamps of the datasets and event_info-files do not match and there are duplicate timestamps in datasets where the date was converted from a leap year to a non leap year. Please use versions 1 (original dataset) or 4 (without future timestamps) instead.

-----

This dataset is published together with the paper "CARE to Compare: A real-world dataset for anomaly detection in wind turbine data" which explains the dataset in detail and defines the CARE score that can be used to evaluate anomaly detection algorithms on this dataset. When referring to this dataset, please cite the paper mentioned in the related work section. 

This new version of the dataset contains one deviation from version 1 regarding the anonymization procedure. Instead of shifting the timestamps of each sub-dataset by a random number of years, the size of the time shift is now determined to be the number of years so that each sub-dataset starts in 2022. This change is made to make the timestamp anonymization more consistent and to avoid future timestamps being present within the data.

The data consists of 95 datasets, containing 89 years of SCADA time series distributed across 36 different wind turbinesfrom the three wind farms A, B and C. The number of features depends on the wind farm; Wind farm A has 86 features, wind farm B has 257 features and wind farm C has 957 features. 

The overall dataset is balanced, as 44 out the 95 datasets contain a labeled anomaly event that leads up to a turbine fault and the other 51 datasets represent normal behavior. Additionally, the quality of training data is ensured by turbine-status-based labels for each data point and further information about some of the given turbine faults are included.

The data for Wind farm A is based on data from the EDP open data platform (https://www.edp.com/en/innovation/open-data/data), and consists of 5 wind turbines of an onshore wind farm in Portugal. It contains SCADA data and information derived by a given fault logbook which defines start timestamps for specified faults. From this data 22 datasets were selected to be included in this data collection. The other two wind farms are offshore wind farms located in Germany. All three datasets were anonymized due to confidentiality reasons for the wind farms B and C.Each dataset is provided in form of a csv-file with columns defining the features and rows representing the data points of the time series. Files

More detailed information can be found in the included README-file.
DOI: 10.5281/zenodo.14854959
title: Wind Turbine SCADA Data For Early Fault Detection
title: CARE To Compare Data

description: Note: Please check out Version 5 of this dataset since some labels have been corrected.

Note: In version 3 there are duplicate timestamps in datasets where the date was converted from a leap year to a non leap year. Please use versions 1 (original dataset) or 4 (without future timestamps) instead.

-----

This dataset is published together with the paper "CARE to Compare: A real-world dataset for anomaly detection in wind turbine data" which explains the dataset in detail and defines the CARE score that can be used to evaluate anomaly detection algorithms on this dataset. When referring to this dataset, please cite the paper mentioned in the related work section. 

The data consists of 95 datasets, containing 89 years of SCADA time series distributed across 36 different wind turbinesfrom the three wind farms A, B and C. The number of features depends on the wind farm; Wind farm A has 86 features, wind farm B has 257 features and wind farm C has 957 features. 

The overall dataset is balanced, as 44 out the 95 datasets contain a labeled anomaly event that leads up to a turbine fault and the other 51 datasets represent normal behavior. Additionally, the quality of training data is ensured by turbine-status-based labels for each data point and further information about some of the given turbine faults are included.

The data for Wind farm A is based on data from the EDP open data platform (https://www.edp.com/en/innovation/open-data/data), and consists of 5 wind turbines of an onshore wind farm in Portugal. It contains SCADA data and information derived by a given fault logbook which defines start timestamps for specified faults. From this data 22 datasets were selected to be included in this data collection. The other two wind farms are offshore wind farms located in Germany. All three datasets were anonymized due to confidentiality reasons for the wind farms B and C.Each dataset is provided in form of a csv-file with columns defining the features and rows representing the data points of the time series. Files

More detailed information can be found in the included README-file.

Version Changes:

Version 2->3:

In version 2 timestamp changes were not consistent with the timestamps in the event-info-files. Version 3 fixes this.

Version 1->2:

Version 2 contains one deviation from version 1 regarding the anonymization procedure. Instead of shifting the timestamps of each sub-dataset by a random number of years, the size of the time shift is now determined to be the number of years so that each sub-dataset starts in 2022. This change is made to make the timestamp anonymization more consistent and to avoid future timestamps being present within the data.
DOI: 10.5281/zenodo.14857470
title: Wind Turbine SCADA Data For Early Fault Detection
title: CARE To Compare Data

description: Note: Please check out Version 5 of this dataset since some labels have been corrected.

This dataset is published together with the paper "CARE to Compare: A real-world dataset for anomaly detection in wind turbine data" which explains the dataset in detail and defines the CARE score that can be used to evaluate anomaly detection algorithms on this dataset. When referring to this dataset, please cite the paper mentioned in the related work section. 

The data consists of 95 datasets, containing 89 years of SCADA time series distributed across 36 different wind turbinesfrom the three wind farms A, B and C. The number of features depends on the wind farm; Wind farm A has 86 features, wind farm B has 257 features and wind farm C has 957 features. 

The overall dataset is balanced, as 44 out the 95 datasets contain a labeled anomaly event that leads up to a turbine fault and the other 51 datasets represent normal behavior. Additionally, the quality of training data is ensured by turbine-status-based labels for each data point and further information about some of the given turbine faults are included.

The data for Wind farm A is based on data from the EDP open data platform (https://www.edp.com/en/innovation/open-data/data), and consists of 5 wind turbines of an onshore wind farm in Portugal. It contains SCADA data and information derived by a given fault logbook which defines start timestamps for specified faults. From this data 22 datasets were selected to be included in this data collection. The other two wind farms are offshore wind farms located in Germany. All three datasets were anonymized due to confidentiality reasons for the wind farms B and C.Each dataset is provided in form of a csv-file with columns defining the features and rows representing the data points of the time series. Files

More detailed information can be found in the included README-file.

Version Changes:

Version 3->4:

The change of the timestamp anonymization lead to duplicate timestamps when transitioning from a leap year to 2022. This is now fixed in Version 4.

Version 2->3:

In version 2 timestamp changes were not consistent with the timestamps in the event-info-files. Version 3 fixes this.

Version 1->2:

Version 2 contains one deviation from version 1 regarding the anonymization procedure. Instead of shifting the timestamps of each sub-dataset by a random number of years, the size of the time shift is now determined to be the number of years so that each sub-dataset starts in 2022. This change is made to make the timestamp anonymization more consistent and to avoid future timestamps being present within the data.
DOI: 10.15468/dl.qg7esj
title: Occurrence Download

description: A dataset containing 14152 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-2.04961 43.27796,-1.90286 43.27796,-1.90286 43.33626,-2.04961 43.33626,-2.09573 43.3324,-2.13161 43.30052,-2.13947 43.28217,-2.10037 43.26908,-2.04961 43.27796))",
 "HasGeospatialIssue is false",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 14152 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007016-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2yhdj3
title: Occurrence Download

description: A dataset containing 2905 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Nepal",
 "TaxonKey is Rhododendron L."
 ]
}

 The dataset includes 2905 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007017-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wbr6y8
title: Occurrence Download

description: A dataset containing 33498742 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Colombia"
 ]
}

 The dataset includes 33498742 records from 4694 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007011-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17287753
title: ly16
DOI: 10.5281/zenodo.17287754
title: ly16
DOI: 10.15468/dl.ufgkfk
title: Occurrence Download

description: A dataset containing 4110 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Czechia",
 "Geometry POLYGON((13.65272 50.55587,13.64617 50.55553,13.63645 50.54969,13.63061 50.53957,13.6338 50.52822,13.64547 50.52474,13.65608 50.52822,13.66368 50.53946,13.66333 50.54598,13.65625 50.54699,13.65997 50.5507,13.65272 50.55587))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Anseriformes",
 "Year 2019-2024"
 ]
}

 The dataset includes 4110 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058318-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x9x9yw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Apterygiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-180 0,-150 0,-150 30,-180 30,-180 0))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058322-250920141307145/datasets/export for details.