cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0196699.10fu
title: SH0196699.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.v4vd3v
title: Occurrence Download

description: A dataset containing 388063 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)"
 ]
 }
 },
 "Geometry POLYGON((38.000 85.000, -27.000 85.000, -27.000 56.000, 38.000 56.000, 38.000 85.000))",
 "Year 1900-1909"
 ]
}

 The dataset includes 388063 records from 566 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000083-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gzzf6k
title: Occurrence Download

description: A dataset listing the 2947 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "PublishingOrg is one of (1e9400fa-ce73-4737-9eaa-f25df148945c, f9b67ad0-9c9b-11d9-b9db-b8a03c50a862, 493fe050-055d-11d8-b84f-b8a03c50a862, b711353c-44d7-4e8b-90c5-16fea0d247e0, 78678140-1815-11da-9544-b8a03c50a862, e88c96a3-5884-4e51-a580-e417ca4c9eed, 66522820-055c-11d8-b84e-b8a03c50a862, cc17c672-0c7d-492f-9252-c7ddacd1df78, 5624d6f9-a94b-42c4-8814-a587e7e5e6f0)",
 "TaxonKey is Mollusca"
 ]
}

 The dataset's 2947 records were derived from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000098-250213122211068/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.cc2krfrj
title: CCDC 2376018: Experimental Crystal Structure Determination

description: Related Article: Moad Bouzid, Didier Poinsot, Clève D. Mboyi, Lukas Ochmann, Bruno Domenichini, Peter R. Schreiner, Jean-Cyrille Hierso|2025|Nanoscale|17|4123|doi:10.1039/D4NR03511A
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.cc2krfsk
title: CCDC 2376019: Experimental Crystal Structure Determination

description: Related Article: Moad Bouzid, Didier Poinsot, Clève D. Mboyi, Lukas Ochmann, Bruno Domenichini, Peter R. Schreiner, Jean-Cyrille Hierso|2025|Nanoscale|17|4123|doi:10.1039/D4NR03511A
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.5hj6yk
title: Occurrence Download

description: A dataset containing 1765 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "TaxonKey is Panthera onca (Linnaeus, 1758)"
 ]
}

 The dataset includes 1765 records from 66 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000106-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h5uybb
title: Occurrence Download

description: A dataset containing 406 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Stereochilus marginatus (Hallowell, 1856))"
 ]
}

 The dataset includes 406 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000107-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.emxda2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pelecanus leucogaster Boddaert, 1783",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000109-250213122211068/datasets/export for details.
DOI: 10.6084/m9.figshare.28408913
title: Fungal Community Composition and Taxonomy Dataset

description: Fungal metadata used in the research project "<b>Land-use changes impact root-fungal network connectivity in a global biodiversity hotspot</b>".
DOI: 10.15468/dl.hhcr4d
title: Occurrence Download

description: A dataset containing 467803 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)"
 ]
 }
 },
 "Geometry POLYGON((38.000 85.000, -27.000 85.000, -27.000 56.000, 38.000 56.000, 38.000 85.000))",
 "Year 1910-1919"
 ]
}

 The dataset includes 467803 records from 539 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000085-250213122211068/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.28408913.v1
title: Metadata Fungal dataset

description: Fungal metadata used in the research project "<b>Land-use changes impact root-fungal network connectivity in a global biodiversity hotspot</b>".
DOI: 10.15468/dl.6tfxpf
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cryptonanus chacoensis (Tate, 1931)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 43 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000108-250213122211068/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.28409012
title: Roots Community Composition and Taxonomy Dataset

description: Roots metadata used in the research "<b>Land-use changes impact root-fungal network connectivity in a global biodiversity hotspot".</b>
DOI: 10.6084/m9.figshare.28409012.v1
title: Metadata Roots

description: Roots metadata used in the research "<b>Land-use changes impact root-fungal network connectivity in a global biodiversity hotspot".</b>
DOI: 10.15468/dl.n95syg
title: Occurrence Download

description: A dataset containing 19172 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Taricha granulosa (Skilton, 1849))"
 ]
}

 The dataset includes 19172 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000110-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.udtr35
title: Occurrence Download

description: A dataset containing 255 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lepidotrigla microptera Günther, 1873",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 255 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000111-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yn6acr
title: Occurrence Download

description: A dataset containing 162 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Calomys tener (Winge, 1888)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 162 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000112-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.7682713
title: BEELINE

description: This collection consists of over 400 single-cell gene expression datasets across four curated and six synthetic gene regulatory networks. It was created to benchmarking algorithms for gene regulatory network inference in Pratapa et al. (2020).

 

Task: The collection can be used to study causal inference algorithms.

 

Summary: 



Size of collection: >400 datasets on 6 - 19 features of different size

Task: Causal Inference Problem

Data Type: Mixed Data

Dataset Scope: Collection of Datasets

Ground Truth: Known Graph

Temporal Structure: Static Data

License: CC BY-NC 4.0 (see 10.5281/zenodo.3701939)

Missing Values: No Missing Values


 

Missingness Statement: There are no missing values.

 

Collection: (for a detailed description see Peng et al. (2024), for simulation details see Pratapa et al. (2020))



Curated: There are experiments on four curated gene regulatory networks: mCAD (Mammalian Cortical Area Development, 14 edges and 5 nodes), VSC (Ventral Spinal Cord Development, 15 edges and 8 nodes), HSC (Hematopoietic Stem Cell Differentiation, 30 edges and 11 nodes), and GSD (Gonadal Sex Determination, 79 edges and 18 nodes).

Synthetic: There are experiments six synthetic gene regulatory networks: dyn-BF (Bifurcating, 12 edges and 5 nodes), dyn-BFC (Bifurcating Converging, 18 edges and 9 nodes), dyn-CY (Cycle, 6 edges and 5 nodes), dyn-LI (Linear, 8 edges and 7 nodes), dyn-LL (Linear Long, 19 edges and 18 nodes), and dyn-TF (Trifurcating, 20 edges and 7 nodes).


 

Files per Experiment:



GroundTruth.csv: This file represents the actual biological regulatory interactions between genes, typically derived from known databases, literature, or synthetic models. An edge weight of +1 represents activation, -1 represents inhibition.

refNetwork.csv: This file is a processed version of the ground truth network, keeping only the sign (+ or -) of interactions.

ExpressionData.csv: This file contains the RNAseq data, with genes as rows and cell IDs as columns.

PseudoTime.csv: This file contains the Pseudotime. It is a computationally inferred measure that orders single cells along a trajectory to represent their progression through a biological process, such as differentiation or development.
DOI: 10.5281/zenodo.7682712
title: BEELINE

description: This collection consists of over 400 single-cell gene expression datasets across four curated and six synthetic gene regulatory networks. It was created to benchmarking algorithms for gene regulatory network inference in Pratapa et al. (2020).

 

Task: The collection can be used to study causal inference algorithms.

 

Summary: 



Size of collection: >400 datasets on 6 - 19 features of different size

Task: Causal Inference Problem

Data Type: Mixed Data

Dataset Scope: Collection of Datasets

Ground Truth: Known Graph

Temporal Structure: Static Data

License: CC BY-NC 4.0 (see 10.5281/zenodo.3701939)

Missing Values: No Missing Values


 

Missingness Statement: There are no missing values.

 

Collection: (for a detailed description see Peng et al. (2024), for simulation details see Pratapa et al. (2020))



Curated: There are experiments on four curated gene regulatory networks: mCAD (Mammalian Cortical Area Development, 14 edges and 5 nodes), VSC (Ventral Spinal Cord Development, 15 edges and 8 nodes), HSC (Hematopoietic Stem Cell Differentiation, 30 edges and 11 nodes), and GSD (Gonadal Sex Determination, 79 edges and 18 nodes).

Synthetic: There are experiments six synthetic gene regulatory networks: dyn-BF (Bifurcating, 12 edges and 5 nodes), dyn-BFC (Bifurcating Converging, 18 edges and 9 nodes), dyn-CY (Cycle, 6 edges and 5 nodes), dyn-LI (Linear, 8 edges and 7 nodes), dyn-LL (Linear Long, 19 edges and 18 nodes), and dyn-TF (Trifurcating, 20 edges and 7 nodes).


 

Files per Experiment:



GroundTruth.csv: This file represents the actual biological regulatory interactions between genes, typically derived from known databases, literature, or synthetic models. An edge weight of +1 represents activation, -1 represents inhibition.

refNetwork.csv: This file is a processed version of the ground truth network, keeping only the sign (+ or -) of interactions.

ExpressionData.csv: This file contains the RNAseq data, with genes as rows and cell IDs as columns.

PseudoTime.csv: This file contains the Pseudotime. It is a computationally inferred measure that orders single cells along a trajectory to represent their progression through a biological process, such as differentiation or development.
DOI: 10.5281/zenodo.14745084
title: UCI Datasets: "Air quality" and "US Census (1990)"

description: Air Quality

This dataset from the UCI repository represents hourly averaged measurements of 5 metal oxide chemical sensors embedded in an air quality chemical multisensor device. The certified analyzer was located on the field in a significantly polluted area, at road level, within an Italian city. Data were recorded from March 2004 to February 2005 (one year), representing the longest freely available recordings of on-field deployed air quality chemical sensor device responses (De Vitoet et al., 2008).

 

Task: The dataset can be used to study causal discovery methods.

 

Summary: 



Size of dataset: 9357 x 15

Task: Causal Discovery

Data Type: Mixed

Dataset Scope: Standalone

Ground Truth: Unknown

Temporal Structure: Time Series

License: CC BY 4.0

Missing Values: No


 

Missingness Statement: There are no missing values.

 

Features:



Date (DD/MM/YYYY)

Time (HH.MM.SS)

True hourly averaged concentration CO in mg/m^3 (reference analyzer)

PT08.S1 (tin oxide) hourly averaged sensor response (nominally CO targeted)

True hourly averaged overall Non Metanic HydroCarbons concentration in microg/m^3 (reference analyzer)

True hourly averaged Benzene concentration in microg/m^3 (reference analyzer)

PT08.S2 (titania) hourly averaged sensor response (nominally NMHC targeted)

True hourly averaged NOx concentration in ppb (reference analyzer)

PT08.S3 (tungsten oxide) hourly averaged sensor response (nominally NOx targeted)

True hourly averaged NO2 concentration in microg/m^3 (reference analyzer)

PT08.S4 (tungsten oxide) hourly averaged sensor response (nominally NO2 targeted)

PT08.S5 (indium oxide) hourly averaged sensor response (nominally O3 targeted)

Temperature in Â°C

Relative Humidity (%)

AH Absolute Humidity


 

Files: 



AirQualityUCI.csv: dataset


 

US Census (1990)

The data represents a one percent sample drawn from the full 1990 census. This was made possible through the Public Use Microdata Samples (PUMS). Furthermore, the few continuous variables were discretized. (UCI Source)

 

Task: The dataset can be used to study causal discovery methods.

 

Summary: 



Size of dataset: 2458285 x 68

Task: Causal Discovery

Data Type: Discrete

Dataset Scope: Standalone

Ground Truth: Unknown

Temporal Structure: Static

License: CC BY 4.0

Missing Values: No


 

Missingness Statement: There are no missing values.

 

Features:



See the file variable_description_US_Census_1990.txt for a detailed description.


 

Files: 



USCensus1990.csv: dataset

variable_description_US_Census_1990.txt: feature details
DOI: 10.5281/zenodo.14794099
title: US Census

description: The data represents a one percent sample drawn from the full 1990 census. This was made possible through the Public Use Microdata Samples (PUMS). Furthermore, the few continuously-measured variables were discretized.

 

Task: The dataset can be used to study causal discovery methods.

 

Summary: 



Size of dataset: 2458285 x 68

Task: Causal Discovery Problem

Data Type: Discrete Data

Dataset Scope: Standalone Dataset

Ground Truth: Unknown Graph

Temporal Structure: Static Data

License: CC0 (see census.gov)

Missing Values: No Missing Values


 

Missingness Statement: There are no missing values.

 

Features:



See the file variable_description_US_Census_1990.txt for a detailed description.


 

Files: 



USCensus1990.csv: dataset

variable_description_US_Census_1990.txt: feature details
DOI: 10.5281/zenodo.8063511
title: US Census

description: The data represents a one percent sample drawn from the full 1990 census. This was made possible through the Public Use Microdata Samples (PUMS). Furthermore, the few continuously-measured variables were discretized.

 

Task: The dataset can be used to study causal discovery methods.

 

Summary: 



Size of dataset: 2458285 x 68

Task: Causal Discovery Problem

Data Type: Discrete Data

Dataset Scope: Standalone Dataset

Ground Truth: Unknown Graph

Temporal Structure: Static Data

License: CC0 (see census.gov)

Missing Values: No Missing Values


 

Missingness Statement: There are no missing values.

 

Features:



See the file variable_description_US_Census_1990.txt for a detailed description.


 

Files: 



USCensus1990.csv: dataset

variable_description_US_Census_1990.txt: feature details
DOI: 10.5281/zenodo.14864404
title: ELITE land surface temperature: FY-4B/AGRI hourly 4km clear-sky LST (2022.6-2023.12)

description: The Essential thermaL Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

This dataset is the 4km hourly clear-sky LST dataset derived by the iTES algorithm  from the FY-4B/AGRI thermal infrared data, covering the AGRI 4km nominal fixed disc (80.6°N-80.6°S, 51.8°E-145.8°W). The temporal resolution and spatial resolution of this dataset are one hour and 4km, respectively.

This is the ELITE FY-4B/AGRI clear-sky LST product in 2022.6-2023.12. 

Dataset Characteristics:



Spatial Coverage: AGRI nominal fixed disc (80.6°N-80.6°S, 51.8°E-145.8°W)

Temporal Coverage: 2022.6-2023.12

Spatial Resolution: 4 km (subsatellite point)

Temporal Resolution: one hour

Data Format: HDF

Scale: 0.01


If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).
DOI: 10.5281/zenodo.14864405
title: ELITE land surface temperature: FY-4B/AGRI hourly 4km clear-sky LST (2022.6-2023.12)

description: The Essential thermaL Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

This dataset is the 4km hourly clear-sky LST dataset derived by the iTES algorithm  from the FY-4B/AGRI thermal infrared data, covering the AGRI 4km nominal fixed disc (80.6°N-80.6°S, 51.8°E-145.8°W). The temporal resolution and spatial resolution of this dataset are one hour and 4km, respectively.

This is the ELITE FY-4B/AGRI clear-sky LST product in 2022.6-2023.12. 

Dataset Characteristics:



Spatial Coverage: AGRI nominal fixed disc (80.6°N-80.6°S, 51.8°E-145.8°W)

Temporal Coverage: 2022.6-2023.12

Spatial Resolution: 4 km (subsatellite point)

Temporal Resolution: one hour

Data Format: HDF

Scale: 0.01


If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).
DOI: 10.5284/1122709
title: Text and Spreadsheet Data from a Rescue Excavation of Braughing Late Iron Age Coin Moulds, Braughing, Hertfordshire, August 2016

description: This digital archive comprises of text and spreadsheets, which provide analysis of a large group of Late Iron Age coin moulds recovered from a Roman-period dump that was eroding into the River Rib at the Scheduled Monument of Braughing Late Iron Age and Roman town. The work was rescue excavation was undertaken in August 2016 Mark Landon and the Braughing Archaeology Group (BAG), with the professional oversight of Jonathan Hunn (Icknield Archaeology).
DOI: 10.5281/zenodo.14864341
title: ELITE land surface temperature: FY-4B/AGRI hourly 4km seamless LST (2022.6-2023.12)

description: The Essential thermaL Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth's radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

This dataset is the ELITE hourly seamless 4 km LST dataset covering the FY-4B/AGRI nominal fixed disc (80.6°N-80.6°S, 51.8°E-145.8°W).  First, an improved temperature and emissivity separation algorithm was used to obtain the clear-sky LST. Then, under the framework of the SEB theory, a unique way was proposed to solve the temperature difference between the cloudy-sky LST and hypothetical clear-sky LST caused by cloud radiative effects.  The temporal resolution and spatial resolution of this dataset are 1 hour and 4 km, respectively.

This is the ELITE FY-4B/AGRI seamless LST product in 2022.6-2023.12. 

Dataset Characteristics:



Spatial Coverage: AGRI nominal fixed disc (80.6°N-80.6°S, 51.8°E-145.8°W)

Temporal Coverage: 2022.6-2023.12

Spatial Resolution: 4 km (subsatellite point)

Temporal Resolution: one hour

Data Format: HDF

Scale: 0.01


If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).