cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.nt9w64
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 "HostingOrganizationKey is c5f7ef70-e233-11d9-a4d6-b8a03c50a862",
 "TaxonKey is Amegilla albocaudata (Dours, 1869)"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082842-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kqg3k5
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-84.4091205999999943 42.2173544999999990, -84.4091205999999943 42.2184633999999974, -84.4091205999999943 42.2197307100000003, -84.4091205999999943 42.2216316800000016, -84.4091205999999943 42.2225821600000017, -84.4091205999999943 42.2243247199999985, -84.4091205999999943 42.2252751999999987, -84.4073767400000037 42.2252751999999987, -84.4057913500000012 42.2252751999999987, -84.4034132700000015 42.2252751999999987, -84.4015900699999975 42.2252751999999987, -84.4001632199999960 42.2252751999999987, -84.3991327199999972 42.2252751999999987, -84.3977852000000013 42.2252751999999987, -84.3977852000000013 42.2239286800000002, -84.3977852000000013 42.2219485099999972, -84.3977852000000013 42.2207604000000032, -84.3977852000000013 42.2188594300000020, -84.3977852000000013 42.2173544999999990, -84.3989741799999962 42.2173544999999990, -84.4010351799999938 42.2173544999999990, -84.4028583799999979 42.2173544999999990, -84.4045230400000008 42.2173544999999990, -84.4062669599999964 42.2173544999999990, -84.4080901600000004 42.2173544999999990, -84.4091205999999943 42.2173544999999990))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0092235-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uuxm8p
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Neoregelia crispata Leme"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046416-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.33kejb
title: Occurrence Download

description: A dataset containing 6199 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-79.9592999999999989 37.2406760000000006, -79.9592999999999989 37.2427784200000005, -79.9592999999999989 37.2442501100000030, -79.9592999999999989 37.2454064499999973, -79.9592999999999989 37.2470883800000010, -79.9592999999999989 37.2492959200000016, -79.9592999999999989 37.2511881000000002, -79.9567840200000006 37.2511881000000002, -79.9540587000000045 37.2511881000000002, -79.9523815799999937 37.2511881000000002, -79.9495514399999934 37.2511881000000002, -79.9471405799999957 37.2511881000000002, -79.9448345400000022 37.2511881000000002, -79.9430523000000051 37.2511881000000002, -79.9430523000000051 37.2491908000000009, -79.9430523000000051 37.2467730199999991, -79.9430523000000051 37.2455115699999979, -79.9430523000000051 37.2434091499999980, -79.9430523000000051 37.2406760000000006, -79.9444152599999995 37.2406760000000006, -79.9465116599999988 37.2406760000000006, -79.9487128800000022 37.2406760000000006, -79.9505996399999930 37.2406760000000006, -79.9525912200000022 37.2406760000000006, -79.9543731600000029 37.2406760000000006, -79.9566791999999964 37.2406760000000006, -79.9592999999999989 37.2406760000000006))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 6199 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082852-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jnkj7w
title: Occurrence Download

description: A dataset containing 11514 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-73.7680844000000064 40.5948861999999977, -73.7680844000000064 40.5972913700000007, -73.7680844000000064 40.5993167800000023, -73.7680844000000064 40.6017219499999982, -73.7680844000000064 40.6047600599999967, -73.7680844000000064 40.6075450000000018, -73.7654219899999930 40.6075450000000018, -73.7628861700000016 40.6075450000000018, -73.7606039300000020 40.6075450000000018, -73.7578145199999966 40.6075450000000018, -73.7543911700000052 40.6075450000000018, -73.7503338500000041 40.6075450000000018, -73.7474176599999964 40.6075450000000018, -73.7456425799999948 40.6075450000000018, -73.7425995899999975 40.6075450000000018, -73.7401905600000021 40.6075450000000018, -73.7382889000000006 40.6075450000000018, -73.7382889000000006 40.6058993600000022, -73.7382889000000006 40.6040005400000013, -73.7382889000000006 40.6026080700000023, -73.7382889000000006 40.6007092500000013, -73.7382889000000006 40.5983040799999984, -73.7382889000000006 40.5948861999999977, -73.7401905600000021 40.5948861999999977, -73.7428531799999973 40.5948861999999977, -73.7443746699999991 40.5948861999999977, -73.7471640699999966 40.5948861999999977, -73.7496998999999960 40.5948861999999977, -73.7529964600000056 40.5948861999999977, -73.7564198200000050 40.5948861999999977, -73.7580681099999964 40.5948861999999977, -73.7604771400000061 40.5948861999999977, -73.7625057999999996 40.5948861999999977, -73.7659291500000052 40.5948861999999977, -73.7680844000000064 40.5948861999999977))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 11514 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093120-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kgqvyn
title: Occurrence Download

description: A dataset containing 6986 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Veratrum lobelianum Bernh.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6986 records from 101 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058513-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hjk2vb
title: Occurrence Download

description: A dataset containing 15216 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1000-1984"
 ]
}

 The dataset includes 15216 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0141385-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tqcup2
title: Occurrence Download

description: A dataset containing 1840 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sitophilus zeamais Motschulsky & V.de, 1855"
 ]
}

 The dataset includes 1840 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0148390-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ikj4vq
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016609-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jea9ls
title: Occurrence Download

description: A dataset containing 109176 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Herps Specimens"
 ]
}

 The dataset includes 109176 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011100-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.lbcuw4
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079166-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.khahwm
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016629-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xgh7pw
title: Occurrence Download

description: A dataset containing 52813730 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is iNaturalist Research-grade Observations"
 ]
}

 The dataset includes 52813730 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0142204-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mcmi7h
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000452-160430102343922/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dnqwyx
title: Occurrence Download

description: A dataset containing 93580849 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Artportalen (Swedish Species Observation System)"
 ]
}

 The dataset includes 93580849 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0184373-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uctou1
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016705-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.oljjig
title: Occurrence Download

description: A dataset containing 1667068639 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 1667068639 records from 19276 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000946-180412121330197/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17205321
title: A deep learning-based computational pipeline predicts developmental outcome in retinal organoids: classification images [maximum projections]

description: Deposited are the source images as used in our publication to predict the tissue development of medaka organoids (https://www.biorxiv.org/content/10.1101/2025.02.19.639061v1).

 

The images are stored in our custom dataset format. In order to read it, you will need to clone the repo: https://github.com/TarikExner/orgAInoid

 

The code to import is the following:

```python

from orgAInoid.classification import OrganoidDataset

data = OrganoidDataset.read_classification_dataset("./path/to/file.cds")

// metadata are accessed via the .metadata attribute. The respective image array index is stored within this table.

data.metadata

//image arrays are stored at the .X and .y[readout] attribute, where attribute is one of "RPE_Final", "Lens_Final", "RPE_classes" and "Lens_classes"

 

For further information refer to the github repository.

```
DOI: 10.5281/zenodo.17205320
title: A deep learning-based computational pipeline predicts developmental outcome in retinal organoids: classification images [maximum projections]

description: Deposited are the source images as used in our publication to predict the tissue development of medaka organoids (https://www.biorxiv.org/content/10.1101/2025.02.19.639061v1).

 

The images are stored in our custom dataset format. In order to read it, you will need to clone the repo: https://github.com/TarikExner/orgAInoid

 

The code to import is the following:

```python

from orgAInoid.classification import OrganoidDataset

data = OrganoidDataset.read_classification_dataset("./path/to/file.cds")

// metadata are accessed via the .metadata attribute. The respective image array index is stored within this table.

data.metadata

//image arrays are stored at the .X and .y[readout] attribute, where attribute is one of "RPE_Final", "Lens_Final", "RPE_classes" and "Lens_classes"

 

For further information refer to the github repository.

```
DOI: 10.57702/sulbrzxx
title: A Gait Triage Toolkit for Overlapping Acoustic Events in Indoor Environments

description: A gait triaging toolkit for overlapping acoustic events in indoor environments
DOI: 10.57702/dqmfps01
title: S3DIS and ScanNet datasets for point cloud semantic segmentation

description: The S3DIS and ScanNet datasets are used for point cloud semantic segmentation.
DOI: 10.15468/dl.7pee8b
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.69985 24.906783, 89.62243100000001 24.901206, 89.54694000000001 24.884614, 89.475251 24.857419, 89.40914600000001 24.820297, 89.350262 24.774171, 89.30005 24.720186, 89.259744 24.65968, 89.230327 24.594152, 89.212509 24.52522, 89.206709 24.454586, 89.213052 24.383991, 89.23136 24.315171, 89.261166 24.249817, 89.301721 24.189532, 89.352019 24.135791, 89.41081800000001 24.08991, 89.47667300000001 24.053009, 89.547972 24.025988, 89.622974 24.009508, 89.69985 24.00397, 89.776726 24.009508, 89.85172799999999 24.025988, 89.923027 24.053009, 89.988882 24.08991, 90.047681 24.135791, 90.097979 24.189532, 90.13853400000001 24.249817, 90.16834 24.315171, 90.18664800000001 24.383991, 90.19299100000001 24.454586, 90.187191 24.52522, 90.16937299999999 24.594152, 90.139956 24.65968, 90.09965 24.720186, 90.04943799999999 24.774171, 89.990554 24.820297, 89.924449 24.857419, 89.85276 24.884614, 89.777269 24.901206, 89.69985 24.906783))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079693-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.17202714
title: A deep learning-based computational pipeline predicts developmental outcome in retinal organoids: classification images [Single Slice]

description: Deposited are the source images as used in our publication to predict the tissue development of medaka organoids (https://www.biorxiv.org/content/10.1101/2025.02.19.639061v1).

 

The images are stored in our custom dataset format. In order to read it, you will need to clone the repo: https://github.com/TarikExner/orgAInoid

 

The code to import is the following:

```python

from orgAInoid.classification import OrganoidDataset

data = OrganoidDataset.read_classification_dataset("./path/to/file.cds")

// metadata are accessed via the .metadata attribute. The respective image array index is stored within this table.

data.metadata

//image arrays are stored at the .X and .y[readout] attribute, where attribute is one of "RPE_Final", "Lens_Final", "RPE_classes" and "Lens_classes"

 

For further information refer to the github repository.

```
DOI: 10.57702/lqnxccrx
title: Customer Service Calls Dataset

description: A dataset consisting of ten years of customer service calls to a fleet truck company.
DOI: 10.5281/zenodo.17202713
title: A deep learning-based computational pipeline predicts developmental outcome in retinal organoids: classification images [Single Slice]

description: Deposited are the source images as used in our publication to predict the tissue development of medaka organoids (https://www.biorxiv.org/content/10.1101/2025.02.19.639061v1).

 

The images are stored in our custom dataset format. In order to read it, you will need to clone the repo: https://github.com/TarikExner/orgAInoid

 

The code to import is the following:

```python

from orgAInoid.classification import OrganoidDataset

data = OrganoidDataset.read_classification_dataset("./path/to/file.cds")

// metadata are accessed via the .metadata attribute. The respective image array index is stored within this table.

data.metadata

//image arrays are stored at the .X and .y[readout] attribute, where attribute is one of "RPE_Final", "Lens_Final", "RPE_classes" and "Lens_classes"

 

For further information refer to the github repository.

```
DOI: 10.5281/zenodo.17205312
title: A deep learning-based computational pipeline predicts developmental outcome in retinal organoids: classification images [sum projections]

description: Deposited are the source images as used in our publication to predict the tissue development of medaka organoids (https://www.biorxiv.org/content/10.1101/2025.02.19.639061v1).

 

The images are stored in our custom dataset format. In order to read it, you will need to clone the repo: https://github.com/TarikExner/orgAInoid

 

The code to import is the following:

```python

from orgAInoid.classification import OrganoidDataset

data = OrganoidDataset.read_classification_dataset("./path/to/file.cds")

// metadata are accessed via the .metadata attribute. The respective image array index is stored within this table.

data.metadata

//image arrays are stored at the .X and .y[readout] attribute, where attribute is one of "RPE_Final", "Lens_Final", "RPE_classes" and "Lens_classes"

 

For further information refer to the github repository.

```
DOI: 10.57702/zeshnsne
title: CMOTB

description: A comprehensive and extensive benchmark dataset for cross-modal object tracking.
DOI: 10.15468/dl.nqaa3p
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anabasis truncata, Anabasis kareliniana, Anabasis pulcherrima, Brachylepis truncata)",
 "HasCoordinate is true",
 "Year is greater than or equal to 1970",
 "Year is less than or equal to 2024",
 "CoordinateUncertaintyInMeters is greater than or equal to 0",
 "CoordinateUncertaintyInMeters is less than or equal to 4500",
 "BasisOfRecord is one of (Human Observation, Observation, Specimen, Material sample, Living Specimen)"
 ]
}

 The dataset includes 23 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079696-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17205311
title: A deep learning-based computational pipeline predicts developmental outcome in retinal organoids: classification images [sum projections]

description: Deposited are the source images as used in our publication to predict the tissue development of medaka organoids (https://www.biorxiv.org/content/10.1101/2025.02.19.639061v1).

 

The images are stored in our custom dataset format. In order to read it, you will need to clone the repo: https://github.com/TarikExner/orgAInoid

 

The code to import is the following:

```python

from orgAInoid.classification import OrganoidDataset

data = OrganoidDataset.read_classification_dataset("./path/to/file.cds")

// metadata are accessed via the .metadata attribute. The respective image array index is stored within this table.

data.metadata

//image arrays are stored at the .X and .y[readout] attribute, where attribute is one of "RPE_Final", "Lens_Final", "RPE_classes" and "Lens_classes"

 

For further information refer to the github repository.

```
DOI: 10.57702/abz0guxc
title: LASA-8D

description: We propose a novel methodology to learn neural contractive dynamical systems, where our neural architecture ensures contraction, and hence, global stability.
DOI: 10.57702/xvam4lh5
title: Multispectral Endoscopic Video

description: A video data source, such as multispectral video acquired during administration of fluorescent tracers
DOI: 10.15129/cb672ec6-07c6-4273-8843-7b2ee57a7ff4
title: Data for: "Institutionalizing from the Middle: the Impacts of Provincial Legislation on Rural Grassroots Democracy in China"

description: This dataset contains the author’s coding of provincial legislation related to rural democracy in China. The data are presented in graphical and HTML formats to facilitate replication and support future research.
DOI: 10.15468/dl.eqxryt
title: Occurrence Download

description: A dataset containing 14157455 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 14157455 records from 7546 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079642-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.