cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.5ymfd7
title: Occurrence Download

description: A dataset containing 2899969 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "PublishingOrg is c71f0513-c95a-4e98-abad-0c222b87ec66",
 "Year 2002-2024"
 ]
}

 The dataset includes 2899969 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074834-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2xp8b2
title: Occurrence Download

description: A dataset containing 270 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Omalotheca norvegica (Gunnerus) Sch.Bip. & F.W.Schultz",
 "MediaType is Image",
 "BasisOfRecord is Human Observation"
 ]
}

 The dataset includes 270 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0408645-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jz3mej
title: Occurrence Download

description: A dataset containing 708 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hyptidendron canum (Pohl ex Benth.) Harley"
 ]
}

 The dataset includes 708 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018115-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aphu6x
title: Occurrence Download

description: A dataset containing 327 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Rhizomys pruinosus Blyth, 1851"
 ]
}

 The dataset includes 327 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061620-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2hjdr4
title: Occurrence Download

description: A dataset containing 6584 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((-73.26199 -37.22031,-73.28636 -37.23095,-73.29975 -37.2337,-73.40343 -37.24812,-73.32649 -37.26299,-73.27469 -37.24543,-73.26851 -37.2453,-73.27572 -37.27249,-73.2649 -37.31741,-73.24585 -37.30099,-73.23864 -37.27215,-73.25581 -37.24571,-73.23864 -37.24468,-73.24757 -37.23301,-73.25684 -37.2155,-73.26199 -37.22031))",
 "Geometry POLYGON((-73.53726 -37.21931,-73.54021 -37.22522,-73.538 -37.23149,-73.52397 -37.23998,-73.50625 -37.24404,-73.4878 -37.26213,-73.48448 -37.27837,-73.46898 -37.28169,-73.45532 -37.28169,-73.4317 -37.27209,-73.42602 -37.25521,-73.43022 -37.23813,-73.43723 -37.22891,-73.49444 -37.22263,-73.51398 -37.20898,-73.53726 -37.21931))",
 "Geometry POLYGON((-73.30868 -37.29515,-73.31348 -37.28519,-73.32825 -37.28622,-73.33786 -37.29034,-73.33923 -37.2979,-73.33202 -37.30579,-73.3176 -37.30648,-73.30868 -37.30305,-73.30868 -37.29515))",
 "Geometry POLYGON((-73.36636 -37.31712,-73.3691 -37.29618,-73.37322 -37.29343,-73.38078 -37.29343,-73.39279 -37.30408,-73.39588 -37.31609,-73.36636 -37.31712))"
 ]
 },
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6584 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0103184-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t7qbkp
title: Occurrence Download

description: A dataset containing 972756 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-31.565747 48.58410666666667, 2.479608666666667 48.58410666666667, 2.479608666666667 65.67073733333334, -31.565747 65.67073733333334, -31.565747 48.58410666666667))",
 "EventDate is 2018-06-01,2018-06-30"
 ]
}

 The dataset includes 972756 records from 466 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014450-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qxarvo
title: Occurrence Download

description: A dataset containing 209263 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nardus stricta L."
 ]
}

 The dataset includes 209263 records from 393 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007490-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nhxzjj
title: Occurrence Download

description: A dataset containing 164027 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is HBRG Insects Dataset Vol 1"
 ]
}

 The dataset includes 164027 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126051-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.we4zh6
title: Occurrence Download

description: A dataset containing 1108 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Tragopan blythii (Jerdon, 1870)"
 ]
}

 The dataset includes 1108 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002070-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mqssln
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Prestonia hammelii J.F.Morales"
 ]
}

 The dataset includes 7 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012805-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tkn9xb
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Etheostoma smithi Page & Braasch, 1976"
 ]
}

 The dataset includes 82 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0348027-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jdm7e8
title: Occurrence Download

description: A dataset containing 65 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Boaedon bedriagae Boulenger, 1906"
 ]
}

 The dataset includes 65 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061640-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fi0ucy
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anthoceros caucasicus Steph."
 ]
}

 The dataset includes 55 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094852-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mzn6my
title: Occurrence Download

description: A dataset containing 421 species occurrences available in GBIF matching the query:
{
 "SpeciesKey" : [
 "is Rubroboletus legaliae (Pilát & Dermek) Della Magg. & Trassin."
 ]
}

 The dataset includes 421 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0129305-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fd4tqb
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pseudohydromys musseri (Flannery, 1989)"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014477-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.az6gv6
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.21_1",
 "TaxonKey is Bubo bubo (Linnaeus, 1758)"
 ]
}

 The dataset includes 16 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0138529-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v89hug
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Nosopsyllus londinensis londinensis)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043406-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d9y69g
title: Occurrence Download

description: A dataset containing 3543 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Country is Germany",
 "DecimalLongitude is greater than or equal to 13.0471013237746",
 "DecimalLongitude is less than 13.050160876959",
 "DecimalLatitude is greater than or equal to 47.27011",
 "DecimalLatitude is less than or equal to 55.05864"
 ]
}

 The dataset includes 3543 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014459-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mdmcya
title: Occurrence Download

description: A dataset containing 9463 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Diplostephium Kunth"
 ]
}

 The dataset includes 9463 records from 168 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0129306-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vscs7k
title: Occurrence Download

description: A dataset containing 878 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arbutus canariensis Duhamel"
 ]
}

 The dataset includes 878 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014509-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13283103
title: Daily cloud-gap-filled Terra–Aqua MODIS  NDSI dataset over High Mountain Asia (2000-2023)

description: 1. The daily cloud-gap-filled (CGF) MODIS normalized difference snow index (NDSI) dataset over High Mountain Asia (HMA) (2000-2023) is generated by combining of the cubic spline interpolation (CSI) method and the Spatio-Temporal Weighted (STW) method. This dataset is derived from daily 500 m MOD10A1 (Terra) and MYD10A1 (Aqua) products.

2. The cloud persistence days (CPD) dataset is also provided. The CPD represents the number of consecutive days of cloud observed for a pixel from the last cloud-free observation to the next cloud-free observation. And the CPD is used to determine the combination of CSI and STW method, which is expressed as: when CPD < 8 d, the CSI method is used; when CPD ≥ 8 d, the STW is used.

3. The CGF MODIS NDSI dataset is provided in ENVI standard format (.img) and the CPD dataset is provided in Geotiff format. And they are all provided in a geographic projection using the WGS84 coordinate system at a 0.005° (about 500 m) resolution. The NDSI value ranges from 0~100 and the CPD value ranges from 0~366. The fill value of both dataset is set to 255 (outside the track coverage of MODIS product).

4. The CGF MODIS NDSI dataset contains 24 compressed packages (named after the normal year) of the daily CGF MODIS NDSI dataset over HMA (2000-2023), and after uncompressing the files are named as “YYYYDDD_HMA_MODIS_NDSI_0.5km.img”. The CPD dataset contains 24 compressed packages (named after the normal year) of the daily CPD dataset over HMA (2000-2023), and after uncompressing the files are named as “YYYYDDD_CPD.tif”. The YYYY represents the year and the DDD represents Julian day (001-365/366).

5. The accuracy of this dataset has been well evaluated based on in-situ snow depth (SD) observations and high-resolution snow cover maps derived from Landsat images. The detailed information can be found in the paper (Deng, G., Tang, Z., Dong, C., Shao, D., & Wang, X. (2024). Development and Evaluation of a Cloud-Gap-Filled MODIS Normalized Difference Snow Index Product over High Mountain Asia. Remote Sensing, 16(1), 192. https://doi.org/10.3390/rs16010192).
DOI: 10.5281/zenodo.15241832
title: Daily cloud-gap-filled Terra–Aqua MODIS  NDSI dataset over High Mountain Asia (2000-2024)

description: 1. The daily cloud-gap-filled (CGF) MODIS normalized difference snow index (NDSI) dataset over High Mountain Asia (HMA) (2000-2024) is generated by combining of the cubic spline interpolation (CSI) method and the Spatio-Temporal Weighted (STW) method. This dataset is derived from daily 500 m MOD10A1 (Terra) and MYD10A1 (Aqua) products.

2. The cloud persistence days (CPD) dataset is also provided. The CPD represents the number of consecutive days of cloud observed for a pixel from the last cloud-free observation to the next cloud-free observation. And the CPD is used to determine the combination of CSI and STW method, which is expressed as: when CPD < 8 d, the CSI method is used; when CPD ≥ 8 d, the STW is used.

3. The CGF MODIS NDSI dataset is provided in ENVI standard format (.img) and the CPD dataset is provided in Geotiff format. And they are all provided in a geographic projection using the WGS84 coordinate system at a 0.005° (about 500 m) resolution. The NDSI value ranges from 0~100 and the CPD value ranges from 0~366. The fill value of both dataset is set to 255 (outside the track coverage of MODIS product).

4. The CGF MODIS NDSI dataset contains 25 compressed packages (named after the normal year) of the daily CGF MODIS NDSI dataset over HMA (2000-2024), and after uncompressing the files are named as “YYYYDDD_HMA_MODIS_NDSI_0.5km.img”. The CPD dataset contains 25 compressed packages (named after the normal year) of the daily CPD dataset over HMA (2000-2024), and after uncompressing the files are named as “YYYYDDD_CPD.tif”. The YYYY represents the year and the DDD represents Julian day (001-365/366).

5. The accuracy of this dataset has been well evaluated based on in-situ snow depth (SD) observations and high-resolution snow cover maps derived from Landsat images. The detailed information can be found in the paper (Deng, G., Tang, Z., Dong, C., Shao, D., & Wang, X. (2024). Development and Evaluation of a Cloud-Gap-Filled MODIS Normalized Difference Snow Index Product over High Mountain Asia. Remote Sensing, 16(1), 192. https://doi.org/10.3390/rs16010192).
DOI: 10.5281/zenodo.7341827
title: Daily cloud-gap-filled Terra–Aqua MODIS  NDSI dataset over High Mountain Asia (2000-2024)

description: 1. The daily cloud-gap-filled (CGF) MODIS normalized difference snow index (NDSI) dataset over High Mountain Asia (HMA) (2000-2024) is generated by combining of the cubic spline interpolation (CSI) method and the Spatio-Temporal Weighted (STW) method. This dataset is derived from daily 500 m MOD10A1 (Terra) and MYD10A1 (Aqua) products.

2. The cloud persistence days (CPD) dataset is also provided. The CPD represents the number of consecutive days of cloud observed for a pixel from the last cloud-free observation to the next cloud-free observation. And the CPD is used to determine the combination of CSI and STW method, which is expressed as: when CPD < 8 d, the CSI method is used; when CPD ≥ 8 d, the STW is used.

3. The CGF MODIS NDSI dataset is provided in ENVI standard format (.img) and the CPD dataset is provided in Geotiff format. And they are all provided in a geographic projection using the WGS84 coordinate system at a 0.005° (about 500 m) resolution. The NDSI value ranges from 0~100 and the CPD value ranges from 0~366. The fill value of both dataset is set to 255 (outside the track coverage of MODIS product).

4. The CGF MODIS NDSI dataset contains 25 compressed packages (named after the normal year) of the daily CGF MODIS NDSI dataset over HMA (2000-2024), and after uncompressing the files are named as “YYYYDDD_HMA_MODIS_NDSI_0.5km.img”. The CPD dataset contains 25 compressed packages (named after the normal year) of the daily CPD dataset over HMA (2000-2024), and after uncompressing the files are named as “YYYYDDD_CPD.tif”. The YYYY represents the year and the DDD represents Julian day (001-365/366).

5. The accuracy of this dataset has been well evaluated based on in-situ snow depth (SD) observations and high-resolution snow cover maps derived from Landsat images. The detailed information can be found in the paper (Deng, G., Tang, Z., Dong, C., Shao, D., & Wang, X. (2024). Development and Evaluation of a Cloud-Gap-Filled MODIS Normalized Difference Snow Index Product over High Mountain Asia. Remote Sensing, 16(1), 192. https://doi.org/10.3390/rs16010192).
DOI: 10.5281/zenodo.7341828
title: Daily cloud-gap-filled Terra–Aqua MODIS  NDSI dataset over High Mountain Asia (2000-2021)

description: 1. The daily cloud-gap-filled (CGF) MODIS normalized difference snow index (NDSI) dataset over High Mountain Asia (HMA) (2000-2021) is generated by combining of the cubic spline interpolation (CSI) method and the Spatio-Temporal Weighted (STW) method. This dataset is derived from daily 500 m MOD10A1 (Terra) and MYD10A1 (Aqua) products.

2. The cloud persistence days (CPD) dataset is also provided. The CPD represents the number of consecutive days of cloud observed for a pixel from the last cloud-free observation to the next cloud-free observation. And the CPD is used to determine the combination of CSI and STW method, which is expressed as: when CPD < 8 d, the CSI method is used; when CPD ≥ 8 d, the STW is used.

3. The CGF MODIS NDSI dataset is provided in ENVI standard format (.img) and the CPD dataset is provided in Geotiff format. And they are all provided in a geographic projection using the WGS84 coordinate system at a 0.005° (about 500 m) resolution. The NDSI value ranges from 0~100 and the CPD value ranges from 0~366. The fill value of both dataset is set to 255 (outside the track coverage of MODIS product).

4. The CGF MODIS NDSI dataset contains 22 compressed packages (named after the normal year) of the daily CGF MODIS NDSI dataset over HMA (2000-2021), and after uncompressing the files are named as “YYYYDDD_HMA_MODIS_NDSI_0.5km.img”. The CPD dataset contains 22 compressed packages (named after the normal year) of the daily CPD dataset over HMA (2000-2021), and after uncompressing the files are named as “YYYYDDD_CPD.tif”. The YYYY represents the year and the DDD represents Julian day (001-365/366).

5. The accuracy of this dataset has been well evaluated based on in-situ snow depth (SD) observations and high-resolution snow cover maps derived from Landsat images. The detailed information can be found in the paper (Deng, G., Tang, Z., Dong, C., Shao, D., & Wang, X. (2024). Development and Evaluation of a Cloud-Gap-Filled MODIS Normalized Difference Snow Index Product over High Mountain Asia. Remote Sensing, 16(1), 192. https://doi.org/10.3390/rs16010192).
DOI: 10.5281/zenodo.15241858
title: Alpha EEG Neurofeedback – Squat Performance and Training Status (Judokas 2024)

description: This dataset accompanies the research article titled "Effects of Alpha-Band EEG Neurofeedback on Load-Specific Squat Performance in Competitive Judokas: The Role of Training Status", which investigates the influence of alpha-band EEG neurofeedback on lower-body strength performance across varying load intensities (35%–100% 1RM) in elite male judokas.

The dataset includes:





Raw EEG data collected at F3 and F4 sites (10–20 system),




Computed Frontal Alpha Asymmetry Index (FAI),




Pre- and post-intervention squat performance data across five relative loads,




Stratification data for training groups (advanced vs. moderately trained),




Derived delta indices (ΔFAI, ΔReps),




Calculated neuromuscular efficiency metrics (ΔReps/ΔFAI),




Full R scripts used for data preprocessing, statistical analyses (RM-ANOVA, MANOVA, ANCOVA), and visualization.



The neurofeedback protocol involved 15 alpha-modulation sessions and was implemented over a 4–5-week period. All data have been de-identified in accordance with ethical guidelines and open science principles.

This repository was preregistered and timestamped prior to formal analysis to ensure full transparency and reproducibility. The materials adhere to the FAIR data principles and are openly accessible for replication and secondary analysis.
DOI: 10.5281/zenodo.15241859
title: Alpha EEG Neurofeedback – Squat Performance and Training Status (Judokas 2024)

description: This dataset accompanies the research article titled "Effects of Alpha-Band EEG Neurofeedback on Load-Specific Squat Performance in Competitive Judokas: The Role of Training Status", which investigates the influence of alpha-band EEG neurofeedback on lower-body strength performance across varying load intensities (35%–100% 1RM) in elite male judokas.

The dataset includes:





Raw EEG data collected at F3 and F4 sites (10–20 system),




Computed Frontal Alpha Asymmetry Index (FAI),




Pre- and post-intervention squat performance data across five relative loads,




Stratification data for training groups (advanced vs. moderately trained),




Derived delta indices (ΔFAI, ΔReps),




Calculated neuromuscular efficiency metrics (ΔReps/ΔFAI),




Full R scripts used for data preprocessing, statistical analyses (RM-ANOVA, MANOVA, ANCOVA), and visualization.



The neurofeedback protocol involved 15 alpha-modulation sessions and was implemented over a 4–5-week period. All data have been de-identified in accordance with ethical guidelines and open science principles.

This repository was preregistered and timestamped prior to formal analysis to ensure full transparency and reproducibility. The materials adhere to the FAIR data principles and are openly accessible for replication and secondary analysis.
DOI: 10.15468/dl.v46wz6
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen, Occurrence evidence)",
 "TaxonKey is Tulostoma nanum (Pat.) J.E.Wright"
 ]
}

 The dataset includes 68 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023232-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.