cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.xxh6gy
title: Occurrence Download

description: A dataset containing 30761 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is Vespa velutina",
 "Year is one of (2024, 2025)",
 "HasCoordinate is true",
 "Geometry POLYGON((3.5 43.5, 12.5 43.5, 12.5 50.5, 3.5 50.5, 3.5 43.5))"
 ]
}

 The dataset includes 30761 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045793-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17886248
title: Radiosonde dataset of:  Integrating Fireline Observations to Characterize Fire Plumes During Pyroconvective Extreme Wildfire Events: Implications for Firefighter Safety and Plume Modeling (Campaigns 2021-2025)

description: Set of radiosonde files (CSV) for in-plume and ambient radiosondes launched during wildfires to assess pyroconvection. 

Files are organized in in-plume (sondes launched into the updraft of the plume) and ambient (sondes launched outside the fire)

More information in the EWED project data portal:  http://wildfiredataportal.eu/
DOI: 10.5281/zenodo.17886250
title: Radiosonde dataset of:  Integrating Fireline Observations to Characterize Fire Plumes During Pyroconvective Extreme Wildfire Events: Implications for Firefighter Safety and Plume Modeling (Campaigns 2021-2025)

description: Set of radiosonde files (CSV) for in-plume and ambient radiosondes launched during wildfires to assess pyroconvection. 

Files are organized in in-plume (sondes launched into the updraft of the plume) and ambient (sondes launched outside the fire)

More information in the EWED project data portal:  http://wildfiredataportal.eu/
DOI: 10.7924/r40c57d8w
title: Data from: Correcting Delocalization Error in Materials with Localized Orbitals and Linear-Response Screening

description: This dataset includes R scripts for generating figures from the manuscript: calculated vs. experimental plot of fundamental gaps, band structures. Band structures are computed from data output by wannier90 and lrLOSC, a module for a local fork of the Quantum ESPRESSO suite. This data package also includes some CSV files with input data (total energies, frontier eigenvalues, lattice parameters) extracted from Quantum ESPRESSO and lrLOSC or input by hand. Abstract of the preprint: Delocalization error prevents density functional theory (DFT) from reaching its full potential, causing problems like systematically underestimated band gaps and misaligned energy levels at interfaces. We introduce lrLOSC to correct delocalization error in materials over a wide range of band gaps. We predict eleven materials' fundamental gaps to within 0.28 eV, while offering a nonzero correction to the total energy. Molecular properties are improved with the same theory (arXiv:2406.06345). lrLOSC is an essential step toward modeling molecules, materials, and their interfaces within the same DFT framework.
DOI: 10.15468/dl.pajvgr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Syllis brevicirrata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045796-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.17414885
title: Climate Risk Analysis Related to Urban Heat Islands in Metropolitan Areas for Urban Health: The Case Study of The Florence Plain - Supplementary materials

description: This dataset supports research aimed at developing a model for assessing and tackling climate risk associated with Urban Heat Islands (UHI) in the Piana Fiorentina area. The study focuses on areas where thermal stress and population sensitivity are especially high, making heat-reduction interventions a priority.

Climate risk is determined by the interaction of three key factors: Hazard, Exposure, and Vulnerability. In the context of heatwaves, the hazard refers to the rise in temperatures. Exposure relates to the presence of people or assets in areas affected by such extreme events, typically measured using census data that show how population is distributed across impacted zones. Vulnerability reflects the limited ability of individuals or communities to cope with or adapt to extreme heat, influenced by factors such as age, health conditions, and urban characteristics (e.g., the availability of adequate infrastructure). By combining these three components, it's possible to create a comprehensive risk map, integrating a hazard index with indicators of exposure and vulnerability. Tools like the Land Surface Temperature (LST) index, play a crucial role in supporting urban planning interventions aimed at reducing the environmental and public health impacts of extreme heat.

The dataset includes spatial and tabular data used to construct the risk model, comprising raster layers (e.g., Land Surface Temperature and NDVI indices) and vector data derived from census and urban planning sources. Files are provided in open formats to facilitate interoperability and reuse. The data can be used to reproduce the analyses presented in the related research and to support further studies on climate adaptation and urban resilience.
DOI: 10.5281/zenodo.17414886
title: Climate Risk Analysis Related to Urban Heat Islands in Metropolitan Areas for Urban Health: The Case Study of The Florence Plain - Supplementary materials

description: This dataset supports research aimed at developing a model for assessing and tackling climate risk associated with Urban Heat Islands (UHI) in the Piana Fiorentina area. The study focuses on areas where thermal stress and population sensitivity are especially high, making heat-reduction interventions a priority.

Climate risk is determined by the interaction of three key factors: Hazard, Exposure, and Vulnerability. In the context of heatwaves, the hazard refers to the rise in temperatures. Exposure relates to the presence of people or assets in areas affected by such extreme events, typically measured using census data that show how population is distributed across impacted zones. Vulnerability reflects the limited ability of individuals or communities to cope with or adapt to extreme heat, influenced by factors such as age, health conditions, and urban characteristics (e.g., the availability of adequate infrastructure). By combining these three components, it's possible to create a comprehensive risk map, integrating a hazard index with indicators of exposure and vulnerability. Tools like the Land Surface Temperature (LST) index, play a crucial role in supporting urban planning interventions aimed at reducing the environmental and public health impacts of extreme heat.

The dataset includes spatial and tabular data used to construct the risk model, comprising raster layers (e.g., Land Surface Temperature and NDVI indices) and vector data derived from census and urban planning sources. Files are provided in open formats to facilitate interoperability and reuse. The data can be used to reproduce the analyses presented in the related research and to support further studies on climate adaptation and urban resilience.
DOI: 10.15468/dl.qp5cfn
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((104.941 -2.405825, 104.870675 -2.41139, 104.80208 -2.427948, 104.736902 -2.455092, 104.676745 -2.492154, 104.623089 -2.538222, 104.577255 -2.592162, 104.540372 -2.652649, 104.513348 -2.718192, 104.49685 -2.787179, 104.491287 -2.857912, 104.496796 -2.928648, 104.513245 -2.997648, 104.54023 -3.06321, 104.577088 -3.123721, 104.622913 -3.177688, 104.676578 -3.223783, 104.73676 -3.260869, 104.801977 -3.288032, 104.870621 -3.304602, 104.941 -3.310172, 105.011379 -3.304602, 105.080023 -3.288032, 105.14524 -3.260869, 105.205422 -3.223783, 105.259087 -3.177688, 105.304912 -3.123721, 105.34177 -3.06321, 105.368755 -2.997648, 105.385204 -2.928648, 105.390713 -2.857912, 105.38515 -2.787179, 105.368652 -2.718192, 105.341628 -2.652649, 105.304745 -2.592162, 105.258911 -2.538222, 105.205255 -2.492154, 105.145098 -2.455092, 105.07992 -2.427948, 105.011325 -2.41139, 104.941 -2.405825))"},{"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 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045797-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17886593
title: Climate web app provenance run run_20251210T213758Z

description: Run-level provenance artefacts (OpenLineage JSONL, enriched JSON, session Parquet, PROV-O TTL graph, and TTL graph PNG) captured from the Climate dashboard.
DOI: 10.5281/zenodo.17886592
title: Climate web app provenance run run_20251210T213758Z

description: Run-level provenance artefacts (OpenLineage JSONL, enriched JSON, session Parquet, PROV-O TTL graph, and TTL graph PNG) captured from the Climate dashboard.
DOI: 10.15468/dl.bwm23v
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((-100.17891 25.70573,-100.17732 25.70573,-100.17732 25.70722,-100.17891 25.70722,-100.17891 25.70573))",
 "Geometry POLYGON((-100.18349 25.70139,-100.17326 25.70139,-100.17326 25.7115,-100.18349 25.7115,-100.18349 25.70139))"
 ]
 },
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 31 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045798-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13139/olcf/2998539
title: Dataset for manuscript "Equipartition and the temperature of maximum density of TIP4P/2005 water"

description: We simulate TIP4P/2005 water in the temperature range of 257 K to 318 K with time-steps
0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density-temperature behavior obtained using 0.25 or 0.50 fs are in excellent agreement with each other but differ from those obtained using time-steps that have been shown earlier to lead to a breakdown of equipartition.  The temperature of maximum density (TMD) is 277.15 K with time-step 0.25 or 0.50 fs, but is shifted to progressively lower values for longer time-steps, a trend that holds for different thermostat/barostat combinations.  Enhancing the water-water dispersion interaction, as has been recommended for simulating disordered proteins in TIP4P/2005, degrades the description of the liquid-vapor phase envelope. We present a simple physically transparent reasoning to highlight the separation of the time-scales between translational and rotational motion. We also develop a metric, Chi, that we term the equipartition anomaly, to detect equipartition violations in simulations that include molecules that are treated as rigid objects. Calculating Chi is shown to be straightforward and sensitive to equipartition violations. A key takeaway from this study is that using sufficiently short time-steps (less than or equal to 0.5 fs) to preserve equipartition is essential for obtaining meaningful liquid water properties and for producing reliable simulation data, as correct-ensemble sampling is fundamental to ensure reproducibility across codes and simulation alogrithms. 

The included dataset provides the raw data used in the preparation of the graphs noted in the manuscript.
DOI: 10.6084/m9.figshare.30854279
title: Supplementary Dataset for "<i>Brachyspira burroughii</i> sp. nov., a novel intestinal spirochete isolated from pigs during swine dysentery surveillance: genomic and phenotypic characteristics"

description: This dataset contains supplementary materials associated with the manuscript describing the genomic, phenotypic, and phylogenetic characterization of <i>Brachyspira burroughii</i> sp. nov. Provided files include supplementary figures, metadata tables, reference gene accessions, and additional supporting data referenced in the main text.
DOI: 10.6084/m9.figshare.30854279.v1
title: Supplementary Dataset for "<i>Brachyspira burroughii</i> sp. nov., a novel intestinal spirochete isolated from pigs during swine dysentery surveillance: genomic and phenotypic characteristics"

description: This dataset contains supplementary materials associated with the manuscript describing the genomic, phenotypic, and phylogenetic characterization of <i>Brachyspira burroughii</i> sp. nov. Provided files include supplementary figures, metadata tables, reference gene accessions, and additional supporting data referenced in the main text.
DOI: 10.15468/qghvbp
title: Glaridoglanis verruciloba sp. nov., a new glyptosternine catfish (Siluriformes, Sisoridae) from the Zayul River in southeastern Tibet, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Gong, Zheng, Wang, Huanshan, Liu, Yanchao, Li, Jianchuan (2025): Glaridoglanis verruciloba sp. nov., a new glyptosternine catfish (Siluriformes, Sisoridae) from the Zayul River in southeastern Tibet, China. ZooKeys 1262: 289-301, DOI: 10.3897/zookeys.1262.172819AbstractGlaridoglanis verruciloba sp. nov. is described from the Zayul River in southeastern Tibet, China. It has long been misidentified as G. andersonii. This new species is diagnosed by the following combination of characters: an enlarged lower lip bearing 4–7 verruciform lobes on the central-posterior margin; an anus situated close to the origin of the anal fin; the ventral surface at the base of maxillary barbels densely covered with striae; 11 branched pectoral-fin rays; 5–6 branched anal-fin rays; and relatively short mandibular barbels. Molecular phylogenetic analyses of mitochondrial cytochrome b sequences further supported the validity of this new species, which is within a well-supported clade with substantial genetic divergence from G. andersonii.
DOI: 10.34740/kaggle/dsv/14098147
title: Indonesian Hoax News Dataset
DOI: 10.15468/dl.qq6k3v
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((104.164 -2.396825, 104.093676 -2.40239, 104.025081 -2.418948, 103.959904 -2.446092, 103.899747 -2.483154, 103.846092 -2.529222, 103.800258 -2.583163, 103.763375 -2.643649, 103.736351 -2.709192, 103.719854 -2.778179, 103.71429 -2.848912, 103.7198 -2.919649, 103.736248 -2.988648, 103.763233 -3.05421, 103.800091 -3.114721, 103.845916 -3.168688, 103.89958 -3.214783, 103.959762 -3.251869, 104.024978 -3.279032, 104.093621 -3.295602, 104.164 -3.301172, 104.234379 -3.295602, 104.303022 -3.279032, 104.368238 -3.251869, 104.42842 -3.214783, 104.482084 -3.168688, 104.527909 -3.114721, 104.564767 -3.05421, 104.591752 -2.988648, 104.6082 -2.919649, 104.61371 -2.848912, 104.608146 -2.778179, 104.591649 -2.709192, 104.564625 -2.643649, 104.527742 -2.583163, 104.481908 -2.529222, 104.428253 -2.483154, 104.368096 -2.446092, 104.302919 -2.418948, 104.234324 -2.40239, 104.164 -2.396825))"},{"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/0045800-251120083545085/datasets/export for details.
DOI: 10.15468/dl.amjnme
title: Occurrence Download

description: A dataset containing 95 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Syllis licheri",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 95 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045799-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j7uhka
title: Occurrence Download

description: A dataset containing 4958 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cardinalis cardinalis cardinalis"
 ]
}

 The dataset includes 4958 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045801-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17379716
title: The Dai Downstream River Flow and Continental Discharge Dataset

description: This is the dataset from the following study submitted to Earth System Science Data (ESSD) in October 2025:

Dai, A., J. Hu, A. Duan, X. Guo, M. Liu, R. Liang, G. Wang, and M. Dai 2025: A Dataset of Global Streamflow and Continental Runoff: An Update to 2024.Scientific Data, submitted, Dec 2025. 

This is an updated version of the Dai and Trenberth Global River Flow and Continental Discharge Dataset available from NCAR at https://gdex.ucar.edu/datasets/d551000/ . It contains monthly flow time series up to Dec 2024 at the farthest downstream station for world's 936 largest rivers, plus annual global continental freshwater discharge since 1948, and annual freshwater discharge through each 1x1degree coastal box into ocean. Read readme.txt for more information.  Contact: Prof. Aiguo Dai, University at Albany, SUNY (adai@albany.edu). 

How to cite this dataset: 

Dai, A., J. Hu, A. Duan, X. Guo, M. Liu, R. Liang, G. Wang, and M. Dai 2025: Dai Downstream River Flow and Continental Discharge Dataset. Zenodo, DOI: 10.5281/zenodo.17379716. https://zenodo.org/uploads/17379716 

Related documention: 

Dai, A., J. Hu, A. Duan, X. Guo, M. Liu, R. Liang, G. Wang, and M. Dai 2025: Global Downstream River Flows and Continental Runoff: An Update to 2024.J. Hydrometeorology, submitted.
DOI: 10.5281/zenodo.17379715
title: The Dai Downstream River Flow and Continental Discharge Dataset

description: This is the dataset from the following study submitted to Earth System Science Data (ESSD) in October 2025:

Dai, A., J. Hu, A. Duan, X. Guo, M. Liu, R. Liang, G. Wang, and M. Dai 2025: A Dataset of Global Streamflow and Continental Runoff: An Update to 2024.Scientific Data, submitted, Dec 2025. 

This is an updated version of the Dai and Trenberth Global River Flow and Continental Discharge Dataset available from NCAR at https://gdex.ucar.edu/datasets/d551000/ . It contains monthly flow time series up to Dec 2024 at the farthest downstream station for world's 936 largest rivers, plus annual global continental freshwater discharge since 1948, and annual freshwater discharge through each 1x1degree coastal box into ocean. Read readme.txt for more information.  Contact: Prof. Aiguo Dai, University at Albany, SUNY (adai@albany.edu). 

How to cite this dataset: 

Dai, A., J. Hu, A. Duan, X. Guo, M. Liu, R. Liang, G. Wang, and M. Dai 2025: Dai Downstream River Flow and Continental Discharge Dataset. Zenodo, DOI: 10.5281/zenodo.17379716. https://zenodo.org/uploads/17379716 

Related documention: 

Dai, A., J. Hu, A. Duan, X. Guo, M. Liu, R. Liang, G. Wang, and M. Dai 2025: Global Downstream River Flows and Continental Runoff: An Update to 2024.J. Hydrometeorology, submitted.
DOI: 10.15468/dl.tpgnxe
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((104.266 -2.396825, 104.195676 -2.40239, 104.127081 -2.418948, 104.061904 -2.446092, 104.001747 -2.483154, 103.948092 -2.529222, 103.902258 -2.583163, 103.865375 -2.643649, 103.838351 -2.709192, 103.821854 -2.778179, 103.81629 -2.848912, 103.8218 -2.919649, 103.838248 -2.988648, 103.865233 -3.05421, 103.902091 -3.114721, 103.947916 -3.168688, 104.00158 -3.214783, 104.061762 -3.251869, 104.126978 -3.279032, 104.195621 -3.295602, 104.266 -3.301172, 104.336379 -3.295602, 104.405022 -3.279032, 104.470238 -3.251869, 104.53042 -3.214783, 104.584084 -3.168688, 104.629909 -3.114721, 104.666767 -3.05421, 104.693752 -2.988648, 104.7102 -2.919649, 104.71571 -2.848912, 104.710146 -2.778179, 104.693649 -2.709192, 104.666625 -2.643649, 104.629742 -2.583163, 104.583908 -2.529222, 104.530253 -2.483154, 104.470096 -2.446092, 104.404919 -2.418948, 104.336324 -2.40239, 104.266 -2.396825))"},{"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/0045802-251120083545085/datasets/export for details.
DOI: 10.15468/dl.wwb9de
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chone gracilis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 26 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045803-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r3tq35
title: Occurrence Download

description: A dataset containing 225991 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-33.52793 42.62552,-34.6292 34.85126,-30.44101 15.46872,-26.15542 11.37794,-22.55163 11.52404,-18.31475 14.15383,-20.31144 20.92311,-16.07456 26.03659,-13.44477 27.83848,-12.61687 28.56898,-12.81167 32.70846,-17.15706 41.58279,-33.52793 42.62552))",
 "TaxonKey is Bryophyta"
 ]
}

 The dataset includes 225991 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045771-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14098176
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.cq7gs4
title: Occurrence Download

description: A dataset containing 157 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is one of (Brazil, Peru)",
 "TaxonKey is Saguinus imperator"
 ]
}

 The dataset includes 157 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045804-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.