cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18325891
title: Satellite-derived Ecosystem Functional Types of Europe

description: This dataset contains the spatial map of satellite-derived Ecosystem Functional Types (EFTs) for Europe, generated from time series (2001–2014) of the Enhanced Vegetation Index (EVI) derived from the MODIS MOD13Q1 product. EFTs represent groups of ecosystems or land surface patches that share similar temporal dynamics of matter and energy exchanges, providing a functional classification of ecosystems based on satellite observations. The study area corresponds to the area defined in the associated manuscript (Cazorla et al., 2026, Biogeosciences), for which the EFTs were derived and analysed. The dataset was developed to assess spatial heterogeneity and interannual variability in ecosystem functioning at regional scales.

In the associated study (Cazorla et al., 2026, Biogeosciences), EFT classes were evaluated against measurements of Net Ecosystem Exchange (NEE) of CO₂ obtained using the Eddy Covariance technique across multiple European sites. Results show that distinct EFT classes exhibit significantly different magnitudes and seasonal dynamics of NEE and that EFTs perform marginally better than Plant Functional Types (PFTs) in explaining regional patterns of carbon exchange. Compared to land-cover or PFT-based classifications, satellite-derived EFTs offer several key advantages: they are directly based on observed ecosystem dynamics, are sensitive to short-term changes in ecosystem performance (e.g. droughts or disturbances), and can be recalculated annually in a consistent and repeatable manner. These properties make EFTs particularly suitable for monitoring interannual changes in ecosystem functioning and functional diversity over large regions.
description: Spatial resolution: ≈ 231 meters




Coordinate reference system: EPSG:4326 - WGS 84 - Geographic




Temporal coverage: 2001–2014




File format: GeoTIFF




Data values and legend:Raster values range from 1 to 64, where each integer value represents a distinct Ecosystem Functional Type (EFT). Each numeric code corresponds to an alphanumeric EFT code (from Aa1 to Dd4), as defined in Cazorla et al. (2026, Biogeosciences).

EFTs are named using two letters and one number, which describe key functional characteristics derived from EVI time series:





The first (uppercase) letter indicates primary production, based on mean EVI values (EVI_mean), increasing from A (low productivity) to D (high productivity).




The second (lowercase) letter represents seasonality, based on the seasonal standard deviation of EVI (EVI_sSD), decreasing from a (high seasonality) to d (low seasonality).




The number is a phenological indicator of the timing of the growing season peak (EVI_DMAX):1 = spring, 2 = summer, 3 = autumn, 4 = winter.
DOI: 10.5281/zenodo.18325889
title: Satellite-derived Ecosystem Functional Types of Europe

description: This dataset contains the spatial map of satellite-derived Ecosystem Functional Types (EFTs) for Europe, generated from time series (2001–2014) of the Enhanced Vegetation Index (EVI) derived from the MODIS MOD13Q1 product. EFTs represent groups of ecosystems or land surface patches that share similar temporal dynamics of matter and energy exchanges, providing a functional classification of ecosystems based on satellite observations. The study area corresponds to the area defined in the associated manuscript (Cazorla et al., 2026, Biogeosciences), for which the EFTs were derived and analysed. The dataset was developed to assess spatial heterogeneity and interannual variability in ecosystem functioning at regional scales.

In the associated study (Cazorla et al., 2026, Biogeosciences), EFT classes were evaluated against measurements of Net Ecosystem Exchange (NEE) of CO₂ obtained using the Eddy Covariance technique across multiple European sites. Results show that distinct EFT classes exhibit significantly different magnitudes and seasonal dynamics of NEE and that EFTs perform marginally better than Plant Functional Types (PFTs) in explaining regional patterns of carbon exchange. Compared to land-cover or PFT-based classifications, satellite-derived EFTs offer several key advantages: they are directly based on observed ecosystem dynamics, are sensitive to short-term changes in ecosystem performance (e.g. droughts or disturbances), and can be recalculated annually in a consistent and repeatable manner. These properties make EFTs particularly suitable for monitoring interannual changes in ecosystem functioning and functional diversity over large regions.
description: Spatial resolution: ≈ 231 meters




Coordinate reference system: EPSG:4326 - WGS 84 - Geographic




Temporal coverage: 2001–2014




File format: GeoTIFF




Data values and legend:Raster values range from 1 to 64, where each integer value represents a distinct Ecosystem Functional Type (EFT). Each numeric code corresponds to an alphanumeric EFT code (from Aa1 to Dd4), as defined in Cazorla et al. (2026, Biogeosciences).

EFTs are named using two letters and one number, which describe key functional characteristics derived from EVI time series:





The first (uppercase) letter indicates primary production, based on mean EVI values (EVI_mean), increasing from A (low productivity) to D (high productivity).




The second (lowercase) letter represents seasonality, based on the seasonal standard deviation of EVI (EVI_sSD), decreasing from a (high seasonality) to d (low seasonality).




The number is a phenological indicator of the timing of the growing season peak (EVI_DMAX):1 = spring, 2 = summer, 3 = autumn, 4 = winter.
DOI: 10.15468/dl.akgrgx
title: Occurrence Download

description: A dataset containing 551 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Equus kiang"
 ]
}

 The dataset includes 551 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002412-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e2dpz4
title: Occurrence Download

description: A dataset containing 42346 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Chenopodiastrum hybridum"
 ]
}

 The dataset includes 42346 records from 724 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002413-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/sk55-nh15
title: "PIRLS-HK - Traditional Chinese reading comprehension question-answer dataset"

description: "The PIRLS-HK dataset was created to address the lack of a realistic benchmark for evaluating large language models (LLMs) on automated short-answer grading (ASAG) for Traditional Chinese K-12 reading comprehension tasks. Existing benchmarks focused on encyclopedic\/STEM knowledge, multiple-choice formats, or Simplified Chinese\/English, leaving Traditional Chinese ASAG underexplored."
DOI: 10.5281/zenodo.18326111
title: measurements

description: This file contains all the measurements taken from all the images included in the study, as well as the findings obtained from those images.
DOI: 10.5281/zenodo.18325482
title: measurements

description: This file contains all the measurements taken from all the images included in the study, as well as the findings obtained from those images.
DOI: 10.15468/dl.ykwas4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((100.642 1.587182, 100.57171 1.581614, 100.503153 1.565047, 100.438015 1.537889, 100.377904 1.50081, 100.324298 1.454722, 100.278517 1.400761, 100.24169 1.340257, 100.214721 1.274699, 100.198275 1.205702, 100.192755 1.134965, 100.198296 1.064229, 100.214762 0.995237, 100.241746 0.929687, 100.278584 0.869192, 100.324367 0.815242, 100.37797 0.769165, 100.438072 0.7320950000000001, 100.503194 0.704945, 100.571732 0.688383, 100.642 0.682816, 100.712268 0.688383, 100.780806 0.704945, 100.845928 0.7320950000000001, 100.90603 0.769165, 100.959633 0.815242, 101.005416 0.869192, 101.042254 0.929687, 101.069238 0.995237, 101.085704 1.064229, 101.091245 1.134965, 101.085725 1.205702, 101.069279 1.274699, 101.04231 1.340257, 101.005483 1.400761, 100.959702 1.454722, 100.906096 1.50081, 100.845985 1.537889, 100.780847 1.565047, 100.71229 1.581614, 100.642 1.587182))"},{"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/0002415-260120142942310/datasets/export for details.
DOI: 10.15468/dl.44mg6e
title: Occurrence Download

description: A dataset containing 280 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((5.0209213694869845 49.9998833333843, 5.020555239341324 50.00251649174769, 5.01939905959571 50.00505300691112, 5.017497151457214 50.00739537921816, 5.014922529528398 50.00945355798019, 5.01177410728109 50.011148407346525, 5.008172900116075 50.01241475372375, 5.004257371270753 50.0132038966786, 5.000178099964654 50.01348548586882, 4.996091978326072 50.013248691049476, 4.992156162608852 50.01250261963375, 4.988522014126121 50.0112759655543, 4.985329265743159 50.009615903093746, 4.982700640665879 50.0075862687246, 4.9807371320514 50.005265101633476, 4.97951412548017 50.00274163840301, 4.979078512750277 50.00011287830588, 4.979446906255965 49.997479852026096, 4.980605020068763 49.99494373775343, 4.982508238537429 49.992601974112404, 4.985083347573486 49.99054451912769, 4.988231359547377 49.98885039846148, 4.991831321518648 49.98758467476916, 4.9957449598193255 49.98679595368592, 4.999821983048193 49.98651452132783, 5.003905841326411 49.98675118406352, 5.007839722976298 49.98749685458843, 5.011472561128986 49.98872290000188, 5.014664822405033 49.990382238685065, 5.0172938577560675 49.9924111443541, 5.01925861156444 49.994731688760346, 5.020483508680185 49.997254730119266, 5.0209213694869845 49.9998833333843))",
 "KingdomKey is one of (Animalia, Fungi, Plantae)",
 "Year is one of (2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026)"
 ]
}

 The dataset includes 280 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002417-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hxzn6h
title: Occurrence Download

description: A dataset containing 751 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Laterallus flaviventer"
 ]
}

 The dataset includes 751 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002416-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y24pxw
title: Occurrence Download

description: A dataset containing 100 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Dragonfly records from the British Dragonfly Society Recording Scheme",
 "Geometry POLYGON((-23.72229 46.51472,18.72229 46.51472,18.72229 63.48528,-23.72229 63.48528,-23.72229 46.51472))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Gomphus vulgatissimus",
 "Year 2024-2024"
 ]
}

 The dataset includes 100 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002422-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2ggn2n
title: Occurrence Download

description: A dataset containing 89 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-73.27200000000001 4.163163, -73.34244700000001 4.157594, -73.411157 4.141022, -73.476435 4.113856, -73.536672 4.076767, -73.590383 4.030669, -73.636246 3.976698, -73.673132 3.916185, -73.70013400000001 3.850621, -73.716589 3.781621, -73.722095 3.710885, -73.71651900000001 3.640154, -73.69999900000001 3.57117, -73.67294699999999 3.505631, -73.636028 3.445149, -73.590154 3.391214, -73.53645400000001 3.34515, -73.47624999999999 3.308093, -73.411022 3.280952, -73.342376 3.264396, -73.27200000000001 3.258832, -73.201624 3.264396, -73.13297799999999 3.280952, -73.06775 3.308093, -73.007546 3.34515, -72.953846 3.391214, -72.907972 3.445149, -72.871053 3.505631, -72.84400100000001 3.57117, -72.82748100000001 3.640154, -72.821905 3.710885, -72.827411 3.781621, -72.84386600000001 3.850621, -72.870868 3.916185, -72.907754 3.976698, -72.95361699999999 4.030669, -73.007328 4.076767, -73.067565 4.113856, -73.13284299999999 4.141022, -73.201553 4.157594, -73.27200000000001 4.163163))"},{"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 89 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002424-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n3s6wj
title: Occurrence Download

description: A dataset containing 438 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Kenya",
 "TaxonKey is Kleinia"
 ]
}

 The dataset includes 438 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002426-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18257755
title: Dichlorophen makes Escherichia coli sensitive to colistin by disrupting the integrity of membranes

description: Supplementary material
DOI: 10.15468/dl.qt238g
title: Occurrence Download

description: A dataset containing 58827 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Myotis myotis)",
 "OccurrenceStatus is Present",
 "SpeciesKey is not null",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2026",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 },
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation)"
 ]
}

 The dataset includes 58827 records from 1208 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002378-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15395704
title: Dataset: Combined Toxicity of Cyanotoxins and Anthropogenic Contaminants on Chlorella vulgaris Insights from Single and Binary Mixture Exposures

description: This is the dataset from the scientific article Combined Toxicity of Cyanotoxins and Anthropogenic Contaminants on Chlorella vulgaris: Insights from Single and Binary Mixture Exposures. It contains ecotoxicological data of the microalgae Chlorella vulgaris exposed to microcystin-LR, cylindrospermopsin, terbuthylazine and cadmium in single-compound exposures, and in five binary mixture exposures: MC-LR and TBA; MC-LR and Cd; CYN and TBA; CYN and Cd; and TBA and Cd.
DOI: 10.5281/zenodo.15395705
title: Dataset: Combined Toxicity of Cyanotoxins and Anthropogenic Contaminants on Chlorella vulgaris Insights from Single and Binary Mixture Exposures

description: This is the dataset from the scientific article Combined Toxicity of Cyanotoxins and Anthropogenic Contaminants on Chlorella vulgaris: Insights from Single and Binary Mixture Exposures. It contains ecotoxicological data of the microalgae Chlorella vulgaris exposed to microcystin-LR, cylindrospermopsin, terbuthylazine and cadmium in single-compound exposures, and in five binary mixture exposures: MC-LR and TBA; MC-LR and Cd; CYN and TBA; CYN and Cd; and TBA and Cd.
DOI: 10.15468/dl.wmqqn3
title: Occurrence Download

description: A dataset containing 43584 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 Atropa belladonna L."
 ]
}

 The dataset includes 43584 records from 428 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003859-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yy2ae6
title: Occurrence Download

description: A dataset containing 1006 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Polygonatum cyrtonema Hua"
 ]
}

 The dataset includes 1006 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006613-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15544632
title: Human from an Articulated Robot Perspective: the HARPER dataset

description: The HARPER dataset is a novel corpus for 3D human body pose estimation and forecasting specifically captured from a quadruped robot’s sensors, offering a unique “robot’s-eye” perspective. It consists of synchronized recordings from Spot’s built-in stereo cameras and a 6-camera OptiTrack motion-capture system, covering 15 interactive actions (10 of which involve physical contact). Alongside the raw data, HARPER provides benchmark splits and evaluation protocols for 3D pose estimation, pose forecasting, and collision-prediction tasks, facilitating reproducible research and direct comparison with published baselines.

Offers:





Robot-Centric ViewpointHARPER focuses on data captured by Boston Dynamics’ quadruped robot Spot, whose low vantage point leads to partial occlusions and unusual viewing angles that challenge standard pose-estimation models




Actions and InteractionsThe dataset includes 15 predefined action classes (e.g., walking, avoiding, physical contact), with 10 classes involving direct human–robot contact, recorded in dyadic interactions between a human subject and the robot




Multi-Sensor SetupEach sequence is captured simultaneously by Spot’s stereo cameras and a high-precision OptiTrack system, yielding sub-millimeter-accurate 3D skeletal ground truth




Benchmarks IncludedHARPER ships with standardized splits and baseline results for three tasks:





3D Human Pose Estimation




Human Pose Forecasting




Collision PredictionThis ensures that future methods can be evaluated directly against the published baselines
DOI: 10.5281/zenodo.15544633
title: Human from an Articulated Robot Perspective: the HARPER dataset

description: The HARPER dataset is a novel corpus for 3D human body pose estimation and forecasting specifically captured from a quadruped robot’s sensors, offering a unique “robot’s-eye” perspective. It consists of synchronized recordings from Spot’s built-in stereo cameras and a 6-camera OptiTrack motion-capture system, covering 15 interactive actions (10 of which involve physical contact). Alongside the raw data, HARPER provides benchmark splits and evaluation protocols for 3D pose estimation, pose forecasting, and collision-prediction tasks, facilitating reproducible research and direct comparison with published baselines.

Offers:





Robot-Centric ViewpointHARPER focuses on data captured by Boston Dynamics’ quadruped robot Spot, whose low vantage point leads to partial occlusions and unusual viewing angles that challenge standard pose-estimation models




Actions and InteractionsThe dataset includes 15 predefined action classes (e.g., walking, avoiding, physical contact), with 10 classes involving direct human–robot contact, recorded in dyadic interactions between a human subject and the robot




Multi-Sensor SetupEach sequence is captured simultaneously by Spot’s stereo cameras and a high-precision OptiTrack system, yielding sub-millimeter-accurate 3D skeletal ground truth




Benchmarks IncludedHARPER ships with standardized splits and baseline results for three tasks:





3D Human Pose Estimation




Human Pose Forecasting




Collision PredictionThis ensures that future methods can be evaluated directly against the published baselines
DOI: 10.17603/ds2-59g8-fh80
title: Post-Disaster Housing Recovery Data from the 2017 Tubbs and 2018 Camp Fires

description: Data sets including parcel level information related to housing reconstruction in Santa Rosa, Unincorporated Sonoma County, and Paradise following the Tubbs Fires and Camp Fires.
DOI: 10.17603/ds2-26gf-dn35
title: FEMA P-2335: Visual Damage States Databases of Reinforced Concrete Components

description: Welcome to the Visual Damage States Databases of Reinforced Concrete Components! The key purpose of the databases is to facilitate the inspection process and damage classification of earthquake-damaged components using experimental data from laboratory tests that document damage as a function of prescribed damage states and damage classes. These databases are a collection of experimental testing programs on various reinforced concrete (RC) components with damage progression photographs. These databases are used in the application of FEMA P-2335 as part of the guidelines for post-earthquake assessment of damaged RC structures. The work forming the basis for this publication was conducted pursuant to a contract with the Federal Emergency Management Agency. The substance of such work is dedicated to the public. The authors are solely responsible for the accuracy of statements or interpretations contained in this publication. No warranty is offered with regard to the results, findings, and recommendations contained herein, either by the Federal Emergency Management Agency, the Applied Technology Council, its directors, members, or employees. These organizations and individuals do not assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any of the information, products, or processes included in this publication.
DOI: 10.17603/ds2-85j6-k851
title: Reduced Order Models for Peak Storm Surge in Texas and Alaska
title: in ADCIRC Reduced Order Modeling

description: This project contains feature data-sets and trained models for creating and training reduced-order models of ADCIRC for predicting maximum storm-surge due to extreme weather events in two regions: (1) Texas and (2) Alaska.
description: Machine learning models of peak storm surge were generated for two regions - Texas and Alaska. The training data for the machine learning models was generated from preexisting ADCIRC databases using the adcirc-rom Python package. Models were trained using the same package. These models were able to accurately reconstruct peak storm surge for historical storms. They are the result of a grid search over a space of potential models.