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

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Borinda edulis (Hsueh f. & T.P.Yi) Stapleton)"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002080-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nccbhm
title: Occurrence Download

description: A dataset containing 1044 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cycas media R.Br."
 ]
}

 The dataset includes 1044 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002081-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14229202
title: Sample Drifter Dataset for example in JuliaConProceedings2023

description: Summary : 



jld2 file that contains inputs to the particle tracking example

region : Gulf of Mexico

source : OceanRobots.jl (incl. data references)


File content :

 ├─🔢 drifters_real ├─🔢 u ├─🔢 v ├─🔢 x ├─🔢 y ├─🔢 x0 ├─🔢 y0 ├─🔢 polygons ├─🔢 res

 └─ ⋯ (3 more entries)
DOI: 10.5281/zenodo.14229203
title: Sample Drifter Dataset for example in JuliaConProceedings2023

description: Summary : 



jld2 file that contains inputs to the particle tracking example

region : Gulf of Mexico

source : OceanRobots.jl (incl. data references)


File content :

 ├─🔢 drifters_real ├─🔢 u ├─🔢 v ├─🔢 x ├─🔢 y ├─🔢 x0 ├─🔢 y0 ├─🔢 polygons ├─🔢 res

 └─ ⋯ (3 more entries)
DOI: 10.15468/dl.hvusab
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Borinda elegans (T.P.Yi) Stapleton)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002082-241126133413365/datasets/export for details.
DOI: 10.24355/dbbs.084-202109291537-0
title: WheatFluxStudy

description: GC-MS analysis of plasma samples that were collected in the framework of a nutritional intervention study supervised by Unilever R&D Vlaardingen, NL (www.clinicaltrials.gov: NCT02662738). Archived data include metabolite concentrations and labeling data of subjects 01, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12 and interventions GLC and WP, which were used for follow-up data analysis.
DOI: 10.24355/dbbs.084-202109020917-0
title: Large-scale vibroacoustic simulations using parallel direct solvers for high-performance clusters - Dataset

description: The dataset contains files to retreive the matrices used as benchmark for the contribution - Sreekumar, H. K. et. al. "Large-scale vibroacoustic simulations using parallel direct solvers for high-performance clusters", DAGA Conference 2021, Vienna, 2021.
DOI: 10.15468/dl.ub2yny
title: Occurrence Download

description: A dataset containing 1044 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cycas media R.Br."
 ]
}

 The dataset includes 1044 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002083-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qkyuvs
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Borinda emaculata (T.P.Yi) Stapleton)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002084-241126133413365/datasets/export for details.
DOI: 10.24355/dbbs.084-202107061200-0
title: Supplementary data for a study on a data driven learning approach for the assessment of data quality

description: This data is 100% artificial (no real patients involved). This dataset was generated to explore the application of simple machine learning to learn knowledge about how simple statistical measures about a dataset (e.g. mean value for variable, value counts etc.) can indicate data quality issues. The generated dummy data, outcome data and MM-results are available in the folder "dummy data, outcome data, MM-results". The numbers of triggered DQ-issue rules are available in folder "triggered issue rules". The MM-results used for machine learning can be found in file "MM-results_export_for_machine_learningresult_exports.csv".
DOI: 10.15468/dl.djh3h4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Borinda erecta (T.P.Yi) Stapleton)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002085-241126133413365/datasets/export for details.
DOI: 10.5281/zenodo.14228781
title: The high dose of biochar reduces polycyclic aromatic hydrocarbons losses during co-composting of sewage sludge and wheat straw

description: The data presents the raw data of organic solvent extractable polycyclic aromatic hydrocarbons and freely dissolved polycyclic aromatic hydrocarbons and temperature during composting as well as physico-chemical properties of composted material.
DOI: 10.5281/zenodo.14228782
title: The high dose of biochar reduces polycyclic aromatic hydrocarbons losses during co-composting of sewage sludge and wheat straw

description: The data presents the raw data of organic solvent extractable polycyclic aromatic hydrocarbons and freely dissolved polycyclic aromatic hydrocarbons and temperature during composting as well as physico-chemical properties of composted material.
DOI: 10.24355/dbbs.084-202105100741-0
title: A System Dynamics Model of the Air Transport System

description: This collection contains a system dynamics model of the air transport system (ATS), developed to assess the impact of different policies on the adoption rate of fully electric aircraft until the year 2050. The model consists of the interaction between three major segments, namely air travel demand, airline industry and aircraft manufacturers. The provided files can be executed using the software Vensim. Furthermore, a data set as an excel file, containing a collection of initial values, parameters, exogenous variables and variables used to calibrate the ATS model is given.
DOI: 10.5281/zenodo.14229303
title: Gilgenburg Apotheke

description: Historical questionnaire/s 1924/1948 and index cards, partly selected enclosures regarding the history of a German pharmacy, catalogued via Kalliope portal (Historischer Fragebogen 1924/1948 und Karteikarten, ggf. gemeinfreie Anlagen zur Apothekengeschichte; als Katalog dient das Nachlassportal Kalliope):

https://kalliope-verbund.info/ead?ead.id=DE-611-BF-70963

Please note: The Kalliope catalogue entry might indicate related material in the archival folder which cannot be published due to copyright or other legal restrictions (NB: Das Katalogisat bei Kalliope kann auch auf Materialien - teils erheblichen Umfangs - verweisen, die aus archiv- oder urheberrechtlichen Gründen nicht veröffentlicht werden dürfen).
DOI: 10.15468/dl.ghwjwv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Borinda extensa (T.P.Yi) Stapleton)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002087-241126133413365/datasets/export for details.
DOI: 10.15468/dl.6rgjnp
title: Occurrence Download

description: A dataset containing 5943329 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1970-2024"
 ]
}

 The dataset includes 5943329 records from 2035 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002049-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.awe3pd
title: Occurrence Download

description: A dataset containing 1637 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Schistura mobbsi, Danio pulcher, Schistura sexcauda, Batasio tigrinus, Betta simplex, Opsarius infrafasciatus, Schistura spilota, Sectoria atriceps, Thryssocypris wongrati, Epalzeorhynchos bicolor, Schistura mahnerti, Amblyceps variegatum, Cynoglossus xiphoideus, Schistura laterimaculata, Serpenticobitis cingulata, Neolissochilus vittatus, Hampala salweenensis, Hypsibarbus salweenensis, Schistura moeiensis, Schistura oedipus, Schistura paucicincta, Schistura reidi, Indostomus crocodilus, Nemacheilus ornatus, Mystus rhegma, Polynemus multifilis, Acrochordonichthys septentrionalis, Parambassis vollmeri, Schistura similis, Fluvitrygon signifer, Devario shanensis, Garra vinciguerrae, Barbus thessalus, Kryptoglanis shajii, Schistura huongensis, Schistura carbonaria, Schistura spiloptera, Schistura bachmaensis, Hypselobarbus dobsoni, Psilorhynchus tenura, Hypselobarbus pulchellus, Ptychobarbus dipogon, Triplophysa scapanognatha, Oxygymnocypris stewartii, Schizopygopsis chui, Schizopygopsis scleracanthus, Schizopygopsis waddellii, Schizopygopsis younghusbandi, Schizopygopsis thermalis, Acheilognathus nguyenvanhaoi, Hisonotus paulinus, Corumbataia cuestae, Otothyropsis marapoama, Rhytiodus lauzannei, Pseudomugil luminatus, Jupiaba poekotero, Batasio fasciolatus, Garra chaudhurii, Pseudolaguvia ferula, Psilorhynchus hamiltoni, Gobio carpathicus, Hassar wilderi, Cynopotamus gouldingi, Peckoltia oligospila, Cichla mirianae, Semaprochilodus brama, Cyphocharax stilbolepis, Ituglanis passensis, Acestrocephalus acutus, Harttia duriventris, Aguarunichthys tocantinsensis, Apteronotus camposdapazi, Baryancistrus longipinnis, Brycon gouldingi, Bryconamericus novae, Cetopsis caiapo, Hypostomus asperatus, Hypostomus atropinnis, Leporinus bistriatus, Leporinus taeniofasciatus, Potamotrygon henlei, Roestes itupiranga, Steindachnerina gracilis, Tridentopsis tocantinsi, Trigonectes strigabundus, Cetopsis sarcodes, Loricaria lata, Hemiodus ternetzi, Creagrutus figueiredoi, Astyanax elachylepis, Melanorivulus pindorama, Pimelodus joannis, Pimelodus stewarti, Typhlobelus macromycterus, Jupiaba elassonaktis, Sternarchorhynchus axelrodi, Scoloplax distolothrix, Ctenocheirodon pristis)",
 "HasCoordinate is true",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 1637 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057808-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29851514
title: The perceived wealth and physical disorder scores annotation dataset for Chinese urban street view images

description: The perceived wealth and physical disorder scores annotation dataset comprises 40,000 Chinese street view images. Half of these images are annotated with perceived wealth scores ranging from 0 to 10, while the other half are annotated with perceived physical disorder scores. Higher scores indicate a greater sense of affluence and disorder in the street scene. These images were annotated by Chinese urban planners. All images are in JPG format and have been uploaded as compressed files. The corresponding perception scores for each image are stored in two CSV tables. These two types of files can be matched using image IDs. Researchers can use this dataset as it is, or augment and supplement it, in order to train their own artificial intelligence perception models to perform large-scale, real-time, automatic inference on other street view images in Chinese cities. This largely overcomes the local prediction bias caused by commonly used datasets such as the MIT Place Pulse Perception Dataset, which rely on Western street view images and Western annotators.<br><br><b>Source publication</b>: Zhang, Y., You, Y., Chen, S., & Cai, L. (2025). Geospatial dataset on human perceptions of wealth and physical disorder in urban China using street view imagery and deep learning. <i>Data in Brief</i>, 112116.
DOI: 10.6084/m9.figshare.29851514.v2
title: The perceived wealth and physical disorder scores annotation dataset for Chinese urban street view images

description: The perceived wealth and physical disorder scores annotation dataset comprises 40,000 Chinese street view images. Half of these images are annotated with perceived wealth scores ranging from 0 to 10, while the other half are annotated with perceived physical disorder scores. Higher scores indicate a greater sense of affluence and disorder in the street scene. These images were annotated by Chinese urban planners. All images are in JPG format and have been uploaded as compressed files. The corresponding perception scores for each image are stored in two CSV tables. These two types of files can be matched using image IDs. Researchers can use this dataset as it is, or augment and supplement it, in order to train their own artificial intelligence perception models to perform large-scale, real-time, automatic inference on other street view images in Chinese cities. This largely overcomes the local prediction bias caused by commonly used datasets such as the MIT Place Pulse Perception Dataset, which rely on Western street view images and Western annotators.<br><br><b>Source publication</b>: Zhang, Y., You, Y., Chen, S., & Cai, L. (2025). Geospatial dataset on human perceptions of wealth and physical disorder in urban China using street view imagery and deep learning. <i>Data in Brief</i>, 112116.
DOI: 10.6084/m9.figshare.29851514.v1
title: The perceived wealth and physical disorder scores annotation dataset for Chinese urban street view images

description: The perceived wealth and physical disorder scores annotation dataset comprises 40,000 Chinese street view images. Half of these images are annotated with perceived wealth scores ranging from 0 to 10, while the other half are annotated with perceived physical disorder scores. Higher scores indicate a greater sense of affluence and disorder in the street scene. These images were annotated by Chinese urban planners. All images are in JPG format and have been uploaded as compressed files. The corresponding perception scores for each image are stored in two CSV tables. These two types of files can be matched using image IDs. Researchers can use this dataset as it is, or augment and supplement it, in order to train their own artificial intelligence perception models to perform large-scale, real-time, automatic inference on other street view images in Chinese cities. This largely overcomes the local prediction bias caused by commonly used datasets such as the MIT Place Pulse Perception Dataset, which rely on Western street view images and Western annotators.
DOI: 10.6084/m9.figshare.29923664
title: The perceived wealth and physical disorder scores prediction dataset for urban China

description: The perceived wealth and physical disorder scores prediction dataset consists of three files, each corresponding to perception data from one of the three analytical levels. Based on the perception image annotation dataset labeled by Chinese urban planners (https://figshare.com/s/a942f102cd07f4a73515), these perception scores are predicted through model training and inference across urban China.The first file (point version) contains perception scores for 36,262,700 street view images. This CSV-formatted data includes the longitude and latitude of each image’s shooting location, the time the image was taken, and the perceived wealth and physical disorder scores. This data can be reprocessed by researchers for their specific analytical need. The second file (grid version) and third file (community version) are stored as GeoTIFF (.tif) files with the Albers conic equal area projection. The mean perceived wealth score and mean perceived physical disorder score from 2013 to 2022 are aggregated using 500m×500m grids and community administrative areas as the analytical units, respectively. They can be processed using GIS software such as ArcGIS and QGIS, as well as Python programming language packages such as Rasterio. We also publish corresponding simplified tables in CSV format showing the mean perceived wealth and physical disorder scores in each grid and community. These tables include the community’s name, the latitude and longitude of the grid (or community) centroid, and the names of the county-, prefecture-, and province-level areas in which the grid (or community) is located.<br><br><b>Source publication</b>: Zhang, Y., You, Y., Chen, S., & Cai, L. (2025). Geospatial dataset on human perceptions of wealth and physical disorder in urban China using street view imagery and deep learning. <i>Data in Brief</i>, 112116.
DOI: 10.6084/m9.figshare.29923664.v2
title: The perceived wealth and physical disorder scores prediction dataset for urban China

description: The perceived wealth and physical disorder scores prediction dataset consists of three files, each corresponding to perception data from one of the three analytical levels. Based on the perception image annotation dataset labeled by Chinese urban planners (https://figshare.com/s/a942f102cd07f4a73515), these perception scores are predicted through model training and inference across urban China.The first file (point version) contains perception scores for 36,262,700 street view images. This CSV-formatted data includes the longitude and latitude of each image’s shooting location, the time the image was taken, and the perceived wealth and physical disorder scores. This data can be reprocessed by researchers for their specific analytical need. The second file (grid version) and third file (community version) are stored as GeoTIFF (.tif) files with the Albers conic equal area projection. The mean perceived wealth score and mean perceived physical disorder score from 2013 to 2022 are aggregated using 500m×500m grids and community administrative areas as the analytical units, respectively. They can be processed using GIS software such as ArcGIS and QGIS, as well as Python programming language packages such as Rasterio. We also publish corresponding simplified tables in CSV format showing the mean perceived wealth and physical disorder scores in each grid and community. These tables include the community’s name, the latitude and longitude of the grid (or community) centroid, and the names of the county-, prefecture-, and province-level areas in which the grid (or community) is located.<br><br><b>Source publication</b>: Zhang, Y., You, Y., Chen, S., & Cai, L. (2025). Geospatial dataset on human perceptions of wealth and physical disorder in urban China using street view imagery and deep learning. <i>Data in Brief</i>, 112116.
DOI: 10.6084/m9.figshare.29923664.v1
title: The perceived wealth and physical disorder scores prediction dataset for urban China

description: The perceived wealth and physical disorder scores prediction dataset consists of three files, each corresponding to perception data from one of the three analytical levels. Based on the perception image annotation dataset labeled by Chinese urban planners (https://figshare.com/s/a942f102cd07f4a73515), these perception scores are predicted through model training and inference across urban China. The first file (point version) contains perception scores for 36,262,700 street view images. This CSV-formatted data includes the longitude and latitude of each image’s shooting location, the time the image was taken, and the perceived wealth and physical disorder scores. This data can be reprocessed by researchers for their specific analytical need. The second file (grid version) and third file (community version) are stored as GeoTIFF (.tif) files with the Albers conic equal area projection. The mean perceived wealth score and mean perceived physical disorder score from 2013 to 2022 are aggregated using 500m×500m grids and community administrative areas as the analytical units, respectively. They can be processed using GIS software such as ArcGIS and QGIS, as well as Python programming language packages such as Rasterio. We also publish corresponding simplified tables in CSV format showing the mean perceived wealth and physical disorder scores in each grid and community. These tables include the community’s name, the latitude and longitude of the grid (or community) centroid, and the names of the county-, prefecture-, and province-level areas in which the grid (or community) is located.
DOI: 10.5281/zenodo.17285664
title: Radiomic Features from Structural MRI in First-Episode Psychosis (FEP) and Healthy Controls (HC)

description: This dataset contains radiomic features extracted from structural T1-weighted MRI scans of participants diagnosed with First-Episode Psychosis (FEP) and matched Healthy Controls (HC). A total of 304 subjects were included, comprising 130 FEP and 174 HC cases. Preprocessing and cortical/subcortical segmentation were performed with FreeSurfer v7.4.2, and radiomic features were extracted using PyRadiomics v3.0.1 following IBSI guidelines. 




The dataset includes: 




Subject identifiers (anonymized) 

Diagnostic labels (FEP vs HC) 

Extracted radiomic features across cortical and subcortical regions ( aparc+aseg Freesurfer in first-order, shape, and multiple texture families: GLCM, GLRLM, GLSZM, NGTDM, GLDM). 




This resource can support reproducibility and benchmarking in neuroimaging-based machine learning studies, enabling the exploration of structural MRI biomarkers in psychosis. 



This work was supported by  the Valencian Regional Government (CIPROM/2023/28) and the Carlos III Healthcare Institute (ISCIII), projects PI20/00473 (to M.D. Moltó), PI22/01985 (to O. Rivero) and CP21/00059 (to O. Rivero), co-funded by the European Union.