cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.4tm357
title: Occurrence Download

description: A dataset listing the 528 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "Geometry POLYGON((2.19811 48.91201,2.20383 48.91452,2.20149 48.91722,2.20087 48.91796,2.19926 48.91906,2.19554 48.91689,2.19544 48.91714,2.19319 48.91623,2.19211 48.91823,2.18847 48.91743,2.18771 48.91888,2.18681 48.91856,2.18538 48.91817,2.18324 48.91776,2.18112 48.91717,2.17791 48.91603,2.17665 48.91702,2.17551 48.91784,2.17305 48.92109,2.17168 48.92261,2.17021 48.92427,2.17013 48.92479,2.16825 48.9265,2.16675 48.92581,2.16666 48.92497,2.16645 48.92483,2.16565 48.92356,2.16604 48.92288,2.16092 48.92033,2.15943 48.91923,2.15993 48.91886,2.16213 48.91631,2.16049 48.91512,2.15898 48.9142,2.16041 48.91242,2.16167 48.90984,2.16008 48.90918,2.16235 48.90737,2.16604 48.90443,2.16572 48.90407,2.16681 48.90336,2.16703 48.90364,2.17354 48.89839,2.17605 48.90018,2.17831 48.90107,2.18425 48.90291,2.18936 48.90383,2.19315 48.9048,2.19565 48.90659,2.20092 48.90879,2.19811 48.91201))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 528 records were derived from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072228-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.97ur3m
title: Occurrence Download

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

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017452-181003121212138/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6w8qxz
title: Occurrence Download

description: A dataset containing 34302336 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-83 13,-83 -14,-60 -14,-60 13,-83 13))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 34302336 records from 4062 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0112920-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cy6ums
title: Occurrence Download

description: A dataset containing 1521552842 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 1521552842 records from 17611 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009324-170826194755519/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/11821924
title: Public Opinion on Climate Change (Updated Daily)
DOI: 10.5281/zenodo.15147938
title: Dataset pertaining to 'Biodiversity in Mountain Soils above the Treeline'

description: This dataset is an annotated bibliographic collection derived from the Web of Science, comprising scientific papers related to biodiversity in soils above the treeline in temperate mountain regions worldwide. It was developed to support the analysis presented in the publication "Biodiversity in Mountain Soils above the Tree Line" (www.doi.org/10.1111/brv.70028). The original dataset was generated by combining groups of search terms for 'soil', 'biodiversity', and 'alpine (high mountain) regions'. The complete search strings used are provided in the publication's Supplementary Information. Each paper in the dataset was annotated through text mining, using curated reference lists of soil organisms, mountain regions and ranges, and research fields. Taxa were extracted using the Global Names Architecture and assigned to one of seven main organismal groups discussed in this publication. Individual papers were then attributed to organismal groups based on the weighed frequency of taxon mentions in the title and abstract. Geographic attribution was performed by identifying mountain range names based on the GMBA Mountain Inventory v.2.0, and other place-based features (e.g., countries, protected areas). Individual papers were then linked to one of 11 main mid-latitude alpine regions discussed in the publication. Research foci were derived from weighted keyword frequencies in the title and abstract. The annotated metadata were used to generate the summary statistics, maps, and figures included in the paper. For detailed information on the annotation methods, classification logic, and analytical outputs, please refer to the publication "Biodiversity in Mountain Soils above the Tree Line" (see 'Related Works' below).
DOI: 10.5281/zenodo.15147939
title: Dataset pertaining to 'Biodiversity in Mountain Soils above the Treeline'

description: This dataset is an annotated bibliographic collection derived from the Web of Science, comprising scientific papers related to biodiversity in soils above the treeline in temperate mountain regions worldwide. It was developed to support the analysis presented in the publication "Biodiversity in Mountain Soils above the Tree Line" (www.doi.org/10.1111/brv.70028). The original dataset was generated by combining groups of search terms for 'soil', 'biodiversity', and 'alpine (high mountain) regions'. The complete search strings used are provided in the publication's Supplementary Information. Each paper in the dataset was annotated through text mining, using curated reference lists of soil organisms, mountain regions and ranges, and research fields. Taxa were extracted using the Global Names Architecture and assigned to one of seven main organismal groups discussed in this publication. Individual papers were then attributed to organismal groups based on the weighed frequency of taxon mentions in the title and abstract. Geographic attribution was performed by identifying mountain range names based on the GMBA Mountain Inventory v.2.0, and other place-based features (e.g., countries, protected areas). Individual papers were then linked to one of 11 main mid-latitude alpine regions discussed in the publication. Research foci were derived from weighted keyword frequencies in the title and abstract. The annotated metadata were used to generate the summary statistics, maps, and figures included in the paper. For detailed information on the annotation methods, classification logic, and analytical outputs, please refer to the publication "Biodiversity in Mountain Soils above the Tree Line" (see 'Related Works' below).
DOI: 10.15468/dl.vtnvbe
title: Occurrence Download

description: A dataset containing 13150 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bufo gargarizans Cantor, 1842"
 ]
}

 The dataset includes 13150 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032976-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ckmpt6
title: Occurrence Download

description: A dataset containing 155783 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Psammisia penduliflora (Dunal) Klotzsch, Solanum acerifolium Humb. & Bonpl. ex Dunal, Solanum oblongum Ruiz & Pav., Piper bartlingianum (Miq.) C.DC., Solanum subinerme Jacq., Piper tuberculatum Jacq., Piper hostmannianum (Miq.) C.DC., Philodendron squamiferum Poepp., Solanum grandiflorum Ruiz & Pav., Solanum aligerum Schltdl., Solanum erianthum D.Don, Philodendron grandifolium (Jacq.) Schott, Piper jacquemontianum (Kunth) Kunth ex Steud., Mangifera indica L., Carica papaya L., Piper amalago L., Annona exsucca DC., Vismia guianensis (Aubl.) DC., Muntingia calabura L., Solanum subsylvestre L.B.Sm. & Downs, Ficus monckii Hassl., Vassobia breviflora (Sendtn.) Hunz., Rubus brasiliensis Mart., Vismia macrophylla Kunth, Physalis angulata L., Trichobius lonchophyllae Wenzel, 1966, Trichobioides perspicillatus Pessõa & Galvão, 1937, Nycterophilia parnelli Wenzel, 1966, Trichobius parasparsus Wenzel, 1976, Speiseria ambigua Kessel, 1925, Trichobius yunkeri Wenzel, 1966, Metelasmus wenzeli Graciolli & Dick, 2004, Trichobius lionycteridis Wenzel, 1966, Strebla carvalhoi Graciolli, 2003, Trichobius phyllostomae Kessel, 1925, Strebla tonatiae (Kessel, 1924), Strebla diaemi Wenzel, 1966, Mastoptera minuta (Lima, 1921), Paraeuctenodes similis Wenzel, 1976, Trichobius angulatus Wenzel, 1976, Trichobius uniformis Curran, 1935, Macrosiphum lilii (Monell, 1880), Rhabdophis ceylonensis (Günther, 1858), Xenochrophis flavipunctatus (Hallowell, 1860), Psammodynastes pulverulentus (Boie, 1827), Ptyas korros (Schlegel, 1837), Xenochrophis piscator Schneider, 1799, Amphibiophilus acanthocirratus Skrjabin, 1916, Cosmocerca ornata (Dujardin, 1845) Diesing, 1861, Diplodiscus japonicus Yamaguti, 1936)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 155783 records from 1264 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032957-250426092105405/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.29070122
title: Greening-cambridge-input-data

description: This data set contains the inputs as used for the research project gha26-greening-cambridge. This includes data gathered from online sources to represent the town of Pirmasens for the case study.
DOI: 10.15468/dl.5scgxy
title: Occurrence Download

description: A dataset listing the 4066193 species recorded in GBIF matching the query:
{ }

 The dataset's 4066193 records were derived from 73110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032963-250426092105405/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.29070134
title: Pirmasens-CEA-data

description: This dataset contains hourly time series data of heating demand and rooftop solar thermal potential for buildings in Pirmasens, Germany. It was generated using the City Energy Analyst (CEA) software, executed by an agent in The World Avatar (TWA) knowledge graph. Inputs were retrieved from TWA and include building geometry, weather data, and terrain elevation.<br><br>Outputs include:<br><br>Hourly heating demand per building<br><br>Hourly rooftop solar thermal potential per building
DOI: 10.5517/ccdc.csd.cc2k9np7
title: CCDC 2362779: Experimental Crystal Structure Determination

description: Related Article: Donghwa Shin, Seo-Jung Han|2025|Org.Lett.|27|4767|doi:10.1021/acs.orglett.5c01178
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2kz00l
title: CCDC 2382319: Experimental Crystal Structure Determination

description: Related Article: Jun-Jie Hao, Tao Jiang, FuJunyang Wu, Hejiang Luo, Rong-Tao Li|2025|Org.Lett.|27|4817|doi:10.1021/acs.orglett.5c01508
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2lp2r4
title: CCDC 2403546: Experimental Crystal Structure Determination

description: Related Article: Kemal Sancak, Gülşah Gül Kılınç, Filiz Durak, Hanifi Özşanlı, Ufuk Çoruh, Burak Barut|2025|J.Mol.Struct.|1339|142414|doi:10.1016/j.molstruc.2025.142414
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.17863/cam.96645.2
title: Research Data supporting "Statistical evaluation of the mechanical properties of partially oxygenated YBCO, oxygenated YBCO and oxygenated YBCO(Ag) single grains"

description: This dataset contains supporting information for the journal article “Statistical evaluation of the mechanical properties of partially oxygenated YBCO, oxygenated YBCO and oxygenated YBCO(Ag) single grains”. The file “README.txt” contains detailed information about the data measurement and evaluation. The file “Raw_data.xlsx” contains the raw data used for the plots illustrated in figures 4, 5, 7, 8 and 10. The file “calculation_weibull_modulus.xlsx” explains the calculation of the Weibull modulus for partially oxygenated YBCO, oxygenated YBCO and oxygenated YBCO(Ag) bulk materials. The folders “Figure_7.zip” and “Figure_8.zip” contain the EDX maps and optical tracking microscope images used to gather the data for figures 7 and 8.
DOI: 10.5281/zenodo.15423563
title: DATASET: Open RGB Imaging Workflow for Morphological and Morphometric Analysis of Fruits using AI: A Case Study on Almonds
DOI: 10.5281/zenodo.15423533
title: Datasets for the publication: Chemical recycling of PLA and its copolyesters with poly(ethylene azelate) via microwave-assisted alkaline hydrolysis and enzymatic hydrolysis. Polymers. 2025

description: Datasets for the publication: Chemical recycling of PLA and its copolyesters with poly(ethylene azelate) via microwave-assisted alkaline hydrolysis and enzymatic hydrolysis. Polymers. 2025
DOI: 10.5281/zenodo.15423534
title: Datasets for the publication: Chemical recycling of PLA and its copolyesters with poly(ethylene azelate) via microwave-assisted alkaline hydrolysis and enzymatic hydrolysis. Polymers. 2025

description: Datasets for the publication: Chemical recycling of PLA and its copolyesters with poly(ethylene azelate) via microwave-assisted alkaline hydrolysis and enzymatic hydrolysis. Polymers. 2025
DOI: 10.6084/m9.figshare.29049626
title: ShareData

description: WRF Simulated Radar Composite Reflectivity<b><i>wrfmdbz_time_lat_lon.nc (time * lat * lon) (4 * 379 * 314)</i></b><b>Horizontal Range</b>: 32.5°N to 35.5°N for Latitude and 111.5°E to 114.5°E for Longitude<b>Time Range</b>: 4 times from 0300 to 0600 UTC on 20 July 2021 with an interval of 1-hrWRF Settings<b><i>namelist.input</i></b>Descriptions of namelist parameters for the simulation in this study<b><i>wrfbdy and wrfinput</i></b>The boundary file (wrfbdy_d01) and input files for corresponding domains (wrfinout*) for the simulation in this study<br>
DOI: 10.5281/zenodo.15262167
title: Pan-European catalogue of datasets for Geothermal Energy assessment

description: Geothermal energy offers a sustainable solution for heating and cooling (H&C) throughout Europe. To ensure successful integration, it is crucial to have comprehensive and harmonized geoscientific datasets. The SAPHEA project team has been actively reviewing, collecting, and disseminating these datasets to assist stakeholders with strategic planning and investment decisions.

The following dataset represents a state-of-the-art overview (as of 2025) of selected pan-European geospatial data sources relevant to geothermal energy applications. All cited datasets are freely available, accessible, and can be downloaded via the URLs provided in the table.
DOI: 10.5281/zenodo.15262168
title: Pan-European catalogue of datasets for Geothermal Energy assessment

description: Geothermal energy offers a sustainable solution for heating and cooling (H&C) throughout Europe. To ensure successful integration, it is crucial to have comprehensive and harmonized geoscientific datasets. The SAPHEA project team has been actively reviewing, collecting, and disseminating these datasets to assist stakeholders with strategic planning and investment decisions.

The following dataset represents a state-of-the-art overview (as of 2025) of selected pan-European geospatial data sources relevant to geothermal energy applications. All cited datasets are freely available, accessible, and can be downloaded via the URLs provided in the table.
DOI: 10.5281/zenodo.15423728
title: Pan-European catalogue of datasets for Geothermal Energy assessment

description: Geothermal energy offers a sustainable solution for heating and cooling (H&C) throughout Europe. To ensure successful integration, it is crucial to have comprehensive and harmonized geoscientific datasets. The SAPHEA project team has been actively reviewing, collecting, and disseminating these datasets to assist stakeholders with strategic planning and investment decisions.

The following dataset represents a state-of-the-art overview (as of 2025) of selected pan-European geospatial data sources relevant to geothermal energy applications. All cited datasets are freely available, accessible, and can be downloaded via the URLs provided in the table.
DOI: 10.5281/zenodo.15392161
title: Enriched Annotations Based on Policy-IE for PP-Analyzer

description: ## Content

- `annotation_configurations`: Configuration files for brat, the annotation tool. Additional configuration files are also provided for each phase.

- `phases`: Each sub-directory represents the annotations of a phase, for each annotator.

- `final`: The final reconciled annotations after the whole annotation process.

- `Annotator-Instruction.pdf`: Instrustions given to annotators for their annotation tasks.

## Usage

To view or modify the annotations, follow these steps:

1. Copy the configuration `annotation_configurations/annotation.conf` to you brat instance

2. Copy the annotations (e.g. the `final` directory) to the directories that your brat instance recognizes (e.g. `bratdata`)         1. Alternatively, you can also copy the annotations from individual phases from individual annotators

3. Start brat, such as a docker container

4. Navigate to the directory and annotation files
DOI: 10.5281/zenodo.15392162
title: Enriched Annotations Based on Policy-IE for PP-Analyzer

description: ## Content

- `annotation_configurations`: Configuration files for brat, the annotation tool. Additional configuration files are also provided for each phase.

- `phases`: Each sub-directory represents the annotations of a phase, for each annotator.

- `final`: The final reconciled annotations after the whole annotation process.

- `Annotator-Instruction.pdf`: Instrustions given to annotators for their annotation tasks.

## Usage

To view or modify the annotations, follow these steps:

1. Copy the configuration `annotation_configurations/annotation.conf` to you brat instance

2. Copy the annotations (e.g. the `final` directory) to the directories that your brat instance recognizes (e.g. `bratdata`)         1. Alternatively, you can also copy the annotations from individual phases from individual annotators

3. Start brat, such as a docker container

4. Navigate to the directory and annotation files
DOI: 10.34740/kaggle/dsv/11822143
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.15076305
title: Percent contribution data of Polish mathematician co-authors

description: This dataset contains data on authors, publications, and co-author percent contributions to publications of Polish habilitation degree applicants, collected from publicly available files from https://www.ck.gov.pl/promotion/type/l.html and https://radon.nauka.gov.pl/dane/pliki-postepowania-awansowe and various university websites. Data was extracted from PDF documents for scientific research into co-author name ordering and relative input contributions of co-authors in mathematics. The datset is an Excel file with the following columns:

source: source websitedomain: scientific domain according to sourcediscipline: scientific discipline according to sourcefamily_name_on_list: applicant family name as listed in sourcegiven_name_on_list: applicant given name as listed in sourcefull_name_on_langing_page: full name according to source, taken from the habilitation proceedings landing pagesubmission_year: year of submission of applicationapplication_number: ID number of proceeding, either as given or extracted from landing page URL, depending on sourcenumerical_percent_contribution_statements_found: whether any numerical percent contribution statements could be found in the self-report PDF. values: YES/NOnum_works_listed: number of works listed for the habilitation publications cyclenum_works_coauthored: number of works of the above which were co-authoredinternal_work_number: a counter to identify work within applications, can go beyond the works belonging to the habilitation cyclereference_in_application: for works with perent contribution data, the bibliographic reference as given in the self-reportnum_coauthors: number of co-authors of a publicationauthor_position: position of the name in the author list of a co-author with a numerical percent contribution, first author would have value 1, second author 2, etc.contribution_percent: the indicated numerical percent contribution, a value up to 100, in percentnote: additional information about source of information when found on university website and percent contribution for works which were not part of habilitation works cyclealphabetical_order: whether the author list was in alphabetical name order. values: YES/NOcontribution_for_applicant: whether the percent contribution value of a co-author is for the habilitation applicant or not. values: YES/NO