cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57745/eo5u7y
title: Phenotypic trait and leaf phenology dataset (1993 - 2022) of Juglans sp. from common gardens in France

description: Données sur des caractères phénotypiques de Juglans regia, Juglans nigra et Juglans regia x J. nigra mesurés dans les jardins communs du réseau INRAE de génétique forestière pour la recherche et l'expérimentation (GEN4X). Ce jeu de données est composé d'observations telles que la hauteur totale, la circonférence, la survie, l'architecture et le débourrement végétatif, réalisées entre 1993 et 2022 dans sept jardins communs du réseau GEN4X : deux tests de provenances, quatre tests de descendances et un test clonal. Les tests sont installés dans des conditions environnementales variées dans le sud de la France. Les jardins communs ont été plantés entre 1993 et 1995 et contiennent chacun entre 200 et 1182 individus, pour un total de plus de 3000 individus. Chaque jardin commun compare entre 8 et 33 génotypes. En comptant les génotypes présents à titre de référence, ce sont 165 génotypes des genres Juglans et Pterocarya qui sont représentés dans ces set jardins communs. Ce type de données de caractères phénotypiques liés à la valeur sélective peuvent être utilisés pour tester l'ampleur et la structuration de la diversité génétique, la plasticité phénotypique et l'adaptation locale dans des conditions variées de sols et de climats. L'archive contient onze fichiers. Le fichier "Desciption_Genotypes_Juglans" contient les métadonnées sur les accessions (provenances, descendances, clones). Le fichier "Description_Jardins_Communs_Juglans" contient les métadonnées sur les sites de plantation. Les deux fichiers texte "Readme" décrivent les données et les entêtes des champs des fichiers de description. Chacun des sept fichiers restants contient les données phénotypiques, un fichier par jardin commun.
DOI: 10.5517/ccdc.csd.cc2m79kr
title: CCDC 2420094: Experimental Crystal Structure Determination

description: Related Article: Till Neumann, Iker Del Rosal, Laurent Maron, Erwann Jeanneau, Vincent Maurel, Serge Gambarelli, Jean-Marie Mouesca, Chloé Thieuleux, Clément Camp|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c02380
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.cc2m79ls
title: CCDC 2420095: Experimental Crystal Structure Determination

description: Related Article: Till Neumann, Iker Del Rosal, Laurent Maron, Erwann Jeanneau, Vincent Maurel, Serge Gambarelli, Jean-Marie Mouesca, Chloé Thieuleux, Clément Camp|2025|Inorg.Chem.|||doi:10.1021/acs.inorgchem.5c02380
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: 10.6084/m9.figshare.30581615
title: Analytic data of figures and tables

description: data for figures and tables
DOI: 10.6084/m9.figshare.30581615.v1
title: Analytic data of figures and tables

description: data for figures and tables
DOI: 10.15468/dl.wwu7n4
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "OccurrenceStatus is Present",
 "TaxonKey is Zygia trunciflora"
 ]
}

 The dataset includes 55 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025044-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16939088
title: Developing central Research Software Engineering units in German research institutions: materials

description: This archive contains the survey responses and associated analysis and plotting scripts for the paper “Developing central Research Software Engineering units in German research institutions” by the same authors.
DOI: 10.5281/zenodo.16939089
title: Developing central Research Software Engineering units in German research institutions: materials

description: This archive contains the survey responses and associated analysis and plotting scripts for the paper “Developing central Research Software Engineering units in German research institutions” by the same authors.
DOI: 10.15468/dl.65r4ad
title: Occurrence Download

description: A dataset containing 371359 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Living Specimen, Occurrence evidence)",
 "DatasetKey is one of (iNaturalist Research-grade Observations, EOD – eBird Observation Dataset)",
 "OccurrenceStatus is Present",
 "TaxonKey is Molothrus aeneus"
 ]
}

 The dataset includes 371359 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025026-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/kwp0uq
title: metadata_GEN4X.tab

description: Metadata for the trials of GEN4X network
DOI: 10.57745/bvd98w
title: Observed Variable.tab

description: :unav
DOI: 10.57745/vrg8ti
title: Codifications_Tests_GEN4X.txt

description: Explication du code de nommage des dispositifs expérimentaux
DOI: 10.57745/y7qxne
title: Study.tab

description: :unav
DOI: 10.57745/ydgyuh
title: Biological Material.tab

description: :unav
DOI: 10.57745/yej290
title: Person.tab

description: :unav
DOI: 10.57745/evbpq5
title: README_MIAPPE.txt

description: :unav
DOI: 10.57745/w8orbs
title: Investigation.tab

description: :unav
DOI: 10.57745/do8zo2
title: Environment.tab

description: :unav
DOI: 10.57745/yxxlkz
title: README_MIAPPE.txt

description: :unav
DOI: 10.17632/bxw23pcwfh
title: The Effect of Retail Chain Expansions on Local Small Businesses: The Case of Dollar General in Florida

description: Replication Materials for "The Effect of Retail Chain Expansions on Local Small Businesses: The Case of Dollar General in Florida"
This repository provides the R scripts and supporting materials to replicate the methodology presented in the paper "The Effect of Retail Chain Expansions on Local Small Businesses: The Case of Dollar General in Florida." The study employs difference-in-differences methods and staggered event models to explore the impact of Dollar General store openings on neighboring small firms in Florida.

Data and Replication
The analysis is based on the National Establishment Time-Series (NETS) Database, a proprietary product licensed from Walls & Associates. Under our data use agreement, we are prohibited from redistributing the raw dataset.

To ensure methodological transparency and demonstrate the functionality of our code, we have created and included a simulated dataset. While this simulated data will not reproduce the exact numerical findings of the paper, it is designed to mimic the structure of the original data. Its purpose is to allow users to run the provided R scripts for data processing and analysis from start to finish, confirming that the code works as intended.

Researchers who wish to fully replicate the paper's results must license the NETS database directly from the provider and apply our provided scripts.
DOI: 10.17632/bxw23pcwfh.4
title: The Effect of Retail Chain Expansions on Local Small Businesses: The Case of Dollar General in Florida

description: Replication Materials for "The Effect of Retail Chain Expansions on Local Small Businesses: The Case of Dollar General in Florida"
This repository provides the R scripts and supporting materials to replicate the methodology presented in the paper "The Effect of Retail Chain Expansions on Local Small Businesses: The Case of Dollar General in Florida." The study employs difference-in-differences methods and staggered event models to explore the impact of Dollar General store openings on neighboring small firms in Florida.

Data and Replication
The analysis is based on the National Establishment Time-Series (NETS) Database, a proprietary product licensed from Walls & Associates. Under our data use agreement, we are prohibited from redistributing the raw dataset.

To ensure methodological transparency and demonstrate the functionality of our code, we have created and included a simulated dataset. While this simulated data will not reproduce the exact numerical findings of the paper, it is designed to mimic the structure of the original data. Its purpose is to allow users to run the provided R scripts for data processing and analysis from start to finish, confirming that the code works as intended.

Researchers who wish to fully replicate the paper's results must license the NETS database directly from the provider and apply our provided scripts.
DOI: 10.6084/m9.figshare.29078828
title: Data from: Filter feeding by oysters reduces disease transmission in a marine host-parasite system

description: The data and statistical analyses are associated with the following manuscript:Chen X, Jones DD, Limjoco CF, Groner ML, Reece KS, and Shields JD. 2025. Filter feeding by oysters reduces disease transmission in a marine host-parasite system. <i>Ecology</i>.The csv files include data collected from field and lab components of the study, and the corresponding R scripts include code required to reproduce the analyses.
DOI: 10.6084/m9.figshare.29078828.v2
title: Data from: Filter feeding by oysters reduces disease transmission in a marine host-parasite system

description: The data and statistical analyses are associated with the following manuscript:Chen X, Jones DD, Limjoco CF, Groner ML, Reece KS, and Shields JD. 2025. Filter feeding by oysters reduces disease transmission in a marine host-parasite system. <i>Ecology</i>.The csv files include data collected from field and lab components of the study, and the corresponding R scripts include code required to reproduce the analyses.
DOI: 10.6084/m9.figshare.29078828.v1
title: Filter feeding by oysters reduces disease transmission in a marine host-parasite system

description: The data and statistical analyses are associated with the following manuscript:Chen X, Jones DD, Limjoco CF, Groner ML, Reece KS, and Shields JD. Filter feeding by oysters reduces disease transmission in a marine host-parasite system. 2025. Ecology. in review.The csv files include data collected from field and lab components of the study, and the corresponding R scripts include code required to reproduce the analyses.
DOI: 10.5281/zenodo.17463344
title: 30 m Normalized Difference Vegetation Index Maps of Pure Pixels over China for Estimation of Fractional Vegetation Cover (2014, 2018, 2022)

description: Using multi-angle remote sensing data, we generated 30-m maps for the normalized difference vegetation index (NDVI) of fully-covered vegetation (Vv) and bare soils (Vs) across China in 2014, 2018 and 2022. These pixel-wise Vv and Vs maps can be integrated with the vegetation index (VI)-based model to facilitate the accurate and rapid estimation of fractional vegetation cover (FVC) across various spatial resolutions and large scales. The products were produced using a multi-angle algorithm (MultiVI), which effectively addressed the spatial variability inherent in Vv and Vs and enhanced the accuracy of FVC estimations in comparison to traditional statistical methods. The estimated FVC demonstrated a root mean square deviation (RMSD) of approximately 0.1 when evaluated against field-measured FVC across different experimental sites.
description: The Vv and Vs data are stored in GeoTIFF files using the WGS-84 (World Geodetic System 1984) coordinate system with UTM (Universal Transverse Mercator) projection. The data are categorized into tiles based on a latitude size of 5° and a longitude size of 6°. The file names consist of 18 characters following these rules: North-South latitude abbreviation (1 digit) + 6-degree zone number (2 digits) + "_" + starting latitude (2 digits) + "_" + product time (4 digits) + "_ " + resolution (3 digits) + "_ " + data attribute (2 digits). Additionally, each image contains a pure NDVI value band range from 0 to 100, with invalid values or water surfaces labelled as 255.
DOI: 10.17632/nkv4pnsmy5
title: Strengthening Climate-Health Literacy through Sustainability Education among dental students: A Quasi-Experimental Evaluation

description: Raw data for the article titled: Strengthening Climate-Health Literacy through Sustainability Education among dental students: A Quasi-Experimental Evaluation
DOI: 10.17632/nkv4pnsmy5.1
title: Strengthening Climate-Health Literacy through Sustainability Education among dental students: A Quasi-Experimental Evaluation

description: Raw data for the article titled: Strengthening Climate-Health Literacy through Sustainability Education among dental students: A Quasi-Experimental Evaluation
DOI: 10.5281/zenodo.17571817
title: Underwater images collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2025-11-06

description: This dataset was collected by an Autonomous Surface Vehicle in St-Leu, Réunion - 2025-11-06. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
description: The Plancha project is co-financed by the Prefecture of Reunion as part of a 2019-2022 convergence and transformation contract, measure 3.3.1.1
DOI: 10.34740/kaggle/dsv/13680889
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.uty29h
title: Occurrence Download

description: A dataset containing 751860 records in GBIF matching the query:

SELECT publishingcountry, specieskey, COUNT(*) as occurrence_count
FROM occurrence
WHERE publishingcountry IS NOT NULL AND specieskey IS NOT NULL AND publishingCountry='GB'
GROUP BY publishingcountry, specieskey
ORDER BY occurrence_count DESC;


 The dataset's 751860 records were derived from 2165 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025040-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/qah-m7p-lwm
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/5dw-7gv-smw
title: Populus L.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7l8-wgb-8ag
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/9g1-bkz-4sa
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/w25-nmy-dst
title: Muntiacus muntjak (Zimmermann, 1780)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/q34-bgg-wxc
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/tz7-ml0-xaq
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/sg8-2kg-e9d
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/pem-cns-q5l
title: Cervus Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/x5p-m3d-w2l
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/6f1-nmh-6j4
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/fdd-m7b-tzg
title: Orthiopteris Copel.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/bex-09y-gpv
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/hbs-0c0-6yl
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/0xm-fd5-jfr
title: Orthiopteris Copel.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/me8-5as-8dq
title: Paguma Gray, 1831

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/cmp-esm-37z
title: Orthiopteris Copel.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/bs1-kxc-p0g
title: Rusa C. H. Smith, 1827

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/pb0-cey-d37
title: Muntiacus muntjak (Zimmermann, 1780)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/1t8-fyk-apt
title: Rhinoceros Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/e8g-yzr-891
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/d7r-bd3-wfj
title: Crocodylus

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/lcn-7ct-8vf
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/9ma-377-01n
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/sx2-kee-zje
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/nm8-sy8-hjm
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.5281/zenodo.13240313
title: Test data sets: File B

description: I am getting an "Entity too large" error when trying to use this file as File B, with File B taxonID: BJ5N3.


The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. 

To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions.

For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](
https://eol.org/docs/eol-dynamic-hierarchy)
DOI: 10.5281/zenodo.13283240
title: Test data sets: File B

description: I am getting an "Entity too large" error when trying to use this file as File B, with File B taxonID: BJ5N3.


The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. 

To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions.

For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](
https://eol.org/docs/eol-dynamic-hierarchy)
DOI: 10.3535/5ax-wmv-tbt
title: Bovidae Gray, 1821

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/31q-zh7-ss4
title: Bovidae Gray, 1821

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/4p4-rq0-0t5
title: Bovidae Gray, 1821

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/x1q-aqs-b1w
title: Sus Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.