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

description: A dataset containing 455 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "Geometry POLYGON((-156.51217 -45.73402,9.51217 -45.73402,9.51217 20.73402,-156.51217 20.73402,-156.51217 -45.73402))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "PublishingOrg is one of (90fd6680-349f-11d8-aa2d-b8a03c50a862, 19456090-b49a-11d8-abeb-b8a03c50a862, 8e1a97a0-3ca8-11d9-8439-b8a03c50a862, 1f55bd0a-6ebe-49a1-8a9c-9258702b6f46, 7b8aff00-a9f8-11d8-944b-b8a03c50a862, bc092ff0-02e4-11dc-991f-b8a03c50a862, 396d5f30-dea9-11db-8ab4-b8a03c50a862, 746e7e20-037e-42dc-88a1-b179fe1fa944, 061b4f20-f241-11da-a328-b8a03c50a862)",
 "TaxonKey is Hypericum laricifolium Juss."
 ]
}

 The dataset includes 455 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001572-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15472789
title: TABLE 2 in Two new mainland sister species for the Taiwanese Bharetta owadai (Lepidoptera, Lasiocampidae, Lasiocampinae, Argudini)

description: TABLE 2. Uncorrected pairwise distances (%) between Bharetta spp. and the outgroup.
Species#123456Bh. sarah sp. nov.11.303.265.548.1414.33Bh. sarah sp. nov.21.304.565.548.1415.64Bh. owadai33.264.564.898.1415.64Bh. cinnamomea45.545.544.899.1215.96Ch. magna58.148.148.149.1213.68M. castrensis614.3315.6415.6415.9613.68
description: Published as part of Saldaitis, Aidas, Lien, Vu Van, Junnila, Amy, Ihle, Siegfried, Sulak, Harald, Yakovlev, Roman V., Volkova, Julia S., Müller, Günter C., Revay, Edita E., Prozorova, Tatiana A. & Prozorov, Alexey M., 2025, Two new mainland sister species for the Taiwanese Bharetta owadai (Lepidoptera, Lasiocampidae, Lasiocampinae, Argudini), pp. 473 in Zootaxa 5633 (3) on page 473, DOI: 10.11646/zootaxa.5633.3.3, http://zenodo.org/record/15435795
DOI: 10.5281/zenodo.15474188
title: Table 1 in Two poorly known Arctic sea anemones, Cactosoma abyssorum and Halcampa arctica (Actiniaria: Halcampidae)

description: Table 1. Size ranges (length × width, in microns) and distribution of cnidae of Cactosoma abyssorum. Letters in brackets correspond to letters in Fig. 3. Таблица 1. РаЗмеры (длина × Ширина, в микронах) и распределение стрекательных капсул Cactosoma abyssorum. Буквы в скобках соответствуют буквам на рис. 3.
Body regionCnidaeSize ranges (µm)Base and scapus(A) basitrichs (few)13–18 × 2.5–3.5Scapulus(B) basitrichs (very numerous)22–28 × 3.5–5Tentacles(C) spirocysts (very numerous) (D) basitrichs (common)20–44 × 2.5–4 18–25 × 2.5–4Actinopharynx(E) basitrichs (common) (F) p -mastigophores (common)17–21 × 2–4 22–30 × 4–5.5Filaments(G) basitrichs (common) (H) p -mastigophores (common)15–21 × 2–3 19–25 × 4–5Endodermbasitrichs (rare)16–21 × 2.5–3.5Physa and scapus(A) basitrichs (common)10–13 × 2–2.5Scapulus(B) spirocysts (very numerous) (C) basitrichs (common)18–28 × 2.5–3.5 12–15 × 2Tentacles(D) spirocysts (very numerous) (E) basitrichs (rare)20–42 × 2–4 15–16 × 2Actinopharynx(F) basitrichs (common) (G) p -mastigophores B1 (numerous)15–16 × 2–2.5 29–40 × 5–6.5Filaments(H) basitrichs (few) (I) p -mastigophores B1 (common) (J) p -mastigophores B1 (common)14–16 × 2–3 9–11 × 4–5 23–32 × 5.5–7.5
description: Published as part of Sanamyan, N. P., Sanamyan, K. E. & Grebelnyi, S. D., 2016, Two poorly known Arctic sea anemones, Cactosoma abyssorum and Halcampa arctica (Actiniaria: Halcampidae), pp. 3-10 in Invertebrate Zoology 13 (1) on page 3, DOI: 10.15298/invertzool.13.1.01, http://zenodo.org/record/15472499
DOI: 10.5281/zenodo.15474192
title: Table 2 in Two poorly known Arctic sea anemones, Cactosoma abyssorum and Halcampa arctica (Actiniaria: Halcampidae)

description: Table 2. Size ranges (length × width, in microns) and distribution of cnidae of the specimens #5, #6 and #7 of Phellia crassa. Таблица 2. РаЗмеры (длина × Ширина, в микронах) и распределение стрекательных капсул ЭкЗемплЯров #5, #6 и #7 Phellia crassa.
Body regionCnidaeSpecimen #5 (lectotype ZMBN 105402)Specimen #6Specimen #7Base and scapusBasitrichs13–20 × 2.5–3.5 (common)15–17 × 2.5–3 (few)14–16 × 2.5–3.5 (few)ScapulusSpirocysts Basitrichs27–32 × 3.5–5 (common) 20–27 × 3–4 (very numerous)(very rare) 21–26 × 3–4.5 (very numerous)20–40 × 3–4 (very rare) 20–25 × 3–4 (very numerous)TentaclesSpirocysts Basitrichs20–40 × 2.5–4.5 (very numerous) 15–20 × 2.5–3.5 (few)20–37 × 2.5–4 (very numerous) 14–18 × 2.5–3.5 (few)17–36 × 1.5–4 (very numerous) 16–18 × 3 (rare)ActinopharynxBasitrichs p -mastigophores17–21 × 2.5–3.5 (common) 18–25 × 4–6– –– –FilamentsBasitrichs p -mastigophores16–25 × 2–3 (common) 23–26 × 5–6.5 (common)– –– –
description: Published as part of Sanamyan, N. P., Sanamyan, K. E. & Grebelnyi, S. D., 2016, Two poorly known Arctic sea anemones, Cactosoma abyssorum and Halcampa arctica (Actiniaria: Halcampidae), pp. 4 in Invertebrate Zoology 13 (1) on page 4, DOI: 10.15298/invertzool.13.1.01, http://zenodo.org/record/15472499
DOI: 10.15468/dl.pcuvf8
title: Occurrence Download

description: A dataset containing 3521 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-170.479 24.22865,-46.56186 24.22865,-46.56186 72.95484,-170.479 72.95484,-170.479 24.22865))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Salix planifolia",
 "Year 1960-2025"
 ]
}

 The dataset includes 3521 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033462-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zvfbrw
title: Occurrence Download

description: A dataset containing 14249 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Arhopalus rusticus",
 "Year 1000-2025"
 ]
}

 The dataset includes 14249 records from 375 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033466-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nmzvp7
title: Occurrence Download

description: A dataset containing 4115 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Canada",
 "Country is Canada"
 ]
 },
 "TaxonKey is one of (Salix planifolia [GBIF Backbone Taxonomy])"
 ]
}

 The dataset includes 4115 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033467-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gvghtg
title: Occurrence Download

description: A dataset containing 321990 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Thunnus"
 ]
}

 The dataset includes 321990 records from 372 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033429-251025141854904/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.29250797
title: Comprehensive Climate, Soil, Agronomic, and Management Dataset for Data-Driven Cotton Irrigation in NW China

description: This paper introduces a unique agricultural multimodal dataset that integrates climate and weather data, real-time soil sensor data (moisture, temperature, and fertility), crop management records, visible and multispectral images of cotton plant, spore and insect images, agronomic and yield data, specifically designed for cotton yield prediction and smart irrigation in the semi-arid climate of northwest China. To validate its utility, we employed multiple machine learning approaches (reinforcement learning, DNNs, XGBoost, MLP, and random forests) to model irrigation-yield dynamics and optimize irrigation strategies. Simulation experiments and field validation show that accurate quantitative irrigation can achieve maximum crop yield or maximum water productivity, underscoring the dataset's potential for data-driven agricultural research, smart decision-making, and sustainable agricultural practices.
DOI: 10.6084/m9.figshare.29250797.v4
title: Comprehensive Climate, Soil, Agronomic, and Management Dataset for Data-Driven Cotton Irrigation in NW China

description: This paper introduces a unique agricultural multimodal dataset that integrates climate and weather data, real-time soil sensor data (moisture, temperature, and fertility), crop management records, visible and multispectral images of cotton plant, spore and insect images, agronomic and yield data, specifically designed for cotton yield prediction and smart irrigation in the semi-arid climate of northwest China. To validate its utility, we employed multiple machine learning approaches (reinforcement learning, DNNs, XGBoost, MLP, and random forests) to model irrigation-yield dynamics and optimize irrigation strategies. Simulation experiments and field validation show that accurate quantitative irrigation can achieve maximum crop yield or maximum water productivity, underscoring the dataset's potential for data-driven agricultural research, smart decision-making, and sustainable agricultural practices.
DOI: 10.6084/m9.figshare.29250797.v3
title: Comprehensive Climate, Soil, Agronomic, and Management Dataset for Data-Driven Cotton Irrigation in NW China

description: This paper introduces a unique agricultural multimodal dataset that integrates climate and weather data, real-time soil sensor data (moisture, temperature, and fertility), crop management records, visible and multispectral images of cotton plant, spore and insect images, agronomic and yield data, specifically designed for cotton yield prediction and smart irrigation in the semi-arid climate of northwest China. To validate its utility, we employed multiple machine learning approaches (reinforcement learning, DNNs, XGBoost, MLP, and random forests) to model irrigation-yield dynamics and optimize irrigation strategies. Simulation experiments and field validation show that accurate quantitative irrigation can achieve maximum crop yield or maximum water productivity, underscoring the dataset's potential for data-driven agricultural research, smart decision-making, and sustainable agricultural practices.
DOI: 10.6084/m9.figshare.30444956
title: What is the best way of collecting data donations? An experiment assessing the feasibility of different data donation approaches to measure mobile and app usage

description: Smartphones are now ubiquitous in daily life, requiring the development of accurate methodologies to study their impact on various aspects of human experience. A promising approach to collect mobile log data is to ask participants to donate, in the context of online surveys, the data that is already available to them through features such as iOS Screen Time and Android Digital Wellbeing. This approach grants participants control over the data they share while providing researchers with valuable observational insights into their mobile and app behaviours. However, the active involvement required from participants poses challenges, leading to low compliance rates and potential biases in the final sample of donors. This study investigates whether the method used to collect data donations, and the incentives provided, have an impact on compliance rates, and the subsequent composition of the sample. Specifically, we implemented a 2 × 3 between-subject web survey experiment (N = 872) in a research-led probability-based panel in Switzerland. Participants were randomly asked to capture and share their data through screenshots, video recordings, and by manual imputation (which we call enhanced recall). Results show that, while compliance rates are very low when using screenshots and video recordings as data donation methods, almost two thirds of participants donated their data by manually imputing their log data. We also found donors to be younger and more technologically adept. Overall, our study sheds light on maximising compliance in data donation studies, offering insights for researchers studying mobile and app usage.
DOI: 10.6084/m9.figshare.30444956.v2
title: What is the best way of collecting data donations? An experiment assessing the feasibility of different data donation approaches to measure mobile and app usage

description: Smartphones are now ubiquitous in daily life, requiring the development of accurate methodologies to study their impact on various aspects of human experience. A promising approach to collect mobile log data is to ask participants to donate, in the context of online surveys, the data that is already available to them through features such as iOS Screen Time and Android Digital Wellbeing. This approach grants participants control over the data they share while providing researchers with valuable observational insights into their mobile and app behaviours. However, the active involvement required from participants poses challenges, leading to low compliance rates and potential biases in the final sample of donors. This study investigates whether the method used to collect data donations, and the incentives provided, have an impact on compliance rates, and the subsequent composition of the sample. Specifically, we implemented a 2 × 3 between-subject web survey experiment (N = 872) in a research-led probability-based panel in Switzerland. Participants were randomly asked to capture and share their data through screenshots, video recordings, and by manual imputation (which we call enhanced recall). Results show that, while compliance rates are very low when using screenshots and video recordings as data donation methods, almost two thirds of participants donated their data by manually imputing their log data. We also found donors to be younger and more technologically adept. Overall, our study sheds light on maximising compliance in data donation studies, offering insights for researchers studying mobile and app usage.
DOI: 10.71760/ukllc-dataset-00439-09
title: UK LLC Managed: NHSE Patient Service Usage Dataset
title: UKLLC_nhse_patient_service_usage

description: Contains the number of appearances and the date of the most recent appearance for each participant for each available NHS England data sources in the UK LLC database. There is one row per participant. The table also includes a ‘last seen date’ for each participant as the most recent record across all NHS data sources.
DOI: 10.71760/ukllc-dataset-00441-04
title: UK LLC Managed: NHSE LSOA11 Mappings Dataset
title: UKLLC_nhse_lsoa11_dataset_mapping

description: This dataset has one row per health interaction where the project has selected the LPS and where participant permissions are in place. The indicator picks from the following NHS datasets where Lower Super Output Area 2011 (LSOA11) is routinely available
DOI: 10.5281/zenodo.17610635
title: Dataset for article "Molecular engineering of individual dye-based nanoparticle photostability for ultrabright two-photon fluorescence"

description: This dataset gather all the raw datas used to produce the figures of the manuscript "Molecular engineering of individual dye-based nanoparticle photostability for ultrabright two-photon fluorescence" by Kurek et al.

The datas have been recorded as .txt files. The attached README file gives all the details of the data files organisation.
DOI: 10.71760/ukllc-dataset-00440-08
title: UK LLC Managed: NHSE Patient Demo Mortality Dataset
title: UKLLC_nhse_patient_demo_mortality

description: Contains the most recent and most reliable record for certain key demographic variables sourced from NHS data sources in the UK LLC database. There is one row per participant.
DOI: 10.5281/zenodo.17610634
title: Dataset for article "Molecular engineering of individual dye-based nanoparticle photostability for ultrabright two-photon fluorescence"

description: This dataset gather all the raw datas used to produce the figures of the manuscript "Molecular engineering of individual dye-based nanoparticle photostability for ultrabright two-photon fluorescence" by Kurek et al.

The datas have been recorded as .txt files. The attached README file gives all the details of the data files organisation.
DOI: 10.15468/dl.hceswr
title: Occurrence Download

description: A dataset containing 98 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 2a7e3080-28a9-11dd-97cd-b8a03c50a862",
 "TaxonKey is Puma concolor"
 ]
}

 The dataset includes 98 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033468-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vncy3j
title: Occurrence Download

description: A dataset containing 4403 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "GadmGid is USA.41_1",
 "TaxonKey is Alligator mississippiensis"
 ]
}

 The dataset includes 4403 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033470-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17560424
title: Dataset and Computational Experiment Results for "Dual-Driven Path Elimination for Vehicle Routing with Idle Times and Arrival-Time Consistency"

description: This repository contains all input and output files associated with the computational experiments described in the article:



Jorge Riera-Ledesma, Inmaculada Rodríguez-Martín, Hipólito Hernández–Pérez,Dual-driven path elimination for vehicle routing with idle times and arrival-time consistency,Computers & Operations Research,2025,107326,https://doi.org/10.1016/j.cor.2025.107326.




Computational Environment


All algorithms were implemented in C++ and compiled with gcc version 13.3.0 on Ubuntu 24.04 LTS, using the -O2 optimization flag. Experiments were executed on a single core of an Intel Core i5-7500 processor with 20 GB RAM.

The CPLEX 22.1 solver (via its callable library) was used to solve the branch-and-cut implementations. A time limit of 7200 seconds was imposed for each instance, replicating the computational setup adopted in:



A Decomposition Algorithm for the Consistent Traveling Salesman Problem with Vehicle Idling,Anirudh Subramanyam and Chrysanthos E. Gounaris, Transportation Science (2018), 52(2), 386–401.
DOI: 10.5281/zenodo.17560423
title: Dataset and Computational Experiment Results for "Dual-Driven Path Elimination for Vehicle Routing with Idle Times and Arrival-Time Consistency"

description: This repository contains all input and output files associated with the computational experiments described in the article:



Jorge Riera-Ledesma, Inmaculada Rodríguez-Martín, Hipólito Hernández–Pérez,Dual-driven path elimination for vehicle routing with idle times and arrival-time consistency,Computers & Operations Research,2025,107326,https://doi.org/10.1016/j.cor.2025.107326.




Computational Environment


All algorithms were implemented in C++ and compiled with gcc version 13.3.0 on Ubuntu 24.04 LTS, using the -O2 optimization flag. Experiments were executed on a single core of an Intel Core i5-7500 processor with 20 GB RAM.

The CPLEX 22.1 solver (via its callable library) was used to solve the branch-and-cut implementations. A time limit of 7200 seconds was imposed for each instance, replicating the computational setup adopted in:



A Decomposition Algorithm for the Consistent Traveling Salesman Problem with Vehicle Idling,Anirudh Subramanyam and Chrysanthos E. Gounaris, Transportation Science (2018), 52(2), 386–401.
DOI: 10.5517/ccdc.csd.cc2mgypr
title: CCDC 2427445: Experimental Crystal Structure Determination

description: Related Article: Alba Cortés-Martínez, Pilar Fernández-Seriñán, Cornelia von Baeckmann, Caterina Caules, Laura Hernández-López, María Susana Gutiérrez, Yunhui Yang, Roberto Sánchez-Naya, José A. Suárez del Pino, Judith Juanhuix, Inhar Imaz, Arnau CarnéSánchez, Daniel Maspoch|2025|Angew.Chem.,Int.Ed.|64|e202505682|doi:10.1002/anie.202505682
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.cc2mgyqs
title: CCDC 2427446: Experimental Crystal Structure Determination

description: Related Article: Alba Cortés-Martínez, Pilar Fernández-Seriñán, Cornelia von Baeckmann, Caterina Caules, Laura Hernández-López, María Susana Gutiérrez, Yunhui Yang, Roberto Sánchez-Naya, José A. Suárez del Pino, Judith Juanhuix, Inhar Imaz, Arnau CarnéSánchez, Daniel Maspoch|2025|Angew.Chem.,Int.Ed.|64|e202505682|doi:10.1002/anie.202505682
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.cc2mgyrt
title: CCDC 2427447: Experimental Crystal Structure Determination

description: Related Article: Alba Cortés-Martínez, Pilar Fernández-Seriñán, Cornelia von Baeckmann, Caterina Caules, Laura Hernández-López, María Susana Gutiérrez, Yunhui Yang, Roberto Sánchez-Naya, José A. Suárez del Pino, Judith Juanhuix, Inhar Imaz, Arnau CarnéSánchez, Daniel Maspoch|2025|Angew.Chem.,Int.Ed.|64|e202505682|doi:10.1002/anie.202505682
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: 10.15468/dl.t3wecm
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Myrciaria splendens",
 "Year 1970-2025"
 ]
}

 The dataset includes 11 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033471-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.