cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.jcs5b9
title: Occurrence Download

description: A dataset containing 3544 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Japan",
 "TaxonKey is Reynoutria japonica"
 ]
}

 The dataset includes 3544 records from 111 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027730-251120083545085/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/13987510
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.17026/ar/yor5dr
title: PAN-00112297 - coin/coin-related, Septimius Severus (193-211), denarius

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00112297&lt;/p&gt;
description: Modified: 2025-06-17T09:13:59+02:00
DOI: 10.15468/dl.8avdcr
title: Occurrence Download

description: A dataset containing 352 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 69.085278",
 "DecimalLatitude is less than or equal to 74.085278",
 "DecimalLongitude is greater than or equal to -100.0",
 "DecimalLongitude is less than or equal to -95.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 352 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027733-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sqt8jq
title: Occurrence Download

description: A dataset containing 3972 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ilex fargesii, Ilex chengkouensis, Ilex cheniana, Ilex chinensis, Ilex chingiana)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3972 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027734-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17813122
title: Data for the controlled flood of the Ebro River on May 5 2022

description: Suspended sediment concentration for the controlled flood of the Ebro River on May 5 2022
DOI: 10.5281/zenodo.17813123
title: Data for the controlled flood of the Ebro River on May 5 2022

description: Suspended sediment concentration for the controlled flood of the Ebro River on May 5 2022
DOI: 10.15125/bath-01424
title: Dataset for "What is the effect of presenting evidence of the mental vs physical health benefits of quitting smoking on motivation to stop smoking? An online randomised controlled experiment"

description: Using this dataset we assessed whether mental health labels presenting information of the benefits of quitting smoking for mental health was more effective than blank labels and physical health labels, and if there were any differences between those with mental ill health, or not. 

Participants took part in an online randomised experiment, with three conditions: i) mental health labels; ii) physical health labels; iii) blank labels. Participants were randomly allocated to label condition, stratified by mental health status, and viewed four labels for at least 10 seconds each. Motivation to stop smoking was measured using the Motivation to Stop Scale (MTSS) before and after viewing the labels.
description: Full details of the study protocol are available from the OSF Project "Positive Messaging for Tobacco Packaging" (Sawyer et al., 2024).
description: Further relevant documentation may be found in the following resources.

   Sawyer, K., Burke, C., Taylor, G. M., Jacobsen, P. C., Gill, F., Freeman, T., Adams, S., Aveyard, P., and Hanafi, A.,  2024.   Positive Messaging for Tobacco Packaging.         OSF.  Available from: https://doi.org/10.17605/OSF.IO/3C75J.
DOI: 10.15468/dl.qr3fgc
title: Occurrence Download

description: A dataset containing 1418 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Tamarix, , , , , , , , , , , , , , , , , , , , , , , , , Obdulia, , , , Diorhabda, , , Cryptoparlatoreopsis, Deserticossus, , Lampetis, , , Cyphosoma, , Tropiocolotes, , , , , Chivaenius, Poophilus, , , Helopelius, Sphenoptera, Istrianis, , , , , , , , , Exaesiopus)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((70 40,103 40,103 60,70 60,70 40))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 1418 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027735-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10476105
title: Supplementary Data: Movement-driven modeling reveals new patterns in disease transmission networks

description: Interactions between individuals of different species are highly relevant in the potential transmission of shared pathogens in multi-host systems. In recent decades, several technologies to study pathogen transmission have been developed, such as proximity loggers, GPS tracking devices, and/or camera traps. Despite the diversity of methods aimed at detecting contacts, the analysis of transmission risk is often reduced to contact rates and the probability of transmission given contact. However, the latter process is continuous over time and unique for each contact, and it is influenced by the characteristics of the contact and the pathogen's relationship with both the host and the environment. In this study, we utilized a movement-based model that decomposes transmission into contact formation, contact duration, and host characteristics, assigning a unique transmission risk to each contact. We aimed to assess whether this more comprehensive approach reveals disease transmission dynamics that are not detected with more traditional approaches. The model was built from GPS data from two management systems in Spain where animal tuberculosis (TB) circulates: a national park, and an area with extensive free-range pigs and cattle farms. In addition, we assessed the effect of the GPS device sampling rate on the performance of the model. Considering the specific conditions under which each contact occurs (i.e., whether the contact is direct or indirect, its duration, the hosts characteristics, the environmental conditions, etc.) resulted in the identification of different transmission dynamics compared to a model based solely on contact rates. This indicates that not taking these conditions into account may result in misidentifying the key species in disease transmission. The different transmission dynamics identified between both management systems highlight the need to analyze each system independently. We found that temporal intervals greater than 30 minutes in the GPS tracking data resulted in missed interactions, and intervals greater than 2 hours may be insufficient in interaction studies for epidemiological purposes. This study describes a clear and repeatable methodology to study pathogen transmission from GPS data, and provides further insights to understand how TB is maintained in multi-host systems under different management scenarios in Mediterranean environments.
DOI: 10.5281/zenodo.8377694
title: Supplementary Data: Movement-driven modeling reveals new patterns in disease transmission networks

description: Interactions between individuals of different species are highly relevant in the potential transmission of shared pathogens in multi-host systems. In recent decades, several technologies to study pathogen transmission have been developed, such as proximity loggers, GPS tracking devices, and/or camera traps. Despite the diversity of methods aimed at detecting contacts, the analysis of transmission risk is often reduced to contact rates and the probability of transmission given contact. However, the latter process is continuous over time and unique for each contact, and it is influenced by the characteristics of the contact and the pathogen's relationship with both the host and the environment. In this study, we utilized a movement-based model that decomposes transmission into contact formation, contact duration, and host characteristics, assigning a unique transmission risk to each contact. We aimed to assess whether this more comprehensive approach reveals disease transmission dynamics that are not detected with more traditional approaches. The model was built from GPS data from two management systems in Spain where animal tuberculosis (TB) circulates: a national park, and an area with extensive free-range pigs and cattle farms. In addition, we assessed the effect of the GPS device sampling rate on the performance of the model. Considering the specific conditions under which each contact occurs (i.e., whether the contact is direct or indirect, its duration, the hosts characteristics, the environmental conditions, etc.) resulted in the identification of different transmission dynamics compared to a model based solely on contact rates. This indicates that not taking these conditions into account may result in misidentifying the key species in disease transmission. The different transmission dynamics identified between both management systems highlight the need to analyze each system independently. We found that temporal intervals greater than 30 minutes in the GPS tracking data resulted in missed interactions, and intervals greater than 2 hours may be insufficient in interaction studies for epidemiological purposes. This study describes a clear and repeatable methodology to study pathogen transmission from GPS data, and provides further insights to understand how TB is maintained in multi-host systems under different management scenarios in Mediterranean environments.
DOI: 10.6084/m9.figshare.30784370
title: Informal Conversation Guide

description: Research assistants built rapport with family members during home visit and engaged with adults in informal conversation about their daily lives, their views on TB as an illness, TB prevention practices, and their experiences accessing TB care, including contact tracing. The informal conversation was not audio-recorded and the research assistant did not use any script but followed the broad topics as developed in the topic guide
DOI: 10.6084/m9.figshare.30784370.v1
title: Informal Conversation Guide

description: Research assistants built rapport with family members during home visit and engaged with adults in informal conversation about their daily lives, their views on TB as an illness, TB prevention practices, and their experiences accessing TB care, including contact tracing. The informal conversation was not audio-recorded and the research assistant did not use any script but followed the broad topics as developed in the topic guide
DOI: 10.15468/dl.aebbua
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dendrolagus dorianus",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 25 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027736-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23673/re-561
title: Data of binary transition metal and nitrogen functionalised silicon oxycarbide electrocatalysts for zn–air battery air electrode application

description: This dataset contains the data presented in the figures of published paper "Binary transition metal and nitrogen functionalised silicon oxycarbide electrocatalysts for zn–air battery air electrode application" International Journal of Energy Research 2025 252866 (https://doi.org/10.1155/er/4252866).
 The electrochemical characterisation data, which was measured in University of Tartu Institute of Chemistry, is for Figures 5, 6, 7, 8 and the nomenclature of the catalysts is the same as in the mentioned article.
DOI: 10.17026/ar/agwpdf
title: PAN-00172431 - lower pump box

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00172431&lt;/p&gt;
description: Modified: 2025-09-17T09:53:34+02:00
DOI: 10.15468/dl.wj2xuu
title: Occurrence Download

description: A dataset containing 151 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mastigeulota kiangsinensis"
 ]
}

 The dataset includes 151 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027738-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rtwea6
title: Occurrence Download

description: A dataset containing 1794 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Abies, , , , , , , , , , , , , , , Abies, , , Abies, , , , , , , Parapsallus, , , , , , , , , , Subilla, Pityokteines, , , , , , , , Corymbitodes, Lysitermus, , , , , , Elatobium, Atractotomoidea, , Pityophthorus, , , , Cupressopathes, Beckerus, , , , , Myriopathes, Semanotus, , Pseudolorryia, , , , Dentatosoma, , , Exoteleia, Proedromys, , , Cryphalus, , , , , , Chrysina, , Gelanes, , Neofusicoccum, , , , Phellopsis, Acryptolaria, , , , , Pseudotelphusa, Cembrotia, Neolygus, Harpactea, Paractenicera, , , , , , , , , , , , , , , , , , Parajulus, Brachytydeus, Coleotechnites, , , , , , Nesodiprion, , , Picea, , Hypocampsis, Panthea)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((70 40,103 40,103 60,70 60,70 40))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 1794 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027740-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10605831
title: Supplementary Data: Camera trapping and GPS telemetry for detecting and quantifying animal interactions: Not anything goes

description: Abstract

GPS telemetry and camera trapping are two widely used approaches to detect animal interactions involving wildlife. However, while the former follows an individual-based approach, the latter follows a population-based approach, which may lead to different outcomes when describing interaction networks. This study compares GPS telemetry, regular grid camera trapping (CT-RG), and resource monitoring through camera trapping (e.g., in water or food; CT-RM) for detecting and quantifying animal interactions. We used simulated trajectories of 150 individuals of 3 imaginary species. We simulated 9 different scenarios of resource visitation frequency and spatial resource aggregation to assess the potential influence of animal behavior and landscape structure. The simulated trajectories were sampled using the three approaches with six different sampling efforts each, and the direct and indirect interactions between the three species were quantified. Additionally, CT-RG and CT-RM were applied in Doñana National Park to evaluate their differences and limitations in field application. In terms of simulation, CT-RM offered the best performance in detecting direct interactions, and GPS achieved good performance at high efforts. Both also achieved good performance in detecting indirect interactions. CT-RG, on the other hand, missed most direct and indirect interactions, but correctly identified all pairs of species interacting indirectly. In the field trial, CT-RM and CT-RG detected almost the same number of pairs interacting indirectly. However, CT-RG missed at least half of the pairs of species interacting directly. GPS performs better than CT-RM when the resource is spatially aggregated, but the opposite is true when the resource is frequently visited. To summarize, CT-MR is the most reliable method for detecting interactions when resource monitoring is feasible (e.g., small ponds in arid areas). Otherwise, GPS may show better performance, although it may miss direct interactions. CT-RG should only be used to detect potential indirect interactions between species, not to quantify them.
DOI: 10.5281/zenodo.10605832
title: Supplementary Data: Camera trapping and GPS telemetry for detecting and quantifying animal interactions: Not anything goes

description: Abstract

GPS telemetry and camera trapping are two widely used approaches to detect animal interactions involving wildlife. However, while the former follows an individual-based approach, the latter follows a population-based approach, which may lead to different outcomes when describing interaction networks. This study compares GPS telemetry, regular grid camera trapping (CT-RG), and resource monitoring through camera trapping (e.g., in water or food; CT-RM) for detecting and quantifying animal interactions. We used simulated trajectories of 150 individuals of 3 imaginary species. We simulated 9 different scenarios of resource visitation frequency and spatial resource aggregation to assess the potential influence of animal behavior and landscape structure. The simulated trajectories were sampled using the three approaches with six different sampling efforts each, and the direct and indirect interactions between the three species were quantified. Additionally, CT-RG and CT-RM were applied in Doñana National Park to evaluate their differences and limitations in field application. In terms of simulation, CT-RM offered the best performance in detecting direct interactions, and GPS achieved good performance at high efforts. Both also achieved good performance in detecting indirect interactions. CT-RG, on the other hand, missed most direct and indirect interactions, but correctly identified all pairs of species interacting indirectly. In the field trial, CT-RM and CT-RG detected almost the same number of pairs interacting indirectly. However, CT-RG missed at least half of the pairs of species interacting directly. GPS performs better than CT-RM when the resource is spatially aggregated, but the opposite is true when the resource is frequently visited. To summarize, CT-MR is the most reliable method for detecting interactions when resource monitoring is feasible (e.g., small ponds in arid areas). Otherwise, GPS may show better performance, although it may miss direct interactions. CT-RG should only be used to detect potential indirect interactions between species, not to quantify them.
DOI: 10.15468/dl.4e3r43
title: Occurrence Download

description: A dataset containing 8984 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ilex cinerea, Ilex cochinchinensis, Ilex confertiflora, Ilex corallina, Ilex crenata)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8984 records from 194 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027741-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15791299
title: An Indoor Radio Mapping Dataset Combining 3D Point Clouds and RSSI

description: The growing number of smart devices supporting bandwidth-intensive and latency-sensitive applications, such as real-timevideo analytics, smart sensing, Extended Reality (XR), etc., necessitates reliable wireless connectivity in indoor environments.In such environments, accurate design of Radio Environment Maps (REMs) enables adaptive wireless network planning andoptimization of Access Point (AP) placement. However, generating realistic REMs remains difficult due to the variability ofindoor environments and the limitations of existing modeling approaches, which often rely on simplified layouts or fully syntheticdata. These challenges are further amplified by the adoption of next-generation Wi-Fi standards, which operate at higherfrequencies and suffer from limited range and wall penetration. To support the efforts in addressing these challenges, wecollected a dataset that combines high-resolution 3D LiDAR scans with Wi-Fi RSSI measurements collected across 20 setupsin a multi-room indoor environment. The dataset includes two measurement scenarios, the first without human presence in theenvironment, and the second with human presence, enabling the development and validation of REM estimation models thatincorporate physical geometry and environmental dynamics. The described dataset supports research in data-driven wirelessmodeling and the development of high-capacity indoor communication networks.
DOI: 10.5281/zenodo.15791300
title: An Indoor Radio Mapping Dataset Combining 3D Point Clouds and RSSI

description: The growing number of smart devices supporting bandwidth-intensive and latency-sensitive applications, such as real-timevideo analytics, smart sensing, Extended Reality (XR), etc., necessitates reliable wireless connectivity in indoor environments.In such environments, accurate design of Radio Environment Maps (REMs) enables adaptive wireless network planning andoptimization of Access Point (AP) placement. However, generating realistic REMs remains difficult due to the variability ofindoor environments and the limitations of existing modeling approaches, which often rely on simplified layouts or fully syntheticdata. These challenges are further amplified by the adoption of next-generation Wi-Fi standards, which operate at higherfrequencies and suffer from limited range and wall penetration. To support the efforts in addressing these challenges, wecollected a dataset that combines high-resolution 3D LiDAR scans with Wi-Fi RSSI measurements collected across 20 setupsin a multi-room indoor environment. The dataset includes two measurement scenarios, the first without human presence in theenvironment, and the second with human presence, enabling the development and validation of REM estimation models thatincorporate physical geometry and environmental dynamics. The described dataset supports research in data-driven wirelessmodeling and the development of high-capacity indoor communication networks.
DOI: 10.15468/dl.gph2gd
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dendrolagus goodfellowi",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 16 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027742-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.