cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14712024
title: Wave attenuation of seagrass in combined wave-current flows

description: The database contain post-processed data of: wave attenuation of seagrass meadows, longitudinal flow velocity above the meadow, mean deflected height of the meadow.Experiments were performed with dynamically-scaled mimics of seagrass exposed to regular waves and a collinear current in laboratory experiments.The experiments are described in more detail in the research article "Turbulence enhances wave attenuation of seagrass in combined wave-current flows" authored by Vettori et al.
DOI: 10.15468/dl.fbhaw5
title: Occurrence Download

description: A dataset containing 7537 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plecotus auritus (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 7537 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000036-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewdqf5
title: Occurrence Download

description: A dataset containing 7881 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dypsis Noronha ex Mart.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7881 records from 146 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000037-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.43vp3q
title: Occurrence Download

description: A dataset containing 83686 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Echinocereus Engelm.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 83686 records from 141 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000038-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60507/fk2/1mttre/7epxeo
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_0.feather
DOI: 10.60507/fk2/1mttre/ammm9o
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_1.feather
DOI: 10.60507/fk2/1mttre/fz2tcn
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_3.feather
DOI: 10.60507/fk2/1mttre/i9olga
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_2.feather
DOI: 10.60507/fk2/1mttre/xjmqut
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_4.feather
DOI: 10.7483/opendata.cms.uql1.0c31
title: /DYToMuMu_M-20_CT10_8TeV-powheg-pythia6/Summer12_DR53X-PU_S10_START53_V19-v1/AODSIM
DOI: 10.60507/fk2/1mttre/6j8vhd
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_8.feather
DOI: 10.60507/fk2/1mttre/6v4jvw
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_9.feather
DOI: 10.60507/fk2/1mttre/heznvx
title: README.txt
DOI: 10.60507/fk2/1mttre/lodilh
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_7.feather
DOI: 10.60507/fk2/1mttre/nvd3bh
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_6.feather
DOI: 10.60507/fk2/1mttre/uz3yfi
title: DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_5.feather
DOI: 10.60507/fk2/1mttre/wee5vc
title: Example.py
DOI: 10.5281/zenodo.14711561
title: NIBIO_UAV_tree_damage

description:  

🌟 Introduction

This repository provides the data used in the research by Puliti and Astrup (2022) Automatic detection of snow breakage at single tree level using YOLOv5 applied to UAV imagery. International Journal of Applied Earth Observation and Geoinformation, 112, p.102946.

 

🌲 Scope of the Data

This dataset is intended for:🔍 Development and benchmarking of object detection models for individual trees and classification of trees based on their health.

Data is provided in the YOLO format with bounding box labels 📦🌲

 













🖥️ Existing Code and Model

The code for model inference, as described in the paper by Puliti and Astrup (2022), is available in the following GitHub repository:

🔗 GitHub Repository for Model Inference

This repository includes:



Inference Scripts: Scripts to apply the trained YOLOv5 model for detecting snow breakage at the single-tree level. 🌲

Pre-trained Models: Downloadable weights for reproducing results from the publication.

Example Workflows: Step-by-step guidance for running the model on your own UAV imagery. 🚁


Make sure to follow the repository’s documentation for setup instructions, dependencies, and usage examples. 💻

 







📜 Citation

If you use this dataset, please give credit by citing the original paper:

@article{PULITI2022102946,title = {Automatic detection of snow breakage at single tree level using YOLOv5 applied to UAV imagery},journal = {International Journal of Applied Earth Observation and Geoinformation},volume = {112},pages = {102946},year = {2022},issn = {1569-8432},doi = {https://doi.org/10.1016/j.jag.2022.102946},url = {https://www.sciencedirect.com/science/article/pii/S1569843222001431},author = {Stefano Puliti and Rasmus Astrup},keywords = {Forest damage, Convolutional neural network, Deep-learning, Drones, Object detection}}

 

⚖️ Licensing

📄 Please refer to the specific licenses below for details on how the data can be used.

🔑 Key Licensing Principles:



✅ You may access, use, and share the dataset and models freely.

🔄 Any derivative works (e.g., trained models, code for training, or prediction tools) must also be made publicly available under the same licensing terms.

🌍 These licenses promote collaboration and transparency, ensuring that research using this dataset benefits the broader scientific and open-source community 🙌
DOI: 10.5281/zenodo.14711562
title: NIBIO_UAV_tree_damage

description:  

🌟 Introduction

This repository provides the data used in the research by Puliti and Astrup (2022) Automatic detection of snow breakage at single tree level using YOLOv5 applied to UAV imagery. International Journal of Applied Earth Observation and Geoinformation, 112, p.102946.

 

🌲 Scope of the Data

This dataset is intended for:🔍 Development and benchmarking of object detection models for individual trees and classification of trees based on their health.

Data is provided in the YOLO format with bounding box labels 📦🌲

 













🖥️ Existing Code and Model

The code for model inference, as described in the paper by Puliti and Astrup (2022), is available in the following GitHub repository:

🔗 GitHub Repository for Model Inference

This repository includes:



Inference Scripts: Scripts to apply the trained YOLOv5 model for detecting snow breakage at the single-tree level. 🌲

Pre-trained Models: Downloadable weights for reproducing results from the publication.

Example Workflows: Step-by-step guidance for running the model on your own UAV imagery. 🚁


Make sure to follow the repository’s documentation for setup instructions, dependencies, and usage examples. 💻

 







📜 Citation

If you use this dataset, please give credit by citing the original paper:

@article{PULITI2022102946,title = {Automatic detection of snow breakage at single tree level using YOLOv5 applied to UAV imagery},journal = {International Journal of Applied Earth Observation and Geoinformation},volume = {112},pages = {102946},year = {2022},issn = {1569-8432},doi = {https://doi.org/10.1016/j.jag.2022.102946},url = {https://www.sciencedirect.com/science/article/pii/S1569843222001431},author = {Stefano Puliti and Rasmus Astrup},keywords = {Forest damage, Convolutional neural network, Deep-learning, Drones, Object detection}}

 

⚖️ Licensing

📄 Please refer to the specific licenses below for details on how the data can be used.

🔑 Key Licensing Principles:



✅ You may access, use, and share the dataset and models freely.

🔄 Any derivative works (e.g., trained models, code for training, or prediction tools) must also be made publicly available under the same licensing terms.

🌍 These licenses promote collaboration and transparency, ensuring that research using this dataset benefits the broader scientific and open-source community 🙌
DOI: 10.15468/dl.k5t3pk
title: Occurrence Download

description: A dataset containing 10636 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eptesicus serotinus (Schreber, 1774)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 10636 records from 171 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000041-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nfucbw
title: Occurrence Download

description: A dataset containing 91431 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhododendron ferrugineum L."
 ]
}

 The dataset includes 91431 records from 385 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000035-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xdbrjw
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ukraine",
 "OccurrenceStatus is Present",
 "TaxonKey is Ictalurus punctatus (Rafinesque, 1818)"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000042-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14712218
title: How avatar can enhance autobiographical memory of patients with substance use disorder

description: Dataset associated with the paper: "How avatar can enhance autobiographical memory of patients with substance use disorder"

This set of raw cannot be made publicly available as including sensitive information, but might be made available to interested researchers upon reasonable requests. Please, forward your request to: fabio.frisone@unicatt.it
DOI: 10.5281/zenodo.14712219
title: How avatar can enhance autobiographical memory of patients with substance use disorder

description: Dataset associated with the paper: "How avatar can enhance autobiographical memory of patients with substance use disorder"

This set of raw cannot be made publicly available as including sensitive information, but might be made available to interested researchers upon reasonable requests. Please, forward your request to: fabio.frisone@unicatt.it
DOI: 10.15468/dl.6x99r8
title: Occurrence Download

description: A dataset containing 2787 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "Country is one of (United States of America, United States Minor Outlying Islands, American Samoa, Micronesia (Federated States of), Guam, Marshall Islands, Northern Mariana Islands, Puerto Rico, Palau, Virgin Islands (U.S.))",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Hybognathus hankinsoni Hubbs, 1929)"
 ]
}

 The dataset includes 2787 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000044-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k5km67
title: Occurrence Download

description: A dataset containing 166 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plecotus austriacus (J.Fischer, 1829)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 166 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000043-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.krmaz4
title: Occurrence Download

description: A dataset containing 14327 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lepus timidus Linnaeus, 1758",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 14327 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000045-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25403/upresearchdata.28247180
title: Level up! digital art exhibition design, layout and final display images : virtual exhibition

description: Researcher developed and curated an online virtual reality group exhibition of selected young female South African artists. In order to do so, I have utilized the advantages presented by virtual reality technology, technologies developed predominantly in the world of gaming to generate an immersive and present viewer experience. The researcher showcase how such an approach towards creating digital exhibitions, embody a number of productive advances over two-dimensional digitally curated exhibitions. Here I refer to the writings of A. Schleiner (2003), S. Foo (2008) and G. Hull and J. Scott (2014) arguing that a shift towards technological displays are inevitable as our audiences continue to evolve. I also refer to the writings of J. Mütterlein (2008), J. Radianti, T.A. Majchrzak, J. Fromm and I. Wohlgenannt (2019), and L. Hyunae, T. Jung, M.C. Dieck and N. Chung (2019) for analysis of various virtual reality display models and devices. Throughout the research study concepts of ‘presence’ and ‘immersion’ as defined by M. Slater (2003) and K.R. Christy and J. Fox (2016), the research paper furthermore also touches on concepts of interactivity as described by E. & G. Coulter-Smith (2006) and calls for more multisensory art experiences such as those by W. Boshoff (1997) and J. Lauwrens (2012)(2022).The final virtual exhibition titled Level Up! is presented as part of the research project and features a series of three solo exhibition experiences presented as interactive art installations. Each level has been designed in collaboration with the individual artists in order to create multisensory site-specific installations. The virtual exhibition features ceramics by Viola Greyling, works on paper by Laura de Harde and prints by Amy-Jane van den Bergh. The virtual exhibition is presented as a downloadable computer game which has been carefully curated to enhance a user’s sense of presence when experiencing artworks in a digital environment.
DOI: 10.25403/upresearchdata.28247180.v1
title: Level up! digital art exhibition design, layout and final display images : virtual exhibition

description: Researcher developed and curated an online virtual reality group exhibition of selected young female South African artists. In order to do so, I have utilized the advantages presented by virtual reality technology, technologies developed predominantly in the world of gaming to generate an immersive and present viewer experience. The researcher showcase how such an approach towards creating digital exhibitions, embody a number of productive advances over two-dimensional digitally curated exhibitions. Here I refer to the writings of A. Schleiner (2003), S. Foo (2008) and G. Hull and J. Scott (2014) arguing that a shift towards technological displays are inevitable as our audiences continue to evolve. I also refer to the writings of J. Mütterlein (2008), J. Radianti, T.A. Majchrzak, J. Fromm and I. Wohlgenannt (2019), and L. Hyunae, T. Jung, M.C. Dieck and N. Chung (2019) for analysis of various virtual reality display models and devices. Throughout the research study concepts of ‘presence’ and ‘immersion’ as defined by M. Slater (2003) and K.R. Christy and J. Fox (2016), the research paper furthermore also touches on concepts of interactivity as described by E. & G. Coulter-Smith (2006) and calls for more multisensory art experiences such as those by W. Boshoff (1997) and J. Lauwrens (2012)(2022).The final virtual exhibition titled Level Up! is presented as part of the research project and features a series of three solo exhibition experiences presented as interactive art installations. Each level has been designed in collaboration with the individual artists in order to create multisensory site-specific installations. The virtual exhibition features ceramics by Viola Greyling, works on paper by Laura de Harde and prints by Amy-Jane van den Bergh. The virtual exhibition is presented as a downloadable computer game which has been carefully curated to enhance a user’s sense of presence when experiencing artworks in a digital environment.
DOI: 10.15468/dl.cmvh5t
title: Occurrence Download

description: A dataset containing 287 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Austria",
 "TaxonKey is Lumbricus rubellus Hoffmeister, 1843"
 ]
}

 The dataset includes 287 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000046-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14712262
title: Coordination of transporter, cargo, and membrane properties during non-vesicular lipid transport

description: Source data for publication Coordination of transporter, cargo, and membrane properties during non-vesicular lipid transport

Source data for Figs.2-8. Fig. 1 does not contain any experimental data.
DOI: 10.15468/dl.7k2e8y
title: Occurrence Download

description: A dataset containing 421 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Spermophilus citellus (Linnaeus, 1766)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2013",
 "Year is less than or equal to 2018",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 421 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000048-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14712263
title: Coordination of transporter, cargo, and membrane properties during non-vesicular lipid transport

description: Source data for publication Coordination of transporter, cargo, and membrane properties during non-vesicular lipid transport

Source data for Figs.2-8. Fig. 1 does not contain any experimental data.
DOI: 10.15468/dl.epsqa9
title: Occurrence Download

description: A dataset containing 146256 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Galanthus alpinus Sosn., Galanthus angustifolius Koss, Galanthus cilicicus Baker, Galanthus elwesii Hook.f., Galanthus fosteri Baker, Galanthus gracilis Čelak., Galanthus ikariae Baker, Galanthus koenenianus Lobin, C.D.Brickell & A.P.Davis, Galanthus krasnovii Khokhr., Galanthus lagodechianus Kem.-Nath., Galanthus nivalis L., Galanthus peshmenii A.P.Davis & C.D.Brickell, Galanthus platyphyllus Traub & Moldenke, Galanthus plicatus M.Bieb., Galanthus reginae-olgae Orph., Galanthus rizehensis Stern, Galanthus transcaucasicus Fomin, Galanthus trojanus A.P.Davis & Özhatay, Galanthus woronowii Losinsk., Galanthus samothracicus Kit Tan & Biel, Galanthus bursanus Zubov, Konca & A.P.Davis, Galanthus lebedevae Timukhin & Tuniyev, Galanthus panjutinii Zubov & A.P.Davis, Galanthus ×valentinei Beck, Galanthus ×allenii Baker)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 146256 records from 609 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000030-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9cab9e
title: Occurrence Download

description: A dataset containing 2963 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Carex grayi J.Carey, Carex punicea K.A.Ford, Carex geniculata Schleich. ex Kunth, 1837, Carex rariflora (Wahlenb.) Sm., Carex pluriflora Hultén)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 2963 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0358349-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c2h2xq
title: Occurrence Download

description: A dataset containing 2167064 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Occurrence evidence",
 "BasisOfRecord is Human Observation"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "or" : [
 "TaxonKey is Alosa pseudoharengus (Wilson, 1811)",
 "TaxonKey is Alosa sapidissima (Wilson, 1811)",
 "TaxonKey is Ameiurus melas (Rafinesque, 1820)",
 "TaxonKey is Ameiurus nebulosus (Lesueur, 1819)",
 "TaxonKey is Amia calva Linnaeus, 1766",
 "TaxonKey is Atractosteus spatula (Lacepède, 1803)",
 "TaxonKey is Esox lucius Linnaeus, 1758",
 "TaxonKey is Esox niger Lesueur, 1818",
 "TaxonKey is Gambusia affinis (Baird & Girard, 1853)",
 "TaxonKey is Ictiobus bubalus (Rafinesque, 1818)",
 "TaxonKey is Ictiobus cyprinellus (Valenciennes, 1844)",
 "TaxonKey is Lepomis cyanellus Rafinesque, 1819",
 "TaxonKey is Lepomis megalotis (Rafinesque, 1820)",
 "TaxonKey is Maccullochella peelii (Mitchell, 1838)",
 "TaxonKey is Micropterus dolomieu Lacepède, 1802",
 "TaxonKey is Micropterus punctulatus (Rafinesque, 1819)",
 "TaxonKey is Morone americana (Gmelin, 1789)",
 "TaxonKey is Morone chrysops (Rafinesque, 1820)",
 "TaxonKey is Perca fluviatilis Linnaeus, 1758",
 "TaxonKey is Petromyzon marinus Linnaeus, 1758",
 "TaxonKey is Pylodictis olivaris (Rafinesque, 1818)",
 "TaxonKey is Salmo salar Linnaeus, 1758",
 "TaxonKey is Sander lucioperca (Linnaeus, 1758)",
 "TaxonKey is Scardinius erythrophthalmus (Linnaeus, 1758)",
 "TaxonKey is Silurus glanis Linnaeus, 1758"
 ]
 },
 "Year 1980-2016"
 ]
}

 The dataset includes 2167064 records from 468 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0266390-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.