cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17369137
title: Dataset de Imagens para Segmentação de 20 Espécies de Ervas Daninhas em Pastagens Amazônicas

description: Este conjunto de dados (dataset) contém 475 imagens anotadas de 20 espécies de plantas daninhas (ervas invasoras) com relevância econômica e agronômica para pastagens na região do Sul e Sudeste do Pará, Brasil. O material foi desenvolvido para suportar o treinamento de modelos de Visão Computacional e Inteligência Artificial, especificamente arquiteturas YOLO (You Only Look Once), visando aplicações em agricultura de precisão e manejo sustentável na Amazônia.

Origem e Metodologia Os dados foram compilados no âmbito da pesquisa "Identificação Automatizada de Espécies Invasoras em Pastagens do Sudeste do Pará com YOLOv8: Uma Abordagem Alinhada à COP30", desenvolvida na Faculdade de Sistemas de Informação da Universidade Federal do Sul e Sudeste do Pará (Unifesspa).





Coleta: As imagens provêm de duas fontes principais: coletas em campo realizadas em propriedades rurais e estabelecimentos comerciais na região (capturando variações de solo, luz e estágios de crescimento) e complementação via base de dados GBIF (Global Biodiversity Information Facility).




Anotação: Todas as imagens foram processadas e anotadas manualmente utilizando a ferramenta CVAT (Computer Vision Annotation Tool). As anotações incluem máscaras de segmentação precisas para cada espécime.




Formato: Os arquivos de anotação foram convertidos e exportados para o formato compatível com a arquitetura YOLOv8 (.txt).



Composição do Dataset





Total de Imagens: 475 imagens.




Divisão Sugerida: O estudo original utilizou uma divisão de 75% para treinamento e 25% para validação.




Classes (Espécies): O dataset abrange 20 espécies: Alternanthera tenella Colla, Amaranthus spinosus L, Andropogon bicornis, Cenchrus echinatus L, Commelina benghalensis L, Cyperus rotundus L, Dactyloctenium aegyptium (L.) Willd, Dichorisandra sp, Digitaria sanguinalis (L.) Scop, Echinochloa colona (L.) Link, Eleusine indica (L.) Gaertn, Lindernia crustacea (L.) F.Muell, Mesosphaerum suaveolens (L.) Kuntze, Mollugo verticillata L, Mucuna pruriens, Phyllanthus niruri L, Psychotria carthagenensis, Sida cordifolia L, Solanum sisymbriifolium Lam e Strychnos pseudoquina.



Aplicações Potenciais





Treinamento e validação de redes neurais para detecção e segmentação de objetos (YOLO, R-CNN, etc.).




Desenvolvimento de aplicativos móveis para identificação de plantas daninhas.




Estudos sobre automação no manejo de pastagens e agricultura de baixo carbono.
DOI: 10.5281/zenodo.17369138
title: Dataset de Imagens para Segmentação de 20 Espécies de Ervas Daninhas em Pastagens Amazônicas

description: Este conjunto de dados (dataset) contém 475 imagens anotadas de 20 espécies de plantas daninhas (ervas invasoras) com relevância econômica e agronômica para pastagens na região do Sul e Sudeste do Pará, Brasil. O material foi desenvolvido para suportar o treinamento de modelos de Visão Computacional e Inteligência Artificial, especificamente arquiteturas YOLO (You Only Look Once), visando aplicações em agricultura de precisão e manejo sustentável na Amazônia.

Origem e Metodologia Os dados foram compilados no âmbito da pesquisa "Identificação Automatizada de Espécies Invasoras em Pastagens do Sudeste do Pará com YOLOv8: Uma Abordagem Alinhada à COP30", desenvolvida na Faculdade de Sistemas de Informação da Universidade Federal do Sul e Sudeste do Pará (Unifesspa).





Coleta: As imagens provêm de duas fontes principais: coletas em campo realizadas em propriedades rurais e estabelecimentos comerciais na região (capturando variações de solo, luz e estágios de crescimento) e complementação via base de dados GBIF (Global Biodiversity Information Facility).




Anotação: Todas as imagens foram processadas e anotadas manualmente utilizando a ferramenta CVAT (Computer Vision Annotation Tool). As anotações incluem máscaras de segmentação precisas para cada espécime.




Formato: Os arquivos de anotação foram convertidos e exportados para o formato compatível com a arquitetura YOLOv8 (.txt).



Composição do Dataset





Total de Imagens: 475 imagens.




Divisão Sugerida: O estudo original utilizou uma divisão de 75% para treinamento e 25% para validação.




Classes (Espécies): O dataset abrange 20 espécies: Alternanthera tenella Colla, Amaranthus spinosus L, Andropogon bicornis, Cenchrus echinatus L, Commelina benghalensis L, Cyperus rotundus L, Dactyloctenium aegyptium (L.) Willd, Dichorisandra sp, Digitaria sanguinalis (L.) Scop, Echinochloa colona (L.) Link, Eleusine indica (L.) Gaertn, Lindernia crustacea (L.) F.Muell, Mesosphaerum suaveolens (L.) Kuntze, Mollugo verticillata L, Mucuna pruriens, Phyllanthus niruri L, Psychotria carthagenensis, Sida cordifolia L, Solanum sisymbriifolium Lam e Strychnos pseudoquina.



Aplicações Potenciais





Treinamento e validação de redes neurais para detecção e segmentação de objetos (YOLO, R-CNN, etc.).




Desenvolvimento de aplicativos móveis para identificação de plantas daninhas.




Estudos sobre automação no manejo de pastagens e agricultura de baixo carbono.
DOI: 10.34740/kaggle/dsv/13864521
title: Multi Source Guava FruitLeaf YOLO CNN Labeled Data
DOI: 10.14470/7f826824
title: Seismic neTwoRk/Array in norThwEstern arGentina (STRATEGy)

description: The STRATEGy network was a temporary seismic network in the NW Argentinean Andean Foreland. It run for about 15 months between June 2016 and August 2017 and consisted of 13 stations for the most parts. Each station contains a Lennartz LE3D/5s seismometer, an Omnirecs DataCube³ext digitizer (100 Hz sampling rate) with external GPS antenna and internal flash memory. Station 14A consisted of a Mark L-4C-3D short-period sensor. The power was supplied through an external batteries that were recharged during the day via a solar panel. The sensors were oriented to magnetic north. The header of the waveform files (NSLC-IDs) still remained in its prior form (network code ST) and haven’t been adapted to the FDSN given code. Station codes (double digits) were assigned from North to South. The last digit of the station code is either A (for their initial position of a station site) or B (the station has been moved during the networks operation time due to low quality recordings at the respective initial site). Each site was chosen on 3 criteria: (1) minimizing the depth to bedrock, (2) maximizing remoteness, and (3) maximizing security, preferentially located within sight of nearby settlements. However, one station (02A) was lost due to theft and many others experienced recording gaps due to animals chewing on cables, malfunctions of electrical parts and mainly flooding of the stations during the austral summer monsoon. The overall network geometry evolved partially due to accessibility of remote locations, maintaining similar interstation distances and focusing around the epicenter of the Mw 5.7 El Galpón earthquake 9 months prior to the network’s starttime. The smallest depths to bedrock were achieved by concentrating the sites around two major bedrock ranges and their piedmont, Cerro Colorado and Sierra de la Candelaria. Waveform data are available from the GEOFON data centre, under network code 2S.
DOI: 10.15468/dl.3ya383
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material sample)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Hyphessobrycon robustulus",
 "Year 1970-2025"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007711-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dvy6xq
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((94.96626 5.92499,94.29736 4.90197,95.6745 3.80026,97.62217 2.12802,99.23538 -0.40985,102.08803 -4.61996,104.27178 -6.80371,105.8063 -6.23318,107.20312 -2.65262,105.23577 -0.7443,103.99635 0.49512,102.36346 1.28206,100.2584 3.13136,97.18935 5.96433,94.96626 5.92499))",
 "TaxonKey is Epicharis"
 ]
}

 The dataset includes 110 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007712-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14470/7t7561754109
title: Lastarria volcano experiment

description: The network consistes in 6 stations surronding the fumarole field at Lastarria volcano. These stations were operative during one month with the final purpose of detect changes in the hydrothermal system triggered by passing of seismic waves produced by artificial explosions. Waveform data are available from the GEOFON data centre, under network code 2G.
DOI: 10.6084/m9.figshare.28803887.v1
title: Data for "Species interactions determine the importance of response diversity for community stability to pulse disturbances"

description: Data for "Species interactions determine the importance of response diversity for community stability to pulse disturbances" by Charlotte Kunze, Owen L. Petchey, Shymaolina Ghosh, and Helmut Hillebrand (2025). Meta-Analysis data should be stored in a folder named 'Data'.<b>Methods</b>This data set contains all effect sizes between a control and a disturbed treatment for 98 experiments used to analyse the relationship between response diversity and community stability. A full description of the methods is in the paper associated to this manuscript. The data contains three sheets:meta contains all metadata to the studies species data gives species-specific response to disturbance and control abbreviations gives all column details:<br>case.IDis a unique identifier for each experiments. Appendix S2 at the paper contains full documentation for each of the experiments.study.IDis a unique identifier for each study.refreference - Appendix S2 at the paper contains full documentation for each of the experiments.spec.infinformation on species or taxa levelorganismorganism typesystemmarine, freshwater or terrestrialfieldfield or mesocosmlatLatitude of the experimentlongLongtitude of the experimentdifferentiationdifferentiation between the experiments in one studydurationtime span of the expeirmenttime unitdayssamplsamplings conducted in the experimentunits_replicatesis the number of replicates in the experimentresp.catcategorizes the response variable as either biomass, abundance.Dayday of the experiment, with 0 being the pre-distrubance day.sourceRelative duration within the experiment, i.e., normalizing the day of the experiment to the duration of the experiment, such that 1 is the final sampling date.funcfunctional responsespeciesspecies namespecies_specificationspecification on species, i.e. plant or vascular plantSTARTindicates start pointRESISTindicates resistanceRESILindicates resilience time pontsRECOVindicates recovery timeCon.MMean of species response in controlCon.SDSD of species response in controlCon.SESE of species response in controlCon.Nnumber of replicates in controlDist.MMean of species response in disturbed treatmentDist.SDSD of species response in disturbed treatmentDIST.SESE of species response in disturbed treatmentDist.Nnumber of replicates in disturbed treatmentLRRone effect size of the disturbance, in most cases a log-response ratio. Again, for detauls see the paper's method sectionvar.lrris the sampling variance of the effect sizes, if blank it could not be derived from the primary literature.
DOI: 10.15468/dl.5grekc
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 34.085278",
 "DecimalLatitude is less than or equal to 44.085278",
 "DecimalLongitude is greater than or equal to 160.0",
 "DecimalLongitude is less than or equal to 170.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007714-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14470/6i800592
title: Identification and Assessment of Deep Geothermal Heat Resources in Challenging Urban Environments (GEO_URBAN)

description: The ability to use geothermal resources to generate heat in urban areas where the demand is greatest has the potential to significantly reduce our reliance on fossil fuels, and to support sustainable energy policies. Potential deep geothermal resources in challenging, lower-enthalpy EU settings remain poorly understood and largely untapped. The GEO-URBAN project aims to explore the potential for low enthalpy geothermal in urban environments. The project will focus on two target locations – Dublin, Ireland and Vallès, Spain – and will provide a feasibility analysis for the commercial development of deep geothermal resources in these regions. The overall objective of GEO-URBAN is to identify the geothermal resources available in two challenging urban locations and to demonstrate a commercialisation strategy that has the potential to be adapted in other similar locations. Waveform data is available from the GEOFON data centre, under network code 1V, and is {fully open.
DOI: 10.15468/dl.mjcnbv
title: Occurrence Download

description: A dataset containing 33999 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((14.83062 56.09041, 14.79882 56.26564, 14.70566 56.434, 14.55399 56.58887, 14.34917 56.72412, 14.0989 56.83429, 13.81299 56.91492, 13.50294 56.96272, 13.18142 56.97573, 12.86168 56.9534, 12.55687 56.89668, 12.2794 56.80788, 12.04035 56.69065, 11.84896 56.54973, 11.71234 56.39077, 11.63516 56.22004, 11.61964 56.04422, 11.66552 55.87007, 11.77028 55.70421, 11.92928 55.55286, 12.13605 55.42164, 12.38258 55.31538, 12.65964 55.23794, 12.95707 55.19213, 13.26412 55.17962, 13.56975 55.20086, 13.86296 55.25508, 14.13312 55.34034, 14.37025 55.45355, 14.56538 55.59056, 14.71085 55.74634, 14.80064 55.91508, 14.83062 56.09041))",
 "OccurrenceStatus is Present",
 "DatasetKey is Swedish Bird Survey: Fixed routes (Standardrutterna)"
 ]
}

 The dataset includes 33999 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007715-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14470/6z7563484593
title: MI-DAM - MultI-parameter monitoring and real-time risk assessment of hydroelectric DAMs in the Kyrgyz Republic

description: The MI-DAM project will develop a robust, low-cost, and adaptable system that includes an early warning element and time-variable fragility functions. The system will continuously monitor the health of hydroelectric dams and the surrounding slopes, undertake on-site processing of recordings by multi-parameter sensors, and forward the most relevant information to response centers (e.g., civil protection). As an example, the project will focus on the Toktogul dam in Central Kyrgyzstan. Waveform data are available from the GEOFON data centre, under network code 1M.
DOI: 10.14470/4w7562667842
title: FoMapS: Seismic investigation of the Fogo magmatic plumbing system, Cape Verde, using multi-array techniques

description: Volcanic eruptions are regularly observed on the island of Fogo, Cape Verde, with an average re-occurrence interval of ca. 20 years. However, the structure and extent of the related volcanic plumbing system are not well understood. Previous studies have investigated earthquakes related to magmatic processes connected with the Fogo volcano using conventional network configurations. Seismicity has been reported to occur mainly southwest of the island of Brava while a more recent study reports on activity focussed between Brava and Fogo. Multi-array seismology has the potential to significantly reduce the localization errors of seismic events in particular for those outside a station network and to lower the detection threshold. The subject of this study is the investigation of the local volcano-related seismicity applying multi-array methods which is a unique task amongst the research activities at German universities. The scientific aims are (a) to precisely map local events to constrain the structure of and the dynamic processes within the volcanic plumbing system, (b) to image the magma source region below the Fogo volcano using reflected and backscattered waves, and (c) to localize low-frequency volcanic tremor events. Waveform data are available from the GEOFON data centre, under network code 9J.
DOI: 10.15468/dl.k9xvc4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "Geometry POLYGON ((-115.7893 35.15274, -115.788 35.15427, -115.7905 35.15522, -115.7918 35.15344, -115.7893 35.15274))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007717-251120083545085/datasets/export for details.
DOI: 10.15468/dl.58mb2n
title: Occurrence Download

description: A dataset containing 4308524 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aves",
 "Year is 1987"
 ]
}

 The dataset includes 4308524 records from 605 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007675-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34894/oorswj
title: Automated segmentation of brain metastases in T1-weighted contrast- enhanced MR images pre and post stereotactic radiosurgery

description: This data package contains the information needed to replicate the research titled - 'Automated segmentation of brain metastases in T1-weighted contrast- enhanced MR images pre and post stereotactic radiosurgery'.
description: This research evaluated the well-known Deep Learning approaches (nnU-Net and MedNeXt) for their segmentation performance on both planning and follow-up MR of brain metastases patients treated with stereotactic radiosurgery. This research can be replicated by following the methodology described in the paper.
description: This research is part of the AMICUS project. The anonymized clinical research data from ETZ is used for this research. This data is present in the research servers at ETZ. My supervisor Wouter De Baene also has access to this research data in research servers at ETZ. Due to privacy reasons, data cannot be moved out of ETZ hospital. The data can be accessed after approval from ETZ Wetenschapsbureau.
DOI: 10.57745/dvqnda
title: MSA_phenotyped_Athaliana.fasta

description: FASTA file containing a multiple sequence alignment (MSA) of nucleic acid sequences
DOI: 10.57745/lpmxi3
title: Multiple Sequence Alignment of Nucleic Acids for the RPS4-RRS1 Locus in several accessions of Arabidopsis thaliana

description: This dataset consists of a FASTA file containing a multiple sequence alignment (MSA) of nucleic acid sequences for the RPS4-RRS1 locus of several accessions of Arabidopsis thaliana. The alignment includes 114 accessions of Arabidopsis thaliana.
DOI: 10.5281/zenodo.17559991
title: Dog brain atlas generated via spatially constrained spectral clustering

description: This repository provides a multi-scale functional parcellation atlas of the domestic dog brain derived from resting-state fMRI using a spatially constrained spectral clustering algorithm. Parcellations were generated from an awake rs-fMRI dataset of 27 pet dogs and registered to the stereotaxic, breed-averaged, symmetric T2-weighted canine template space described by Nitzsche et al. (2019), then resampled to 2 mm isotropic resolution.

The dataset consists of whole-brain segmentations stored as 3D NIfTI label maps at multiple resolutions ranging from 20 to 300 parcels in steps of 20 (N = 20, 40, …, 300). All segmentations are defined in Nitzsche et al. (2019) template space at 2 mm isotropic voxel size and share its orientation and dimensions; voxel values encode integer parcel IDs, with 0 denoting background/non-brain voxels.

The construction of the atlas, as well as its evaluation in terms of cross-dataset and within-participant reproducibility (Dice coefficient, Adjusted Rand Index), within-parcel functional homogeneity, and concordance with the Johnson et al. (2020) anatomical atlas, is detailed in Hernandez-Perez et al., Dog brain atlas generated via spatially constrained spectral clustering (preprint/manuscript linked in this record).

These parcellations are intended for use in canine fMRI connectivity and task-based studies, ROI definition, and comparative canine–human neuroimaging. When using this resource, please cite the accompanying article and this Zenodo dataset (DOI) and acknowledge that the segmentations are defined in Nitzsche et al. (2019) template space at 2 mm isotropic resolution.
DOI: 10.5281/zenodo.17559992
title: Dog brain atlas generated via spatially constrained spectral clustering

description: This repository provides a multi-scale functional parcellation atlas of the domestic dog brain derived from resting-state fMRI using a spatially constrained spectral clustering algorithm. Parcellations were generated from an awake rs-fMRI dataset of 27 pet dogs and registered to the stereotaxic, breed-averaged, symmetric T2-weighted canine template space described by Nitzsche et al. (2019), then resampled to 2 mm isotropic resolution.

The dataset consists of whole-brain segmentations stored as 3D NIfTI label maps at multiple resolutions ranging from 20 to 300 parcels in steps of 20 (N = 20, 40, …, 300). All segmentations are defined in Nitzsche et al. (2019) template space at 2 mm isotropic voxel size and share its orientation and dimensions; voxel values encode integer parcel IDs, with 0 denoting background/non-brain voxels.

The construction of the atlas, as well as its evaluation in terms of cross-dataset and within-participant reproducibility (Dice coefficient, Adjusted Rand Index), within-parcel functional homogeneity, and concordance with the Johnson et al. (2020) anatomical atlas, is detailed in Hernandez-Perez et al., Dog brain atlas generated via spatially constrained spectral clustering (preprint/manuscript linked in this record).

These parcellations are intended for use in canine fMRI connectivity and task-based studies, ROI definition, and comparative canine–human neuroimaging. When using this resource, please cite the accompanying article and this Zenodo dataset (DOI) and acknowledge that the segmentations are defined in Nitzsche et al. (2019) template space at 2 mm isotropic resolution.
DOI: 10.15468/dl.86jfxn
title: Occurrence Download

description: A dataset containing 2713 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Apium chilense, Apium fernandezianum, Apium panul, Apium prostratum)",
 "BasisOfRecord is Specimen",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2713 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007719-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.