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

description: A dataset containing 84 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Epeoloides pilosulus (Cresson, 1879)"
 ]
}

 The dataset includes 84 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009715-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2nring
title: Occurrence Download

description: A dataset containing 1482 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Diasporus diastema (Cope, 1875)"
 ]
}

 The dataset includes 1482 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006949-160311141623029/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9h5xx3
title: Occurrence Download

description: A dataset containing 784 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Mimosa bimucronata (DC.) Kuntze"
 ]
}

 The dataset includes 784 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007343-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/178710b2b19eaf6a0e9fac233404725d
title: Mummichog (Fundulus heteroclitus) counts and gut content analysis from lift trap transect collections along Rowley River tidal creeks associated with long term fertilization experiments, Rowley, MA.

description: The lift traps were used to capture mummichogs accessing the high marsh platform. Mummichogs were collected to study the effect of marsh-edge geomorphology on mummichog distribution and foraging. The TIDE project aims to simulate eutrophication on a large scale by the addition of NO3- aiming to reach 70μM concentrations from May to September every year during the growing season. This fertilization of the marsh has been going on at Sweeney Creek since the 2004 growing season through 2016 and at Clubhead Creek in 2005 and from 2009 till 2016. Years 2017-2020 are enrichment recovery years.
DOI: 10.18434/m32208
title: Evaluation of 3D Interest Point Detection Techniques via Human-generated Ground Truth

description: This benchmark aims to provide tools to evaluate 3D Interest Point Detection Algorithms with respect to human generated ground truth. Please refer to the paper for more information about this benchmark: Helin Dutagaci, Chun Pan Cheung, Afzal Godil: Evaluation of 3D interest point detection techniques via human-generated ground truth", The Visual Computer, 2012. Using a web-based subjective experiment, human subjects marked 3D interest points on a set of 3D models. The models were organized in two datasets: Dataset A and Dataset B. Dataset A consists of 24 models which were hand-marked by 23 human subjects. Dataset B is larger with 43 models, and it contains all the models in Dataset B. The number of human subjects who marked all the models in this larger set is 16. We have compared five 3D Interest Point Detection algorithms. The interest points detected on the 3D models of the dataset can be downloaded from the link next to the corresponding algorithm. Please refer to README for details. Mesh saliency [Lee et al. 2005] : Interest points by mesh saliency Salient points [Castellani et al. 2008] : Interest points by salient points 3D-Harris [Sipiran and Bustos, 2010] : Interest points by 3D-Harris 3D-SIFT [Godil and Wagan, 2011] : Interest points by 3D-SIFT (Please note that some models in the dataset are not watertight, hence their volumetric representations could not be generated. Therefore, 3D-SIFT algorithm wasn't able to detect interest points for those models.) Scale-dependent corners [Novatnack and Nishino, 2007] : Interest points by SD corners HKS-based interest points [Sun et al. 2009]: Interest points by HKS method Please Cite the Paper: Dutagaci, Helin, Chun Pan Cheung, and Afzal Godil. "Evaluation of 3D interest point detection techniques via human-generated ground truth." The Visual Computer 28.9 (2012): 901-917.
DOI: 10.6084/m9.figshare.3761562.v2150
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5066/p9w1cktf
title: Forest Structure Data for Burned and Unburned Sites at Sequoia and Kings Canyon National Parks

description: These data represent tree diameter, species, mortality status, and plot attributes from 164 plots in Sequoia and Kings Canyon national parks, California. Plots were matched with local records of recent fire history to determine burn status and year burned if applicable. These data support the following publication: van Mantgem, P.J., Caprio, A.C., Stephenson, N.L. and Das, A.J., 2021. Forest Resistance to Extended Drought Enhanced by Prescribed Fire in Low Elevation Forests of the Sierra Nevada. Forests, 12(9), p.1248. https://doi.org/10.3390/f12091248
DOI: 10.5066/p9pqa90o
title: Estrogen equivalents of surface water in Pennsylvania, 2012-2017

description: The data were gathered as part of a long-term, seasonal assessment of estrogenicity in selected locations within Pennsylvania from 2012-2017. Data were collected over this time frame to determine seasonal and annual changes in surface water estrogenicity.Estrogen is reported as estrogen equivalents (EEQ) as determined by a bioluminescent yeast estrogen screen. A total of 193 grab water samples were collected during this time of which 41 percent had EEQ above the limit of detection. The maximum estrogen equivalents (EEQ) measured was 5.44 ng EEQ/ L, while the median concentration was 0.44 ng/L. POCIS samplers were deployed at a number of sites to determine time-weighted estrogenicity between 2014 and 2017. A total of 150 POCIS samples were deployed over this time of which 77 percent had EEQ above the limit of detection.. The maximum estrogen equivalents (EEQ) measured was 12 ng EEQ/ POCIS.
DOI: 10.5281/zenodo.6336018
title: Materiales complementarios para la metodología sobre Entornos Personales de Aprendizaje (PLEs) en ingeniería

description: Materiales complementarios para el articulo sobre entornos personales de aprendizaje en ingeniería (PLEs). Los materiales están compuestos de los siguientes documentos: Encuestas aplicadas a los estudiantes (años 2020 y 2021). Guiones de entrevistas semiestructurada aplicadas en los años 2020 y 2021. Rúbrica de evaluación diseñada y aplicada para la evaluación de los blogs y videos en los cursos.
DOI: 10.5281/zenodo.6336017
title: Materiales complementarios para la metodología sobre Entornos Personales de Aprendizaje (PLEs) en ingeniería

description: Materiales complementarios para el articulo sobre entornos personales de aprendizaje en ingeniería (PLEs). Los materiales están compuestos de los siguientes documentos: Encuestas aplicadas a los estudiantes (años 2020 y 2021). Guiones de entrevistas semiestructurada aplicadas en los años 2020 y 2021. Rúbrica de evaluación diseñada y aplicada para la evaluación de los blogs y videos en los cursos.
DOI: 10.21223/cyiuhh/zhzrow
title: 02-Data-dictionario-EncuestasVicuñas_17-02-22.xlsx

description: :unav
DOI: 10.21223/cyiuhh/zdmovm
title: 01-Data-EncuestasVicuñas_16-02-22.xlsx

description: :unav
DOI: 10.25921/h0d9-rs72
title: EK80 Water Column Sonar Data Collected During DAFT1-C11-201701 Deployment
DOI: 10.25949/17067443
title: 16S rDNA amplicon sequence data - Maules Creek

description: 16S rDNA amplicon sequence data for samples from groundwater, hyporheic zone and surface waters at Maules Creek, 2015-2016.<br>Data sequenced at Ramaciotti Centre NSW using Illumina MiSeq 250 bp reads, demultiplexed<br>See Korbel et al (in review) for full details of sample collection and processing
DOI: 10.25949/17067443.v1
title: 16S rDNA amplicon sequence data - Maules Creek

description: 16S rDNA amplicon sequence data for samples from groundwater, hyporheic zone and surface waters at Maules Creek, 2015-2016.<br>Data sequenced at Ramaciotti Centre NSW using Illumina MiSeq 250 bp reads, demultiplexed<br>See Korbel et al (in review) for full details of sample collection and processing
DOI: 10.25949/17067455
title: 18S rDNA amplicon sequence data - Maules Creek

description: 18S rDNA amplicon sequence data for samples from groundwater, hyporheic zone and surface waters at Maules Creek, NSW, Australia, 2015-2016.<br><br>Data sequenced at Ramaciotti Centre NSW using Illumina MiSeq 250 bp reads, demultiplexed<br>See Korbel et al (in review) for full details of sample collection and processing
DOI: 10.25949/17067455.v1
title: 18S rDNA amplicon sequence data - Maules Creek

description: 18S rDNA amplicon sequence data for samples from groundwater, hyporheic zone and surface waters at Maules Creek, NSW, Australia, 2015-2016.<br><br>Data sequenced at Ramaciotti Centre NSW using Illumina MiSeq 250 bp reads, demultiplexed<br>See Korbel et al (in review) for full details of sample collection and processing
DOI: 10.5281/zenodo.6336030
title: BIM Guides Survey

description: We present the result of a survey of BIM Guides available online, in Brazil or internationally, based on a reference list presented in Sacks, Gurevich, and Shrestha (2016) (https://www.itcon.org/paper/2016/29) and expanded with Internet searches to identify more guides on Building Information Modeling. The synthesis or title of the guides allows the teacher, or anyone interested in general, to identify material to support the process of implementing BIM in a project. The guides are characterized by the following fields: TITLE: title of the document or site; COUNTRY: country of origin of the guide; REFERENCE: bibliographic reference of the guide in ABNT format; LINK: URL to the online location of the guide; SUMMARY: summary of the content.
DOI: 10.5281/zenodo.6336029
title: BIM Guides Survey

description: We present the result of a survey of BIM Guides available online, in Brazil or internationally, based on a reference list presented in Sacks, Gurevich, and Shrestha (2016) (https://www.itcon.org/paper/2016/29) and expanded with Internet searches to identify more guides on Building Information Modeling. The synthesis or title of the guides allows the teacher, or anyone interested in general, to identify material to support the process of implementing BIM in a project. The guides are characterized by the following fields: TITLE: title of the document or site; COUNTRY: country of origin of the guide; REFERENCE: bibliographic reference of the guide in ABNT format; LINK: URL to the online location of the guide; SUMMARY: summary of the content.
DOI: 10.5281/zenodo.6336023
title: Pseudoxenodon macrops decontaminated FSCR

description: .
DOI: 10.5281/zenodo.6336022
title: Pseudoxenodon macrops decontaminated FSCR

description: .
DOI: 10.5281/zenodo.6335642
title: Dust extinction curves: Draine R_V=5.5 model

description: This dataset is based on the models described in Benson (2018). <strong>Dust Properties</strong> Dust grain properties are taken from Draine (2003) - specifically their model with R<sub>V</sub>=5.5. <strong>Stellar Geometry</strong> Galactic disks follow exponential profiles in the radial direction, and sech<sup>2</sup> distributions in the vertical direction. The vertical scale height is set to a multiple, <em>h</em><sub>d</sub>, of the stellar disk scale length, and its value is encoded in each file name. Spheroids follow spherical Hernquist (1990) profiles. <strong>Dust Geometry</strong> Dust is distributed in the disk, and follows exponential profiles in both radial and vertical directions. The vertical scale height is set to a multiple, <em>h</em><sub>z</sub>, of the stellar disk scale length, and its value is encoded in each file name.
DOI: 10.5281/zenodo.6335641
title: Dust extinction curves: Draine R_V=5.5 model

description: This dataset is based on the models described in Benson (2018). <strong>Dust Properties</strong> Dust grain properties are taken from Draine (2003) - specifically their model with R<sub>V</sub>=5.5. <strong>Stellar Geometry</strong> Galactic disks follow exponential profiles in the radial direction, and sech<sup>2</sup> distributions in the vertical direction. The vertical scale height is set to a multiple, <em>h</em><sub>d</sub>, of the stellar disk scale length, and its value is encoded in each file name. Spheroids follow spherical Hernquist (1990) profiles. <strong>Dust Geometry</strong> Dust is distributed in the disk, and follows exponential profiles in both radial and vertical directions. The vertical scale height is set to a multiple, <em>h</em><sub>z</sub>, of the stellar disk scale length, and its value is encoded in each file name.
DOI: 10.13020/rbjq-nn61
title: Simulation data for "Adsorption of Charge Sequence-Specific Polydisperse Polyelectrolytes"
DOI: 10.5281/zenodo.6336049
title: Pleiades member candidates via STARGO with Gaia EDR3

description: Members of the Pleiades open cluster are selected by using the STARGO method (Yuan et al. 2018) with Gaia early data release 3 (EDR3; Gaia Collaboration et al. 2021) data. See Li et al. 2021 (in prep. for Research Note of the AAS) for a detailed description. We downloaded the Gaia EDR3 data 100 pc from the center of Pleiades (X, Y, Z) = (−121.38, +29.17, −54.47) pc in Heliocentric Cartesian coordinates (Galli et al. 2017; Olivares et al. 2018). After removing artifacts and poor quality photometric sources (Lindegren et al 2018), we select stars within a radius of 10.8 mas yr^−1 from the center of the mean proper motion (μα cos δ, μδ ) = (+19.997, −45.548) mas yr<sup>-1</sup> of Pleiades (Gaia Collaboration et al. 2018) and input the 5D parameters (X, Y, Z, μα cosδ, μδ) into STARGO. We allow a 5% field star contamination rate in our identified members. We correct the distance of individual stars in Pleiades for the pseudo-elongation generated by parallax errors, via a Bayesian approach described in Carrera et al. (2019) and Pang et al. (2020, 2021). The mass of individual members in Pleiades is computed via the k-D tree method by taking the mass of the nearest point in the isochrone of 125 Myr (Lodieu et al. 2019) with AV = 0.11 mag and [Fe/H] = 0.08 (Gossage et al. 2018). "x_c", "y_c", "z_c" are the cluster position with distance correction in Heliocentric Cartesian coordinates. "Mass" represents the mass estimate of each star member via k-D tree method (Millman & Aivazis 2011). The descriptions of other parameters are found by opening the fits. file in TOPCAT.
DOI: 10.5281/zenodo.5067750
title: Pleiades member candidates via STARGO with Gaia EDR3

description: Members of the Pleiades open cluster are selected by using the STARGO method (Yuan et al. 2018) with Gaia early data release 3 (EDR3; Gaia Collaboration et al. 2021) data. See Li et al. 2021 (in prep. for Research Note of the AAS) for a detailed description. We downloaded the Gaia EDR3 data 100 pc from the center of Pleiades (X, Y, Z) = (−121.38, +29.17, −54.47) pc in Heliocentric Cartesian coordinates (Galli et al. 2017; Olivares et al. 2018). After removing artifacts and poor quality photometric sources (Lindegren et al 2018), we select stars within a radius of 10.8 mas yr^−1 from the center of the mean proper motion (μα cos δ, μδ ) = (+19.997, −45.548) mas yr<sup>-1</sup> of Pleiades (Gaia Collaboration et al. 2018) and input the 5D parameters (X, Y, Z, μα cosδ, μδ) into STARGO. We allow a 5% field star contamination rate in our identified members. We correct the distance of individual stars in Pleiades for the pseudo-elongation generated by parallax errors, via a Bayesian approach described in Carrera et al. (2019) and Pang et al. (2020, 2021). The mass of individual members in Pleiades is computed via the k-D tree method by taking the mass of the nearest point in the isochrone of 125 Myr (Lodieu et al. 2019) with AV = 0.11 mag and [Fe/H] = 0.08 (Gossage et al. 2018). "x_c", "y_c", "z_c" are the cluster position with distance correction in Heliocentric Cartesian coordinates. "Mass" represents the mass estimate of each star member via k-D tree method (Millman & Aivazis 2011). The descriptions of other parameters are found by opening the fits. file in TOPCAT.
DOI: 10.5281/zenodo.6336041
title: Quercus bicolor decontaminated FSCR

description: .
DOI: 10.5281/zenodo.6336040
title: Quercus bicolor decontaminated FSCR

description: .
DOI: 10.6084/m9.figshare.19319897
title: Dataset 6 Biolog Time Series Data

description: Dataset 6: All Biolog Data
DOI: 10.6084/m9.figshare.19319897.v1
title: Dataset 6 Biolog Time Series Data

description: Dataset 6: All Biolog Data
DOI: 10.6084/m9.figshare.19319783.v1
title: NOMAD Chemical Formulas and Calculation IDs

description: Two columns: `calc_id` (Calculation ID) and `formula` (Chemical Formula). Some calculation IDs may have missing chemical formulas. The list has not been filtered down to unique chemical formulas. No structural information is included directly in this data.<br>The data was downloaded on 2022-03-07 using https://github.com/sparks-baird/nomad-examples/blob/0.1.0/all_formula_basic_metadata.py
DOI: 10.5281/zenodo.5866593
title: Quantifying the spatial homogeneity of urban road networks via graph neural networks

description: Publication: Quantifying the spatial homogeneity of urban road networks via graph neural networks, Nature Machine Intelligence, 2022. Publication DOI: 10.1038/s42256-022-00462-y Please refer to https://github.com/jiang719/road-network-predictability.
DOI: 10.5281/zenodo.5866592
title: Quantifying the spatial homogeneity of urban road networks via graph neural networks

description: Publication: Quantifying the spatial homogeneity of urban road networks via graph neural networks, Nature Machine Intelligence, 2022. Publication DOI: 10.1038/s42256-022-00462-y Please refer to https://github.com/jiang719/road-network-predictability.
DOI: 10.6084/m9.figshare.19319903
title: Dataset 7_Isolate Genomes.zip

description: 35 Strain Genome Sequences
DOI: 10.6084/m9.figshare.19319900
title: Dataset8_CuratedStrainSpecificModels.zip

description: 35 Strain-Specific Models
DOI: 10.6084/m9.figshare.19319906
title: Dataset9_415_DraftModels.zip

description: 415 Draft Strain-Specific Models
DOI: 10.6084/m9.figshare.19319906.v1
title: Dataset9_415_DraftModels.zip

description: 415 Draft Strain-Specific Models
DOI: 10.6084/m9.figshare.19319909
title: Dataset 10_Validation_Experiment.zip

description: Validation Experiment Data
DOI: 10.34820/fk2/0ykdry/7q39sg
title: datasetWS2017.tab

description: :unav
DOI: 10.34820/fk2/0ykdry/fcjwkl
title: rmse.m

description: :unav
DOI: 10.34820/fk2/0ykdry/bxacfm
title: svm_berhasil.m

description: :unav
DOI: 10.34820/fk2/0ykdry/uqkhre
title: rsquare.m

description: :unav
DOI: 10.34820/fk2/0ykdry/sexik9
title: mape.m

description: :unav
DOI: 10.34820/fk2/0ykdry
title: ws prediction

description: ws prediction
DOI: 10.5281/zenodo.6336053
title: Scolopax bukidnonensis decontaminated FSCR

description: .
DOI: 10.5281/zenodo.6336052
title: Scolopax bukidnonensis decontaminated FSCR

description: .
DOI: 10.5281/zenodo.6336069
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Stylianos Chatzimanolis, https://orcid.org/0000-0001-9008-0611. Claims were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5281/zenodo.6336078
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Sarah Tassell, https://orcid.org/0000-0002-8083-3111. Claims were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5281/zenodo.3557001
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Sarah Tassell, https://orcid.org/0000-0002-8083-3111. Claims were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.34943/8caab894-0dcf-45cd-8c8b-9278a783b225
title: Port Hardy Accelerometer Deployed 2019-06-26

description: The Nanometrics Titan SMA (S/N 000617) was deployed on 2019-06-26 at Port Hardy. Port Hardy is a small community on northern Vancouver Island. This device is a Accelerometer. Accelerometers are instruments that measure accelerations. Acceleration can be static such as gravity pulling objects toward the earth, or dynamic as caused by oscillatory movements of the instrument. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/ed26ee6a-e67a-4c27-9358-fe2cb1588ab3
title: Port Hardy Accelerometer Deployed 2019-06-26

description: The Nanometrics Titan SMA (S/N 000617) was deployed on 2019-06-26 at Port Hardy. Port Hardy is a small community on northern Vancouver Island. This device is a Accelerometer. Accelerometers are instruments that measure accelerations. Acceleration can be static such as gravity pulling objects toward the earth, or dynamic as caused by oscillatory movements of the instrument. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.5281/zenodo.6253779
title: Sensitivity of a Coarse-Resolution Global Ocean Model to a Spatially Variable Neutral Diffusivity - ACCESS-OM2 data and plotting routines

description: This repository contains the processed data and plotting routines associated with the article Holmes, Groeskamp, Stewart and McDougall (2022), Sensitivity of a Coarse-Resolution Global Ocean Model to a Spatially Variable Neutral Diffusivity, Journal of Advances in Modeling Earth Systems (JAMES), doi: 10.1029/2021MS002914, http://dx.doi.org/10.1029/2021MS002914 The contents includes post-processed data output from the 1-degree ACCESS-OM2 ocean-sea-ice model simulations and the python/jupyter plotting routines required to make the plots. The processing script is Holmes2022JAMES_Neutral_Diffusion_ACCESS-OM2_Plotting_Script.ipynb. The data files consist of time-averages or time series of certain metrics processed using NCO tools from the raw ACCESS-OM2 simulation output.
DOI: 10.5281/zenodo.6253778
title: Sensitivity of a Coarse-Resolution Global Ocean Model to a Spatially Variable Neutral Diffusivity - ACCESS-OM2 data and plotting routines

description: This repository contains the processed data and plotting routines associated with the article Holmes, Groeskamp, Stewart and McDougall (2022), Sensitivity of a Coarse-Resolution Global Ocean Model to a Spatially Variable Neutral Diffusivity, Journal of Advances in Modeling Earth Systems (JAMES), doi: 10.1029/2021MS002914, http://dx.doi.org/10.1029/2021MS002914 The contents includes post-processed data output from the 1-degree ACCESS-OM2 ocean-sea-ice model simulations and the python/jupyter plotting routines required to make the plots. The processing script is Holmes2022JAMES_Neutral_Diffusion_ACCESS-OM2_Plotting_Script.ipynb. The data files consist of time-averages or time series of certain metrics processed using NCO tools from the raw ACCESS-OM2 simulation output.