cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25405/data.ncl.13214219.v1
title: SIfig16_REV_sourceData_FtsAmNG_D213A_PHMM_37C.xlsx

description: Raw data for Supp. Fig. 16<br>
DOI: 10.25405/data.ncl.13214219
title: SIfig16_REV_sourceData_FtsAmNG_D213A_PHMM_37C.xlsx

description: Raw data for Supp. Fig. 16<br>
DOI: 10.25405/data.ncl.13214423
title: fig4ab_SIfig21b_REV_sourceData_mNG_PBP2B_PC19_CDM_30C.mat

description: Raw data for Fig. 4a-b and Supp. Fig. 21b, CDM 30C<br>
DOI: 10.25405/data.ncl.13214423.v1
title: fig4ab_SIfig21b_REV_sourceData_mNG_PBP2B_PC19_CDM_30C.mat

description: Raw data for Fig. 4a-b and Supp. Fig. 21b, CDM 30C<br>
DOI: 10.6084/m9.figshare.12309992
title: Three-dimensional versus two-dimensional transthoracic echocardiography for left ventricular outflow tract measurements in severe aortic stenosis. A cross-sectional study using computer tomography and Haegar sizers as reference

description: <i>Objectives.</i> In grading of aortic stenosis, two-dimensional transthoracic echocardiography (2D TTE) routinely results in underestimation of the left ventricular outflow tract (LVOT) area, and hence the aortic valve area (AVA). We investigated whether three-dimensional (3D) TTE measurements of the LVOT would be more accurate. We evaluated the feasibility, agreement and inter-observer variability of 3D TTE LVOT measurements with computed tomography (CT) and Haegar sizers as reference. <i>Design.</i> Sixty-one patients with severe aortic stenosis were examined with 2D and 3D TTE. 41 had CT and 13 also had perioperative Haegar sizing. Pearson’s correlation and Bland-Altman plots were used to compare methods. Inter-observer variability was tested for 2D and 3D TTE. Trial registration: Current research information system in Norway (CRISTIN). Id: 555249. <i>Results.</i> Feasibility was 67% with 3D TTE and 100% with 2D TTE and CT. Mean LVOT area for 2D, 3D, CT and Haegar sizers were 3.7 ± 0.6 cm2, 4.0 ± 0.9 cm2, 5.2 ± 0.8 cm2 and 4.4 ± 1.0 cm2 respectively. Bias and limits of agreements for 2D TTE was 1.5 ± 1.3 cm2, compared with CT and 0.4 ± 1.5 cm2 with Haegar sizers. Corresponding results for 3D TTE were 1.2 ± 1.6 cm2 and 0.2 ± 1.8 cm2. Intraclass correlation coefficients for LVOT area were 0.62 for 3D and 0.86 for 2D. <i>Conclusions.</i> 2D TTE showed better feasibility and inter-observer variability in measurements of LVOT than 3D TTE. Both echocardiographic methods underestimated LVOT area compared to CT and Haegar sizers. These observations suggest that 2D TTE is still preferable to 3D TTE in the assessment of aortic stenosis.
DOI: 10.6084/m9.figshare.12309992.v1
title: Three-dimensional versus two-dimensional transthoracic echocardiography for left ventricular outflow tract measurements in severe aortic stenosis. A cross-sectional study using computer tomography and Haegar sizers as reference

description: <i>Objectives.</i> In grading of aortic stenosis, two-dimensional transthoracic echocardiography (2D TTE) routinely results in underestimation of the left ventricular outflow tract (LVOT) area, and hence the aortic valve area (AVA). We investigated whether three-dimensional (3D) TTE measurements of the LVOT would be more accurate. We evaluated the feasibility, agreement and inter-observer variability of 3D TTE LVOT measurements with computed tomography (CT) and Haegar sizers as reference. <i>Design.</i> Sixty-one patients with severe aortic stenosis were examined with 2D and 3D TTE. 41 had CT and 13 also had perioperative Haegar sizing. Pearson’s correlation and Bland-Altman plots were used to compare methods. Inter-observer variability was tested for 2D and 3D TTE. Trial registration: Current research information system in Norway (CRISTIN). Id: 555249. <i>Results.</i> Feasibility was 67% with 3D TTE and 100% with 2D TTE and CT. Mean LVOT area for 2D, 3D, CT and Haegar sizers were 3.7 ± 0.6 cm2, 4.0 ± 0.9 cm2, 5.2 ± 0.8 cm2 and 4.4 ± 1.0 cm2 respectively. Bias and limits of agreements for 2D TTE was 1.5 ± 1.3 cm2, compared with CT and 0.4 ± 1.5 cm2 with Haegar sizers. Corresponding results for 3D TTE were 1.2 ± 1.6 cm2 and 0.2 ± 1.8 cm2. Intraclass correlation coefficients for LVOT area were 0.62 for 3D and 0.86 for 2D. <i>Conclusions.</i> 2D TTE showed better feasibility and inter-observer variability in measurements of LVOT than 3D TTE. Both echocardiographic methods underestimated LVOT area compared to CT and Haegar sizers. These observations suggest that 2D TTE is still preferable to 3D TTE in the assessment of aortic stenosis.
DOI: 10.25405/data.ncl.13214285
title: fig4ab_SIfig21a_SIfig27_REV_sourceData_mNG_PBP2B_PC19_PHMM_37C.mat

description: Raw data for Fig. 4a-b, Supp. Fig. 21a, and Supp. Fig. 27, PHMM 37C<br>
DOI: 10.25405/data.ncl.13214285.v1
title: fig4ab_SIfig21a_SIfig27_REV_sourceData_mNG_PBP2B_PC19_PHMM_37C.mat

description: Raw data for Fig. 4a-b, Supp. Fig. 21a, and Supp. Fig. 27, PHMM 37C<br>
DOI: 10.25405/data.ncl.13214351
title: Fig4c_constrictionData_mNG_PBP2B_CDM_30C.mat

description: Raw data for Fig. 4c, CDM 30C<br>
DOI: 10.25405/data.ncl.13214351.v1
title: Fig4c_constrictionData_mNG_PBP2B_CDM_30C.mat

description: Raw data for Fig. 4c, CDM 30C<br>
DOI: 10.25405/data.ncl.13214390
title: Fig4c_constrictionData_mNG_PBP2B_CDM_37C.mat

description: Raw data for Fig. 4c, CDM 37C<br>
DOI: 10.25405/data.ncl.13214390.v1
title: Fig4c_constrictionData_mNG_PBP2B_CDM_37C.mat

description: Raw data for Fig. 4c, CDM 37C<br>
DOI: 10.25405/data.ncl.13259126
title: Fig4c_constrictionData_mNG_PBP2B_PHMM_30C.mat

description: Raw data for Fig. 4c, PHMM 30C<br>
DOI: 10.25405/data.ncl.13259126.v1
title: Fig4c_constrictionData_mNG_PBP2B_PHMM_30C.mat

description: Raw data for Fig. 4c, PHMM 30C<br>
DOI: 10.25405/data.ncl.13259132
title: Fig4c_constrictionData_mNG_PBP2B_PHMM_37C.mat

description: Raw data for Fig. 4c, PHMM 37C<br>
DOI: 10.25405/data.ncl.13259132.v1
title: Fig4c_constrictionData_mNG_PBP2B_PHMM_37C.mat

description: Raw data for Fig. 4c, PHMM 37C<br>
DOI: 10.6084/m9.figshare.12563192
title: CovMulNet19.zip

description: CovMulNet19 is a comprehensive network containing all available known interactions involving SARS-CoV-2 proteins, interacting-human proteins, diseases and symptoms that are related to these human proteins, and compounds that can potentially target them. Extensive network analysis methods, based on a bootstrap approach, allow us to prioritise a list of diseases that display a high similarity to \covid and a list of drugs that could potentially be beneficial to treat patients. As a key feature of CovMulNet19, the inclusion of symptoms allows a deeper characterization of the disease pathology, representing a useful proxy for CoVid19-related molecular processes. We recapitulate many of the known symptoms of the disease and we find the most similar diseases to COVID-19 reflect conditions that are risk factors in patients. <br>
DOI: 10.6084/m9.figshare.12563192.v6
title: CovMulNet19.zip

description: CovMulNet19 is a comprehensive network containing all available known interactions involving SARS-CoV-2 proteins, interacting-human proteins, diseases and symptoms that are related to these human proteins, and compounds that can potentially target them. Extensive network analysis methods, based on a bootstrap approach, allow us to prioritise a list of diseases that display a high similarity to \covid and a list of drugs that could potentially be beneficial to treat patients. As a key feature of CovMulNet19, the inclusion of symptoms allows a deeper characterization of the disease pathology, representing a useful proxy for CoVid19-related molecular processes. We recapitulate many of the known symptoms of the disease and we find the most similar diseases to COVID-19 reflect conditions that are risk factors in patients. <br>
DOI: 10.25405/data.ncl.13214225
title: SIfig24_REV_constrictionData_mNG_PBP2B_PHMM_37C_PC19_noDMSO.mat

description: Raw data for Supp. Fig. 24, no DMSO<br>
DOI: 10.25405/data.ncl.13214225.v1
title: SIfig24_REV_constrictionData_mNG_PBP2B_PHMM_37C_PC19_noDMSO.mat

description: Raw data for Supp. Fig. 24, no DMSO<br>
DOI: 10.25405/data.ncl.13214222
title: SIfig24_REV_constrictionData_mNG_PBP2B_PHMM_37C_DMSO.mat

description: Raw data for Supp. Fig. 24, DMSO<br>
DOI: 10.25405/data.ncl.13214222.v1
title: SIfig24_REV_constrictionData_mNG_PBP2B_PHMM_37C_DMSO.mat

description: Raw data for Supp. Fig. 24, DMSO<br>
DOI: 10.25405/data.ncl.13214216
title: SIfig17_REV_sourceData_FtsZGFP_D213A_CDM_30C.mat

description: Raw data for Supp. Fig. 17<br>
DOI: 10.25405/data.ncl.13214216.v1
title: SIfig17_REV_sourceData_FtsZGFP_D213A_CDM_30C.mat

description: Raw data for Supp. Fig. 17<br>
DOI: 10.25405/data.ncl.13214210
title: SIfig2_Cell Length Analysis.csv

description: Raw data for Supp. Fig. 2<br>
DOI: 10.25405/data.ncl.13214210.v1
title: SIfig2_Cell Length Analysis.csv

description: Raw data for Supp. Fig. 2<br>
DOI: 10.25405/data.ncl.13214438
title: Fig3b_REV_sourceData_FtsZGFP_PC19.csv

description: Raw data for Fig. 3b<br>
DOI: 10.25405/data.ncl.13214438.v1
title: Fig3b_REV_sourceData_FtsZGFP_PC19.csv

description: Raw data for Fig. 3b<br>
DOI: 10.25405/data.ncl.13259141
title: Fig3d_SIfig18_REV_sourceData_2color_PC19.csv

description: Raw data for Fig. 3d and Supp. Fig. 18<br>
DOI: 10.25405/data.ncl.13259141.v1
title: Fig3d_SIfig18_REV_sourceData_2color_PC19.csv

description: Raw data for Fig. 3d and Supp. Fig. 18<br>
DOI: 10.17632/9ypp55zhj6.1
title: Data for elevated CI on 27 June in Central-east China

description: Files named as vdras*.nc are output from VDRAS model, more description about vdras outputs can be seen in the vdras_readme.pdf; Files named as wrfout*.nc are output from WRFV4.0 model; AWS_accumulated_precipitation.nc and CI_related_prep_AWSs.nc are rainfall data generated from AWSs; Radar_data are radar observations in NetCDF format from 00 to 12 UTC, on 27 June, 2016. There are two variables in each file. CSCART is reflectivity, and URSCART is radial velocity. Folders named in sequence, from Radar_data_01 to Radar_data_05, represent radar station rHBJZ, rHBYC, rHNCD, rHNCS, and rHNYY.
DOI: 10.25405/data.ncl.13214255
title: SIfig19_REV_sourceData_mNG_PBP2B_PHMM_37C.csv

description: Raw data for Supp. Fig. 19<br>
DOI: 10.25405/data.ncl.13214255.v1
title: SIfig19_REV_sourceData_mNG_PBP2B_PHMM_37C.csv

description: Raw data for Supp. Fig. 19<br>
DOI: 10.17632/m28yb8sk5y.1
title: Netflow data analysis to identify malicious activity

description: Netflow data from a large public institution. The data indicate countries and network area from where network scanning activities originate. These data can be analyzed to identify potentially malicious actors.
DOI: 10.17632/8sydnkkgtb.1
title: Component data of oil sample treated by microwave and/or nano catalyst

description: Firstly, 10% to 50% water content was selected for the experimental study. Secondly, the metal nano catalyst was prepared by a certain method. Then, the viscosity reduction treatment was carried out under the optimal processing conditions of microwave-only treatment, nano-catalyst-only treatment, and treatment using nano-catalysts assisted with microwave treatment. After the processing, we used solubility to separate the group components to obtain SARA (saturates, aromatics, resins and asphaltenes), used a Fourier infrared spectrometer to perform infrared analysis, used an element analyzer to determine the C, H, O, N, and S content, and used a gas chromatography mass spectrometry to detect changes in the composition of the oil sample to finally explore the mechanism of viscosity reduction.
DOI: 10.25405/data.ncl.13214207
title: SIfig14_REV_sourceData_FtsZGFP_PC19_CDM_30C.csv

description: Raw data for Supp. Fig. 14<br>
DOI: 10.25405/data.ncl.13214207.v1
title: SIfig14_REV_sourceData_FtsZGFP_PC19_CDM_30C.csv

description: Raw data for Supp. Fig. 14<br>
DOI: 10.17632/47fwktdc6r.1
title: My analysis data

description: It's a test for my analysis database
DOI: 10.25405/data.ncl.13214249
title: SIfig15_REV_sourceData_FtsZGFP_PC58_PHMM_37C.csv

description: Raw data for Supp. Fig. 15<br>
DOI: 10.25405/data.ncl.13214249.v1
title: SIfig15_REV_sourceData_FtsZGFP_PC58_PHMM_37C.csv

description: Raw data for Supp. Fig. 15<br>
DOI: 10.25405/data.ncl.13214213
title: SIfig10_REV_sim_Zdynamics_allTrackCSVs.zip

description: Raw data for Supp. Fig. 10<br>
DOI: 10.25405/data.ncl.13214213.v1
title: SIfig10_REV_sim_Zdynamics_allTrackCSVs.zip

description: Raw data for Supp. Fig. 10<br>
DOI: 10.17632/963z9x3frd.1
title: Plumage manipulation alters associations between behavior, physiology, internal microbiome, and fitness

description: Data and R code that goes with the paper: Plumage manipulation alters associations between behavior, physiology, internal microbiome, and fitness.
DOI: 10.17632/y8fnbz9j2x.1
title: Fish assemblage and fish habitat response to intentional, managed streamflow intermittency

description: Fish assemblage data and fish habitat data collected from 10 sites in the Rio Grande near Bosque del Apache National Wildlife Refuge, New Mexico, in 2020. Surveys were performed weekly for five weeks as surface was intentionally reduced.
DOI: 10.25405/data.ncl.13259159
title: Fig2c_FtsZGFP_DMSO.csv

description: Raw data for Fig. 2c, DMSO<br>
DOI: 10.25405/data.ncl.13259159.v1
title: Fig2c_FtsZGFP_DMSO.csv

description: Raw data for Fig. 2c, DMSO<br>
DOI: 10.17632/rsjcmdwby7.2
title: Age-specific sensitivity of sperm length and testes size to developmental temperature.
DOI: 10.17632/d7grg846wv.1
title: Hedonic dataset of the metropolitan housing market—cases in South Korea

description: This dataset was generated for analyzing the economic impacts of subway networks on housing prices in metropolitan areas. The provision of transit networks and accompanying improvement in accessibility induce various impacts and we focused on the economic impacts realized through housing prices. As a proxy of housing price, we consider the price of condominiums, the dominant housing type in South Korea. Although our focus is transit accessibility and housing prices, the presented dataset is applicable to other studies. In particular, it provides a wide range of variables closely related to housing price, including housing properties, local amenities, local demographic characteristics, and control variables for the seasonality. Many of these variables were scientifically generated by our research team. Various distance variables were constructed in a geographic information system environment based on public data and they are useful not only for exploring environmental impacts on housing prices, but also for other statistical analyses in regard to real estate and social science research. The four metropolitan areas covered by the data—Busan, Daegu, Daejeon, and Gwangju—are independent of the transit systems of Greater Seoul, providing accurate information on the metropolitan structure separate from the capital city.
DOI: 10.25405/data.ncl.13259162
title: Fig2c_FtsZGFP_PC19.csv

description: Raw data for Fig. 2c, PC19<br>
DOI: 10.25405/data.ncl.13259162.v1
title: Fig2c_FtsZGFP_PC19.csv

description: Raw data for Fig. 2c, PC19<br>
DOI: 10.17632/x22n4y8s33.1
title: Phase Separation-mediated Condensation of Whirlin-Myo15-Eps8 Stereocilia Tip Complex

description: Raw imaging data for Lin et al Phase Separation-mediated Condensation of Whirlin-Myo15-Eps8 Stereocilia Tip Complex.
DOI: 10.25405/data.ncl.13259165
title: Fig2c_FtsZGFP_PenG.csv

description: Raw data for Fig. 2c, PenG<br>
DOI: 10.25405/data.ncl.13259165.v1
title: Fig2c_FtsZGFP_PenG.csv

description: Raw data for Fig. 2c, PenG<br>
DOI: 10.17632/9y2yhw45zt.1
title: Data from a Survey of the Philippines’ Local Governments on their Risk Management Strategies to Natural Disasters
DOI: 10.17632/kbvcdw5b4m.2
title: Data for: Clinical Mastitis in Cows based on Udder Parameter using Internet of Things (IoT)

description: The data is collected from the udder of a cow to detect clinical mastitis. The four flex sensors and a temperature sensor are used to collect the udder data. Milk image is processed to find the quality of milk which also affects clinical mastitis. In the milk quality attribute, 0 indicates the normal milk and 1 indicates the abnormal milk. The data attributes are Cow_ID, Day, Breed, Month after giving birth, previous occurrence of mastitis, size of an udder (udder front left inhale and exhale limit, udder front right inhale and exhale limit, udder rear left inhale and exhale limit, udder rear right inhale and exhale limit), the temperature of a cow, the hardness of an udder from user input via a switch, and pain due to swelling of an udder. There are two class normal cows indicated as 0 and mastitis cow indicated as 1. By analyzing the data using an efficient algorithm faster track of clinical mastitis in the cow is provided. The SAC is designed to deploy flex sensors and temperature sensor, using raspberry pi and analog to digital converter data from the sensors are wirelessly collected. As sensors are connected to the internet the IoT is in the picture to gather data. The IoT is used to monitor animal health so the concept is called the Internet of Animal Health Things (IoAHT).
DOI: 10.15468/dl.9qv5ch
title: Occurrence Download

description: A dataset containing 2040 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhododendron wadanum"
 ]
}

 The dataset includes 2040 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010425-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.spwtch
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.28_1",
 "TaxonKey is Melilotus albus"
 ]
}

 The dataset includes 74 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010426-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/1re-75g-xp0
title: Oligia latruncula ([Denis & Schiffermüller], 1775)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/4jb-dmt-md3
title: Eupithecia abbreviata Stephens, 1831

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/dl.fdvccx
title: Occurrence Download

description: A dataset containing 1195 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Month is October",
 "PublishingCountry is Portugal",
 "TaxonKey is Ichthyaetus audouinii"
 ]
}

 The dataset includes 1195 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010427-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kb45ru
title: Occurrence Download

description: A dataset containing 12981 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Rosa sherardii"
 ]
}

 The dataset includes 12981 records from 170 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010428-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d9fra4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eichhornia azurea",
 "Country is Japan",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010430-250827131500795/datasets/export for details.
DOI: 10.15468/dl.btd69g
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eichhornia azurea",
 "Country is Netherlands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010431-250827131500795/datasets/export for details.
DOI: 10.15468/dl.fwmen5
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eichhornia azurea",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010432-250827131500795/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/12913171
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.3535/7rn-31g-5xj
title: Amathusiini

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/mpa-81k-hnh
title: Satyrinae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/teb-r72-dtv
title: Danaini

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/e2b-g2e-ncs
title: Danaini

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/e4a-kdx-1z7
title: Danaini

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/r6t-jdv-dgz
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/hm4-av4-8ty
title: Danaini

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/s1x-7s8-pwn
title: Satyrinae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/v8h-0tg-x2d
title: Danaini

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/p5e-fny-dra
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/xbe-nan-tpc
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/dl.j36fcx
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lates microlepis)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 36 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010436-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7h6fec
title: Occurrence Download

description: A dataset containing 1019 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ribes maximowiczianum"
 ]
}

 The dataset includes 1019 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010435-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/b1c-mg4-67l
title: Lepidoptera Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/13f-nzd-ezd
title: Nymphalidae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/38t-g7m-m3c
title: Nymphalidae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.