cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2pc2fl
title: CCDC 2483299: Experimental Crystal Structure Determination

description: Related Article: Wuji Wei, Yunbin Li, Furong Yuan, Yixuan Lin, Hongyu Lin, Guanrui Han, Bingxiang Ma, Zhen Yuan, Shengchang Xiang, Banglin Chen, Zhangjing Zhang|2025|Angew.Chem.,Int.Ed.|64|e19313|doi:10.1002/anie.202519313
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2qd5s3
title: CCDC 2514155: Experimental Crystal Structure Determination

description: Related Article: Wuji Wei, Yunbin Li, Furong Yuan, Yixuan Lin, Hongyu Lin, Guanrui Han, Bingxiang Ma, Zhen Yuan, Shengchang Xiang, Banglin Chen, Zhangjing Zhang|2025|Angew.Chem.,Int.Ed.|64|e19313|doi:10.1002/anie.202519313
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2lt4n7
title: CCDC 2407449: Experimental Crystal Structure Determination

description: Related Article: Priyanuj Hazarika, Bishal Bhattacharyya, Dipankar Nath, Nilakshi Dutta, Babulal Das, Diganta Sarma|2026|CSD Communication|||
description: Related Article: Hazarika, P.K., Bhattacharyya, B., Nath, D., Dutta, N., Das, B. and Sarma, D.,|2025|Eur.J.Org.Chem.|28|e202500575|doi:10.1002/ejoc.202500575
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.fc9j5q
title: Occurrence Download

description: A dataset containing 934 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((118.247 6.073138, 118.176344 6.067567, 118.107432 6.050991, 118.041964 6.023821, 117.981555 5.986726, 117.927696 5.940621, 117.881712 5.886645, 117.844734 5.826127, 117.817672 5.76056, 117.801189 5.691559, 117.795687 5.620826, 117.801297 5.5501, 117.817877 5.481124, 117.845016 5.415595, 117.882043 5.355125, 117.928044 5.301201, 117.981887 5.255149, 118.042245 5.218101, 118.107636 5.190969, 118.176451 5.174418, 118.247 5.168855, 118.317549 5.174418, 118.386364 5.190969, 118.451755 5.218101, 118.512113 5.255149, 118.565956 5.301201, 118.611957 5.355125, 118.648984 5.415595, 118.676123 5.481124, 118.692703 5.5501, 118.698313 5.620826, 118.692811 5.691559, 118.676328 5.76056, 118.649266 5.826127, 118.612288 5.886645, 118.566304 5.940621, 118.512445 5.986726, 118.452036 6.023821, 118.386568 6.050991, 118.317656 6.067567, 118.247 6.073138))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 934 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007711-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3qf892
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.88439 23.917733, 88.80757199999999 23.912156, 88.732665 23.895564, 88.661531 23.868369, 88.595934 23.831248, 88.537498 23.785122, 88.487666 23.731136, 88.447661 23.670627, 88.418459 23.605094, 88.40076500000001 23.536155, 88.394997 23.465513, 88.401279 23.394908, 88.419437 23.326077, 88.44900800000001 23.260711, 88.489249 23.200412, 88.539163 23.146659, 88.597517 23.100766, 88.66287699999999 23.063856, 88.733644 23.036828, 88.808087 23.020343, 88.88439 23.014803, 88.96069300000001 23.020343, 89.03513599999999 23.036828, 89.105903 23.063856, 89.171263 23.100766, 89.229617 23.146659, 89.27953100000001 23.200412, 89.319772 23.260711, 89.349343 23.326077, 89.367501 23.394908, 89.373783 23.465513, 89.368015 23.536155, 89.35032099999999 23.605094, 89.321119 23.670627, 89.281114 23.731136, 89.23128199999999 23.785122, 89.17284600000001 23.831248, 89.107249 23.868369, 89.036115 23.895564, 88.961208 23.912156, 88.88439 23.917733))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007713-260120142942310/datasets/export for details.
DOI: 10.5066/p1ay9pk9
title: Results of generalized least-squares (GLS) regression for 63 USGS streamgages in urban areas in Washington D.C. and parts of Delaware, Maryland, New Jersey, Pennsylvania, and Virginia using data through water year 2022

description: This dataset contains results of generalized least-squares (GLS) regression for 63 streamflow gaging stations (streamgages) operated by the U.S. Geological Survey (USGS) on urban streams in Washington D.C. and parts of Delaware, Maryland, New Jersey, Pennsylvania, and Virginia. This dataset was created to support the Washington D.C. StreamStats project funded by the Washington D.C. Department of Energy and Environment (DOEE). GLS regression was used to relate drainage area, basin slope, and percent of impervious cover (Kline and others, 2025b) to previously published estimates of streamflows corresponding to the 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 annual exceedance probabilities (AEPs; Kline and others, 2025a). From this regression, equations were developed that can be used to predict streamflows corresponding to the eight selected AEPs at ungaged locations on urban streams (percent developed imperviousness greater than 10%; Homer and others, 2015) in the study area. Standard errors of prediction ranged from 46.1 percent for the 0.2 AEP (the 5-year flood) to 55.0 percent for the 0.002 AEP (the 500-year flood).  GLS regression was conducted using version 3.0 of USGS weighted regression (WREG) software (Farmer, 2019; Eng and others, 2009).The input and output files from GLS regression in WREG are located within the "WREG_input.zip" folder. The input files are a text file of basin characteristics for all 63 selected streamgages in the study area ("DC_WREG_SiteInfo.txt") and the peak-flow ("DCStreamStats_FFreq.pkf") and specification ("DCStreamStats_FFreq.psf") files from at-site flood-frequency analysis in version 8.1.0 of USGS PeakFQ software. The following WREG output files are located in the "GLS_output" directory in sub-directories by AEP: "coef.txt," "CoVarMat.txt," "FitandResid.txt," "modelInput.txt," "outputRaw.rda," "PerformanceMetrics.txt," "ResLevInf.txt," and "Weighting.txt". USGS site information, values of the basin characteristics, WLS estimates of streamflows corresponding to the selected AEPs and their variances, and the residual from GLS regression are in file "GLS_Results.csv". The regression equations for each AEP and their associated performance metrics are in file "RegressionEquations.csv".
DOI: 10.15468/dl.3yd43c
title: Occurrence Download

description: A dataset containing 178 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Centrochelys sulcata",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation)"
 ]
}

 The dataset includes 178 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007714-260120142942310/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/14595923
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.9p5rxy
title: Occurrence Download

description: A dataset containing 85 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Azorella lycopodioides",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 85 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007715-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yzv8b6
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((102.238 6.075138, 102.167344 6.069567, 102.098431 6.052991, 102.032963 6.025821, 101.972554 5.988726, 101.918695 5.942621, 101.87271 5.888645, 101.835733 5.828127, 101.808671 5.76256, 101.792188 5.693559, 101.786685 5.622826, 101.792295 5.5521, 101.808876 5.483124, 101.836015 5.417595, 101.873042 5.357125, 101.919043 5.303201, 101.972886 5.257149, 102.033245 5.220101, 102.098636 5.192969, 102.167451 5.176418, 102.238 5.170855, 102.308549 5.176418, 102.377364 5.192969, 102.442755 5.220101, 102.503114 5.257149, 102.556957 5.303201, 102.602958 5.357125, 102.639985 5.417595, 102.667124 5.483124, 102.683705 5.5521, 102.689315 5.622826, 102.683812 5.693559, 102.667329 5.76256, 102.640267 5.828127, 102.60329 5.888645, 102.557305 5.942621, 102.503446 5.988726, 102.443037 6.025821, 102.377569 6.052991, 102.308656 6.069567, 102.238 6.075138))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007716-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13020/ngm8-2t32
title: Narrative Dynamic Assessment Task (NDAT): Protocol Fidelity Checklist

description: The Narrative Dynamic Assessment Task (NDAT) is a tool that can be used by speech-language pathologists and researchers to better understand the language learning skills of children. The NDAT was designed for use with 5- to 6-year old multilingual children who speak English in addition to another home language. The NDAT includes three phases: Test, Teach, and Retest and can be completed in less than 30 minutes. The NDAT was developed by the was developed by the Child Language Intervention Lab at the University of Minnesota as part of the NIH-funded SMART Explicit Study (R01DC017927), which examines explicit and implicit grammatical instruction. These materials are released to provide researchers and clinicians with a tool for evaluating morphosyntactic skills in children aged 5 to 9 years. No participant data are included.
description: The upload includes administration and scoring instructions and an examiner fidelity of administration checklist.
DOI: 10.15468/dl.q7q4up
title: Occurrence Download

description: A dataset containing 63 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anopheles benarrochi"
 ]
}

 The dataset includes 63 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007717-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18353227
title: om GNSS inversion and reduced-order modeling-accelerated rate-and-state friction simulations Code and Data

description: Yohai Magen1, Dave A. May1, Alice-Agnes Gabriel1,2

1 Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, CA, USA

2 Department of Earth and Environmental Sciences, Ludwig-Maximilians-Universität München, Munich, Germany

 

**Corresponding author**: Yohai Magen (ymagen@ucsd.edu)

 

---

Please read README.md for more details
DOI: 10.5281/zenodo.18353226
title: om GNSS inversion and reduced-order modeling-accelerated rate-and-state friction simulations Code and Data

description: Yohai Magen1, Dave A. May1, Alice-Agnes Gabriel1,2

1 Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, CA, USA

2 Department of Earth and Environmental Sciences, Ludwig-Maximilians-Universität München, Munich, Germany

 

**Corresponding author**: Yohai Magen (ymagen@ucsd.edu)

 

---

Please read README.md for more details
DOI: 10.15468/dl.x8ygc5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.88439 23.917733, 88.80757199999999 23.912156, 88.732665 23.895564, 88.661531 23.868369, 88.595934 23.831248, 88.537498 23.785122, 88.487666 23.731136, 88.447661 23.670627, 88.418459 23.605094, 88.40076500000001 23.536155, 88.394997 23.465513, 88.401279 23.394908, 88.419437 23.326077, 88.44900800000001 23.260711, 88.489249 23.200412, 88.539163 23.146659, 88.597517 23.100766, 88.66287699999999 23.063856, 88.733644 23.036828, 88.808087 23.020343, 88.88439 23.014803, 88.96069300000001 23.020343, 89.03513599999999 23.036828, 89.105903 23.063856, 89.171263 23.100766, 89.229617 23.146659, 89.27953100000001 23.200412, 89.319772 23.260711, 89.349343 23.326077, 89.367501 23.394908, 89.373783 23.465513, 89.368015 23.536155, 89.35032099999999 23.605094, 89.321119 23.670627, 89.281114 23.731136, 89.23128199999999 23.785122, 89.17284600000001 23.831248, 89.107249 23.868369, 89.036115 23.895564, 88.961208 23.912156, 88.88439 23.917733))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007718-260120142942310/datasets/export for details.
DOI: 10.6084/m9.figshare.31136815
title: Cryo-EM maps and models for GluN1/GluN3A NMDARs

description: Cryo-EM maps and models for the antagonist-bound, pre-active, active, and desensitized state GluN1/GluN3A receptors.
DOI: 10.6084/m9.figshare.31136815.v1
title: Cryo-EM maps and models for GluN1/GluN3A NMDARs

description: Cryo-EM maps and models for the antagonist-bound, pre-active, active, and desensitized state GluN1/GluN3A receptors.
DOI: 10.5281/zenodo.18344369
title: Horizontal decorrelation scales of turbulent dissipation in the ocean thermocline: datasets

description: Processed and gridded data in netCDF format for the seven FCS profilers deployed during the Feb 2025 Arcterx cruise in the West Pacific Ocean.

The associated paper is Hughes and Moum (2026) Horizontal decorrelation scales of turbulent dissipation in the ocean thermocline, submitted to the Journal of Physical Oceanography.

Profillers were deployed on February 6 and left to profile once every ~30 minutes. The dataset here, as in the associated paper, is for the first three weeks after deployment. Profiles were from the surface to ~180m and back.

Individual profiles were processed following Hughes et al. (2023), Ocean Sci., doi: 10.5194/os-19-193-2023https://github.com/OceanMixingGroup/flippin-chi-solo

Profiles were then interpolated onto a 1m vertical grid.Interpolation is nearest neighbor for turbulence quantities (and profiling speed).Linear interpolation otherwise.

Variables:

z (Nz, 1):               Depth grid (m)time (1, Nt):            Seconds since Jan 01, 1970 (UTC)isUP (1, Nt):            Whether profile is upwardlat (1, Nt):             Latitude (decimal degrees)lon (1, Nt):             Longitude (decimal degrees)T1 (Nz, Nt):             Temperature from thermistor 1 (degC)T2 (Nz, Nt):             Temperature from thermistor 2 (degC)T (Nz, Nt):              Best combination of T1 and T2 (degC)Wspd (Nz, Nt):           Profiling speed (m/s, positive for both directions)Wspd_min (Nz, Nt):       Min profiling speed in block (m/s, positive for both directions)eps1 (Nz, Nt):           Dissipation rate from shear probe 1 (W/kg)eps2 (Nz, Nt):           Dissipation rate from shear probe 2 (W/kg)epsilon (Nz, Nt):        Best combination of eps1 and eps2 (W/kg)eps1_chi (Nz, Nt):       Dissipation rate from thermistor 1 (W/kg)eps2_chi (Nz, Nt):       Dissipation rate from thermistor 2 (W/kg)epsilon_chi (Nz, Nt):    Best combination of eps1_chi and eps2_chi (W/kg)dTdz (Nz, Nt):           Temperature gradient (K/m)N2 (Nz, Nt):             Squared buoyancy frequency from dTdz (s^-2)MLD (Nt):                Mixed layer depth inferred from epsilon (m)

Additional, higher-resolution Seabird CTD data:

z (Nz_ctd, 1)            Depth grid for Seabird CTD data (m)T (Nz_ctd, Nt):          Temperature from Seabird CTD (degC); only downcastsS (Nz_ctd, Nt):          Salinity from Seabird CTD (psu); only downcasts

Created by Ken Hughes's scripts: arcterx23_create_mat_summary.mconvert_arcterx25_mat_summaries_to_netcdf.m

Additional notes:

If this is unit 4007, combined epsilon is just eps2.If this is unit 4009, combined epsilon is just eps1.Data that were obviously bad were manually removed
DOI: 10.5281/zenodo.18344370
title: Horizontal decorrelation scales of turbulent dissipation in the ocean thermocline: datasets

description: Processed and gridded data in netCDF format for the seven FCS profilers deployed during the Feb 2025 Arcterx cruise in the West Pacific Ocean.

The associated paper is Hughes and Moum (2026) Horizontal decorrelation scales of turbulent dissipation in the ocean thermocline, submitted to the Journal of Physical Oceanography.

Profillers were deployed on February 6 and left to profile once every ~30 minutes. The dataset here, as in the associated paper, is for the first three weeks after deployment. Profiles were from the surface to ~180m and back.

Individual profiles were processed following Hughes et al. (2023), Ocean Sci., doi: 10.5194/os-19-193-2023https://github.com/OceanMixingGroup/flippin-chi-solo

Profiles were then interpolated onto a 1m vertical grid.Interpolation is nearest neighbor for turbulence quantities (and profiling speed).Linear interpolation otherwise.

Variables:

z (Nz, 1):               Depth grid (m)time (1, Nt):            Seconds since Jan 01, 1970 (UTC)isUP (1, Nt):            Whether profile is upwardlat (1, Nt):             Latitude (decimal degrees)lon (1, Nt):             Longitude (decimal degrees)T1 (Nz, Nt):             Temperature from thermistor 1 (degC)T2 (Nz, Nt):             Temperature from thermistor 2 (degC)T (Nz, Nt):              Best combination of T1 and T2 (degC)Wspd (Nz, Nt):           Profiling speed (m/s, positive for both directions)Wspd_min (Nz, Nt):       Min profiling speed in block (m/s, positive for both directions)eps1 (Nz, Nt):           Dissipation rate from shear probe 1 (W/kg)eps2 (Nz, Nt):           Dissipation rate from shear probe 2 (W/kg)epsilon (Nz, Nt):        Best combination of eps1 and eps2 (W/kg)eps1_chi (Nz, Nt):       Dissipation rate from thermistor 1 (W/kg)eps2_chi (Nz, Nt):       Dissipation rate from thermistor 2 (W/kg)epsilon_chi (Nz, Nt):    Best combination of eps1_chi and eps2_chi (W/kg)dTdz (Nz, Nt):           Temperature gradient (K/m)N2 (Nz, Nt):             Squared buoyancy frequency from dTdz (s^-2)MLD (Nt):                Mixed layer depth inferred from epsilon (m)

Additional, higher-resolution Seabird CTD data:

z (Nz_ctd, 1)            Depth grid for Seabird CTD data (m)T (Nz_ctd, Nt):          Temperature from Seabird CTD (degC); only downcastsS (Nz_ctd, Nt):          Salinity from Seabird CTD (psu); only downcasts

Created by Ken Hughes's scripts: arcterx23_create_mat_summary.mconvert_arcterx25_mat_summaries_to_netcdf.m

Additional notes:

If this is unit 4007, combined epsilon is just eps2.If this is unit 4009, combined epsilon is just eps1.Data that were obviously bad were manually removed
DOI: 10.15468/dl.btj5hh
title: Occurrence Download

description: A dataset containing 934 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((118.167 6.093137, 118.096341 6.087566, 118.027426 6.070991, 117.961956 6.043821, 117.901546 6.006725, 117.847684 5.960621, 117.801699 5.906644, 117.76472 5.846126, 117.737657 5.780559, 117.721174 5.711559, 117.715671 5.640825, 117.721282 5.570099, 117.737863 5.501123, 117.765003 5.435594, 117.802031 5.375124, 117.848034 5.321201, 117.901878 5.275149, 117.962239 5.238102, 118.027632 5.210969, 118.096449 5.194418, 118.167 5.188856, 118.237551 5.194418, 118.306368 5.210969, 118.371761 5.238102, 118.432122 5.275149, 118.485966 5.321201, 118.531969 5.375124, 118.568997 5.435594, 118.596137 5.501123, 118.612718 5.570099, 118.618329 5.640825, 118.612826 5.711559, 118.596343 5.780559, 118.56928 5.846126, 118.532301 5.906644, 118.486316 5.960621, 118.432454 6.006725, 118.372044 6.043821, 118.306574 6.070991, 118.237659 6.087566, 118.167 6.093137))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 934 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007719-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.