cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc29jz61
title: CCDC 2131473: Experimental Crystal Structure Determination

description: Related Article: Shaochuan Li, Caiping Liu, Qihui Chen, Feilong Jiang, Daqiang Yuan, Qing-Fu Sun, Maochun Hong|2022|Chemical Science|13|9016|doi:10.1039/D2SC03093D
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.cc29jz72
title: CCDC 2131474: Experimental Crystal Structure Determination

description: Related Article: Shaochuan Li, Caiping Liu, Qihui Chen, Feilong Jiang, Daqiang Yuan, Qing-Fu Sun, Maochun Hong|2022|Chemical Science|13|9016|doi:10.1039/D2SC03093D
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.cc29jz83
title: CCDC 2131475: Experimental Crystal Structure Determination

description: Related Article: Shaochuan Li, Caiping Liu, Qihui Chen, Feilong Jiang, Daqiang Yuan, Qing-Fu Sun, Maochun Hong|2022|Chemical Science|13|9016|doi:10.1039/D2SC03093D
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.cc29jzlf
title: CCDC 2131485: Experimental Crystal Structure Determination

description: Related Article: Shaochuan Li, Caiping Liu, Qihui Chen, Feilong Jiang, Daqiang Yuan, Qing-Fu Sun, Maochun Hong|2022|Chemical Science|13|9016|doi:10.1039/D2SC03093D
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.cc29jzmg
title: CCDC 2131486: Experimental Crystal Structure Determination

description: Related Article: Shaochuan Li, Caiping Liu, Qihui Chen, Feilong Jiang, Daqiang Yuan, Qing-Fu Sun, Maochun Hong|2022|Chemical Science|13|9016|doi:10.1039/D2SC03093D
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: 10.25678/0008nj
title: Data for: Pixel-based mapping of open field and protected agriculture using constrained Sentinel-2 data

description: Protected agriculture boosts the production of vegetables, berries and fruits, and it plays a pivotal role in guaranteeing food security globally in the face of climate change. Remote sensing is proven to be useful for identifying the presence of (low-tech) plastic greenhouses and plastic mulches. However, the classification accuracy notoriously decreases in the presence of small-scale farming, heterogeneous land cover and unaccounted seasonal management of protected agriculture. Here, we present the random forest-based pixel-level Open field and Protected Agriculture land cover Classifier (OPAC) developed using Sentinel-2 L2A data. OPAC is trained using tiles from Switzerland over 2 years and the Almeria region in Spain over 1 acquisition day. OPAC classifies eight land covers typical of open field and protected agriculture (plastic mulches, low-tech greenhouses and for the first time high-tech greenhouses). Finally, we assess (1) how the land covers in OPAC are labelled in the Sentinel-2 Scene Classification Layer (SCL) and (2) the correspondence between pixels classified as protected agriculture by OPAC and by the best performing Advanced Plastic Greenhouse Index (APGI). To reduce anthropogenic land covers, we constrain the classification task to agricultural areas retrieved from cadastral data or the Corine Land Cover map. The 5-fold cross-validation reveals an overall accuracy of 92% but other classification scores are moderate when keeping the separation among the three classes of protected agriculture. However, all scores substantially improve upon grouping the three classes into one (with an Intersection Over Union of 0.58 as an average among the scores of the three classes and of 0.98 for one single class). Given the recently acknowledged importance of Sentinel-2 Band 1 (central wavelength of 443 nm), the classification accuracy of OPAC for the Swiss small-scale farming is mostly limited by the band's reduced spatial accuracy (60 m). A careful visual assessment indicates that OPAC achieves satisfactory generalization capabilities also in North European (the Netherlands) and four Mediterranean areas (Spain, Italy, Crete and Turkey) without the need of adding location and temporal specific information. There is good agreement among natural land covers classified by OPAC and the SCL. However, the SCL does not have a class for protected agriculture, the latter being often classified as clouds. APGI achieved similar to lower classification accuracies than OPAC. Importantly, the APGI classification task depends on a user-defined space- and time-specific threshold, whereas OPAC does not. Therefore, OPAC paves the way for rapid mapping of protected agriculture at continental scale.
DOI: 10.5281/zenodo.7105334
title: MHD model output for Ganymede's magnetosphere during Juno's flyby

description: This dataset contains the complete simulation output from our MHD model of Ganymede's magnetosphere adapted to Juno's PJ34 flyby in 2021 (Duling et al. 2022). The data was obtained by our application of the PLUTO simulation code v4.4 (Mignone et al. 2007) (http://plutocode.ph.unito.it/) described in Duling et al. 2022. The dataset includes the simulation variables on the simulation grid for a single timestep after steady state was reached. The grid has spherical geometry (r, theta, phi) with phi=0° longitude pointing towards Jupiter (positive y axis of the GPhiO system), phi=90° longitude pointing in the upstream direction (negative x axis of GPhiO) and theta=0° latitude at Ganymede's north pole (positive z axis of GPhiO). The following model variables are included: rho: plasma mass density<br> prs: thermal plasma pressure<br> vx1: plasma velocity radial component<br> vx2: plasma velocity theta component<br> vx3: plasma velocity phi component<br> Bx1: magnetic field radial component<br> Bx2: magnetic field theta component<br> Bx3: magnetic field phi component Additionally the following derived variables are included: Jx1: electric current density radial component<br> Jx2: electric current density theta component<br> Jx3: electric current density phi component<br> Bpx1: plasma magnetic field radial component<br> Bpx2: plasma magnetic field theta component<br> Bpx3: plasma magnetic field phi component Plasma magnetic field means that part of the total magnetic field that results from the plasma interaction. It equals the total magnetic field subtracted by the homogeneous upstream field and Ganymede's intrinsic and induced field. All values are in normalized units with these normalization factors: NORMR = 2.631e8 cm<br> NORMV = 1.4e7 cm/s<br> NORMRHO = 1.661e-22 g/cm^3<br> NORMPRS = 3.255e-08 dyne/cm^2<br> NORMB = 6.395e-04 Gauss<br> NORMJ = 5.801e-03 statA/cm^2 In Duling et al. 2022 we present results of a model sensitivity study. This dataset includes model output from our best guess setup (default setup) only. Since the data is in PLUTO's binary format "flt" we provide a Python code snippet that reads the data to data arrays. <strong>grid.out</strong><br> This ASCII file contains the grid dimensions and coordinates of the cell boundaries. <strong>data.0020.flt</strong><br> This binary file contains the simulation variables on the cell centers of the grid. <strong>pluto.0.log</strong><br> This ASCII file contains the header of the PLUTO logfile. <strong>read_data.py</strong><br> This Python code snippet helps with reading the data.
description: {"references": ["Mignone, A., Bodo, G., Massaglia, S., Matsakos, T., Tesileanu, O., Zanni, C., & Ferrari, A. (2007). PLUTO: A numerical code for computational astro- physics. The Astrophysical Journal Supplement Series, 170 (1), 228\u2013242. doi: 10.1086/513316", "http://plutocode.ph.unito.it/"]}
DOI: 10.5281/zenodo.7628718
title: MHD Model of Ganymede's Magnetosphere: Predicted magnetic field on Juno's trajectory

description: This dataset contains model results from a magnetohydrodynamic (MHD) model of Ganymede's magnetosphere adapted to Juno's PJ34 flyby in 2021. Here we publish predicted magnetic field components on Juno's trajectory that can be compared to MAG measurements and are displayed in Figure 3 of Duling et al. (2022). Each file contains data from one model. The dataset includes all models with parameter variations from Duling et al. (2022). These are summarized in Table 1 of Duling et al. (2022) and displayed in Figure 3 with the gray lines. If not varied, all models are run with the following parameters: Upstream Jovian background magnetic field B<sub>0 </sub>= (−15,24,−75) nT<br> Upstream plasma velocity v<sub>0</sub> = 140 km/s<br> Upstream plasma mass density \(\rho\)<sub>0</sub> = 100 amu/cm<sup>3</sup><br> Upstream plasma thermal pressure p<sub>0</sub> = 2.8 nPa<br> Ionization frequency \(\nu_{ion}\) = 2.2e-8/s<br> Atmospheric surface mass density \(n_{n,0}\) = 8e6/cm<sup>3</sup><br> Dipole Gauss coefficient \(g_1^0\) = −716.8 nT The published data files correspond to the following models with each one parameter variation: Parameter Value Filename Suffix default model - default Upstream Jovian background magnetic field (measured before flyby) B<sub>0 </sub>= (−16,3,−70) nT B0before Upstream Jovian background magnetic field (measured after flyby) B<sub>0 </sub>= (−14,43,−80) nT B0after Upstream plasma velocity (min) v<sub>0</sub> = 120 km/s v- Upstream plasma velocity (max) v<sub>0</sub> = 160 km/s v+ Upstream plasma mass density (min) \(\rho\)<sub>0</sub> = 10 amu/cm<sup>3</sup> rho- Upstream plasma mass density (max) \(\rho\)<sub>0</sub> = 160 amu/cm<sup>3</sup> rho+ Upstream plasma thermal pressure (min) p<sub>0</sub> = 1.0 nPa p- Upstream plasma thermal pressure (max) p<sub>0</sub> = 5.0 nPa p+ Ionization frequency (min) \(\nu_{ion}\) = 0.5e-8/s prod- Ionization frequency (max) \(\nu_{ion}\) = 10.0e-8/s prod+ Atmospheric surface mass density (min) \(n_{n,0}\) = 1.6e6/cm<sup>3</sup> nn- Atmospheric surface mass density (max) \(n_{n,0}\) = 40e6/cm<sup>3</sup> nn+ Dipole Gauss coefficient (min) \(g_1^0\) = −702.5 nT dipole- Dipole Gauss coefficient (max) \(g_1^0\) = −731.1 nT dipole+ Magnetic Field components and Juno's position are in GPhiO system. GPhiO is defined by the primary direction z parallel to Jupiter’s rotation axis, the secondary direction y is pointing from Ganymede's towards Jupiter's barycenter and x completes the right-handed system approximately in direction of plasma flow. Columns: Spacecraft time [UTC]<br> Bx modeled magnetic field in GPhiO [nT]<br> By modeled magnetic field in GPhiO [nT]<br> Bz modeled magnetic field in GPhiO [nT]<br> B modeled magnetic field magnitude [nT]<br> x of Juno in GPhiO [km]<br> y of Juno in GPhiO [km]<br> z of Juno in GPhiO [km]
DOI: 10.5281/zenodo.7628719
title: MHD Model of Ganymede's Magnetosphere: Predicted magnetic field on Juno's trajectory

description: This dataset contains model results from a magnetohydrodynamic (MHD) model of Ganymede's magnetosphere adapted to Juno's PJ34 flyby in 2021. Here we publish predicted magnetic field components on Juno's trajectory that can be compared to MAG measurements and are displayed in Figure 3 of Duling et al. (2022). Each file contains data from one model. The dataset includes all models with parameter variations from Duling et al. (2022). These are summarized in Table 1 of Duling et al. (2022) and displayed in Figure 3 with the gray lines. If not varied, all models are run with the following parameters: Upstream Jovian background magnetic field B<sub>0 </sub>= (−15,24,−75) nT<br> Upstream plasma velocity v<sub>0</sub> = 140 km/s<br> Upstream plasma mass density \(\rho\)<sub>0</sub> = 100 amu/cm<sup>3</sup><br> Upstream plasma thermal pressure p<sub>0</sub> = 2.8 nPa<br> Ionization frequency \(\nu_{ion}\) = 2.2e-8/s<br> Atmospheric surface mass density \(n_{n,0}\) = 8e6/cm<sup>3</sup><br> Dipole Gauss coefficient \(g_1^0\) = −716.8 nT The published data files correspond to the following models with each one parameter variation: Parameter Value Filename Suffix default model - default Upstream Jovian background magnetic field (measured before flyby) B<sub>0 </sub>= (−16,3,−70) nT B0before Upstream Jovian background magnetic field (measured after flyby) B<sub>0 </sub>= (−14,43,−80) nT B0after Upstream plasma velocity (min) v<sub>0</sub> = 120 km/s v- Upstream plasma velocity (max) v<sub>0</sub> = 160 km/s v+ Upstream plasma mass density (min) \(\rho\)<sub>0</sub> = 10 amu/cm<sup>3</sup> rho- Upstream plasma mass density (max) \(\rho\)<sub>0</sub> = 160 amu/cm<sup>3</sup> rho+ Upstream plasma thermal pressure (min) p<sub>0</sub> = 1.0 nPa p- Upstream plasma thermal pressure (max) p<sub>0</sub> = 5.0 nPa p+ Ionization frequency (min) \(\nu_{ion}\) = 0.5e-8/s prod- Ionization frequency (max) \(\nu_{ion}\) = 10.0e-8/s prod+ Atmospheric surface mass density (min) \(n_{n,0}\) = 1.6e6/cm<sup>3</sup> nn- Atmospheric surface mass density (max) \(n_{n,0}\) = 40e6/cm<sup>3</sup> nn+ Dipole Gauss coefficient (min) \(g_1^0\) = −702.5 nT dipole- Dipole Gauss coefficient (max) \(g_1^0\) = −731.1 nT dipole+ Magnetic Field components and Juno's position are in GPhiO system. GPhiO is defined by the primary direction z parallel to Jupiter’s rotation axis, the secondary direction y is pointing from Ganymede's towards Jupiter's barycenter and x completes the right-handed system approximately in direction of plasma flow. Columns: Spacecraft time [UTC]<br> Bx modeled magnetic field in GPhiO [nT]<br> By modeled magnetic field in GPhiO [nT]<br> Bz modeled magnetic field in GPhiO [nT]<br> B modeled magnetic field magnitude [nT]<br> x of Juno in GPhiO [km]<br> y of Juno in GPhiO [km]<br> z of Juno in GPhiO [km]
DOI: 10.6084/m9.figshare.20472123
title: surveytraitsarchive.xlsx

description: To evaluate how <em>Sedum</em> cover and water availability effect spontaneous plant biomass and both species and functional richness, we conducted a 10-month experiment in green roof microcosms sown with a mix of 14 plant species that commonly occur as spontaneous species on green roofs. We measured species abundance, biomass, and functional traits (specific leaf area, leaf dry matter content, and relative growth rate), and calculated species and functional richness.
DOI: 10.15468/dl.ujpsje
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rudgea quisquiliae Bruniera & Torres-Leite"
 ]
}

 The dataset includes 18 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0192498-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vk7z2a
title: Occurrence Download

description: A dataset containing 2286 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-104.14764 19.36336,-104.17456 19.35857,-104.19543 19.33162,-104.21631 19.28289,-104.2319 19.25469,-104.20532 19.2296,-104.17401 19.2239,-104.13171 19.1907,-104.07843 19.1741,-104.03668 19.18862,-104.02075 19.21923,-104.01471 19.24309,-104.02734 19.27978,-104.05701 19.30674,-104.09326 19.34199,-104.13062 19.35235,-104.13062 19.35235,-104.14764 19.36336))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2286 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0334405-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bf2wx8
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Clanculus albanyensis Jansen, 1995"
 ]
}

 The dataset includes 40 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045127-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s4zk3v
title: Occurrence Download

description: A dataset containing 188 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 {
 "or" : [
 "TaxonKey is Arceuthobium azoricum Wiens & Hawksw.",
 "TaxonKey is Arctagrostis latifolia (R.Br.) Griseb.",
 "TaxonKey is Arctophila fulva (Trin.) Andersson",
 "TaxonKey is Arenaria ciliata subsp. pseudofrigida Ostenf. & O.C.Dahl",
 "TaxonKey is Arenaria humifusa Wahlenb.",
 "TaxonKey is Arenaria provincialis Chater & G.Halliday",
 "TaxonKey is Argyranthemum pinnatifidum subsp. succulentum (Lowe) Humphries",
 "TaxonKey is Argyranthemum thalassophilum (Svent.) Humphries",
 "TaxonKey is Armeria berlengensis Daveau",
 "TaxonKey is Armeria helodes F.Martini & Poldini",
 "TaxonKey is Armeria littoralis Boiss.",
 "TaxonKey is Armeria neglecta Girard",
 "TaxonKey is Armeria pseudarmeria (Murray) Mansf.",
 "TaxonKey is Armeria rouyana Daveau",
 "TaxonKey is Armeria sampaioi (Bernis) Nieto Fel.",
 "TaxonKey is Armeria soleirolii Duby, 1830",
 "TaxonKey is Artemisia campestris subsp. bottnica (Lundstr. ex Kindb.) Tutin, 1976",
 "TaxonKey is Artemisia eriantha Ten.",
 "TaxonKey is Artemisia genipi Stechm.",
 "TaxonKey is Artemisia laciniata Willd.",
 "TaxonKey is Artemisia oelandica (Besser) Krasch.",
 "TaxonKey is Artemisia pancicii Ronniger ex Danihelka & Marhold",
 "TaxonKey is Asphodelus bento-rainhae P.Silva",
 "TaxonKey is Asplenium adulterinum Milde",
 "TaxonKey is Asplenium jahandiezi Rouy",
 "TaxonKey is Aster sorrentinii (Tod.) Lojac.",
 "TaxonKey is Astragalus alopecurus Pall.",
 "TaxonKey is Astragalus aquilanus Anzal.",
 "TaxonKey is Astragalus centralpinus Braun-Blanq.",
 "TaxonKey is Astragalus macrocarpus subsp. lefkarensis Meikle & Kirchhoff",
 "TaxonKey is Astragalus maritimus Moris",
 "TaxonKey is Astragalus peterfii Javorka",
 "TaxonKey is Astragalus verrucosus Moris",
 "TaxonKey is Asyneuma giganteum (Boiss.) Bornm.",
 "TaxonKey is Athamanta cortiana Ferrarini",
 "TaxonKey is Avenula hackelii (Henriq.) Holub",
 "TaxonKey is Azorina vidalii (H.C.Watson) Feer",
 "TaxonKey is Bassia saxicola (Guss.) A.J.Scott",
 "TaxonKey is Bellevalia dubia subsp. hackelii (Freyn) Feinbrun",
 "TaxonKey is Bellevalia hackelii Freyn",
 "TaxonKey is Berberis maderensis Lowe",
 "TaxonKey is Beta patula Sol. ex Aiton",
 "TaxonKey is Biscutella neustriaca Bonnet",
 "TaxonKey is Biscutella sempervirens subsp. vicentina (Samp.) Malag., 1973",
 "TaxonKey is Biscutella vincentina (Samp.) Rothm. ex Guinea",
 "TaxonKey is Botrychium simplex E.Hitchc.",
 "TaxonKey is Brassica glabrescens Poldini",
 "TaxonKey is Brassica hilarionis Post",
 "TaxonKey is Brassica insularis Moris",
 "TaxonKey is Brassica macrocarpa Guss."
 ]
 }
 ]
}

 The dataset includes 188 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002609-150410134957023/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h1m0l4
title: Occurrence Download

description: A dataset containing 136 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Heosemys annandalii (Boulenger, 1903)"
 ]
}

 The dataset includes 136 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036722-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9pcr3b
title: Occurrence Download

description: A dataset containing 1111 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Streptanthus heterophyllus Nutt."
 ]
}

 The dataset includes 1111 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0192501-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yq6dps
title: Occurrence Download

description: A dataset containing 101 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Coleochloa setifera (Ridl.) Gilly",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 101 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002609-150512124619364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zxqvs7
title: Occurrence Download

description: A dataset containing 640 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-73.84072 5.58606,-73.82247 5.55764,-73.78077 5.55451,-73.70074 5.57146,-73.68875 5.61082,-73.69396 5.6554,-73.75548 5.70727,-73.8084 5.70753,-73.85506 5.66582,-73.84072 5.58606))",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 640 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036526-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fughhw
title: Occurrence Download

description: A dataset containing 437 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is JPN.27_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Asterales"
 ]
}

 The dataset includes 437 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061763-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wweu82
title: Occurrence Download

description: A dataset containing 106021 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Thymus vulgaris L.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 106021 records from 589 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045143-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.