cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.3hw7vp
title: Occurrence Download

description: A dataset containing 864 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Macropus parma Waterhouse, 1846"
 ]
}

 The dataset includes 864 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002951-150316153013904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bjqvwv
title: Occurrence Download

description: A dataset containing 140 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Viburnum caudatum Greenm."
 ]
}

 The dataset includes 140 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0193580-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gk4axn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is 5acfef52-fcd3-4fff-ab5b-04eb5b9fee39"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046479-231002084531237/datasets/export for details.
DOI: 10.15468/dl.y6cmfw
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sciodaphyllum brownei Spreng."
 ]
}

 The dataset includes 55 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0193579-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kor2ya
title: Occurrence Download

description: A dataset containing 100 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Spergularia echinosperma Celak.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 100 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002951-150410134957023/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ntc9qk
title: Occurrence Download

description: A dataset containing 403 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Celtis boninensis Koidz."
 ]
}

 The dataset includes 403 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056223-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m72azr
title: Occurrence Download

description: A dataset containing 651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Apodemus semotus Thomas, 1908",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 651 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002951-150422101436696/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nraer6
title: Occurrence Download

description: A dataset containing 5717 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cercocarpus ledifolius Nutt."
 ]
}

 The dataset includes 5717 records from 143 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056658-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gre50z
title: Occurrence Download

description: A dataset containing 4628 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leopardus Gray, 1842"
 ]
}

 The dataset includes 4628 records from 129 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002951-150512124619364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xd6nyz
title: Occurrence Download

description: A dataset listing the 3394933 species recorded in GBIF matching the query:
{
 "OccurrenceStatus" : [
 "is Present"
 ]
}

 The dataset's 3394933 records were derived from 39304 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063564-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vqysni
title: Occurrence Download

description: A dataset containing 316 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corryocactus Britton & Rose"
 ]
}

 The dataset includes 316 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006949-171025204727650/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cdwrr3
title: Occurrence Download

description: A dataset containing 304236 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((83.2487 -17.64838,114.41316 -43.64746,154.70312 -53.80604,182.42399 -52.60078,187.24501 -31.76708,185.00668 -7.31762,180.18565 14.37697,163.1399 27.11824,145.06107 33.3167,124.74391 34.69413,94.95689 23.67466,84.45395 3.87403,83.2487 -17.64838))",
 "TaxonKey is Araneae"
 ]
}

 The dataset includes 304236 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005178-200221144449610/datasets/export for details.
DOI: 10.15468/dl.nisem4
title: Occurrence Download

description: A dataset containing 197 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cordia dodecandra DC."
 ]
}

 The dataset includes 197 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006950-150922153815467/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.52q7qc
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-79.92732558139537 -8.11046511627907,-78.18313953488374 -8.11046511627907,-78.18313953488374 -6.36627906976744,-79.92732558139537 -6.36627906976744,-79.92732558139537 -8.11046511627907))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Oreochromis niloticus (Linnaeus, 1758)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019088-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cqkpbq
title: Occurrence Download

description: A dataset containing 2397622845 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (Africa, Asia, Oceania, North America, South America, Europe)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2397622845 records from 44423 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031230-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.6335951
title: Dust extinction curves: Grasil-like

description: These datasets are based on the models described in Benson (2018), and are intended to mimic the geometries used by Grasil. <strong>Dust Properties</strong> Dust grain properties are taken from Draine (2003) - specifically their model with either R<sub>V</sub>=3.1 or R<sub>V</sub>=5.5 as encoded in the file name with prefix dustD03. <strong>Stellar Geometry</strong> Galactic disks follow exponential profiles in both radial and vertical directions, with the vertical scale height equal to 0.1 or 0.5 times the radial scale length as encoded in the file name with prefix hzStars. Note that spheroid radii in this work are listed as the scale radius, <em>r</em><sub>s</sub>, while Ferrara et al. (1999) listed the corresponding effective radius, <em>r</em><sub>e</sub>=<em>r</em><sub>s</sub>/1.16. <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 height. The value of <em>h</em><sub>z</sub> is encoded in each file name with prefix hzDust.
DOI: 10.5281/zenodo.6335950
title: Dust extinction curves: Grasil-like

description: These datasets are based on the models described in Benson (2018), and are intended to mimic the geometries used by Grasil. <strong>Dust Properties</strong> Dust grain properties are taken from Draine (2003) - specifically their model with either R<sub>V</sub>=3.1 or R<sub>V</sub>=5.5 as encoded in the file name with prefix dustD03. <strong>Stellar Geometry</strong> Galactic disks follow exponential profiles in both radial and vertical directions, with the vertical scale height equal to 0.1 or 0.5 times the radial scale length as encoded in the file name with prefix hzStars. Note that spheroid radii in this work are listed as the scale radius, <em>r</em><sub>s</sub>, while Ferrara et al. (1999) listed the corresponding effective radius, <em>r</em><sub>e</sub>=<em>r</em><sub>s</sub>/1.16. <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 height. The value of <em>h</em><sub>z</sub> is encoded in each file name with prefix hzDust.
DOI: 10.26186/146288
title: Tasmanian East Coast (GA4883)

description: This resource includes bathymetry data acquired during the Tasmanian East Coast bathymetry survey collected by Institute for Marine and Antarctic Studies (IMAS) University of Tasmania (UTAS) during the period 12 – 23 April 2021 on the RV Abyss using a Kongsberg Maritime EM2040C multibeam sonar (contracted from CSIRO). The Tasmanian East Coast bathymetry survey was led by Dr. Vanessa Lucieer (IMAS). The purpose of the project was to map the fine-scale spatial distribution of key abalone habitat impacted by urchins in &lt; 25 m water depth using multibeam acoustic imagery. This dataset contains seven 0.5m-resolution 32-bit floating point geotiff files of the bathymetry in study area and transits, derived from the processed EM2040C bathymetry data, using CARIS HIPS and SIPS software. A detailed report on the survey is provided in: Lucieer V, Keane J, Shelamoff V, Nau A, Ling S, Mapping abalone habitat impacted by Centrostephanus on the east coast of Tasmania: Final contracted report for the Abalone Industry Reinvestment Fund (AIRF Project 2021) and Tasmanian Climate Change Office (Climate Research Grants Program 2021), Institute for Marine and Antarctic Studies, UTAS, December (2021) [Contract Report] http://ecite.utas.edu.au/148298. This dataset is not to be used for navigational purposes. This dataset is published with the permission of the CEO, Geoscience Australia.
DOI: 10.26186/146333
title: Bunurong Marine National Park survey 2017 (GA4879)

description: This resource includes bathymetry data acquired during the Bunurong Marine National Park bathymetry survey acquired by Deakin University Marine Mapping Lab during the period of 14 – 16 June and 21 – 22 September 2017 onboard the MV Yolla using a Kongsberg Maritime EM2040C multibeam sonar. The Bunurong Marine National Park bathymetry survey was led by Dr. Daniel Ierodiaconou (Deakin University). The survey was part of a Parks Victoria project to better understand the habitats and associated biodiversity of Bunurong Marine National Park. This dataset contains a 2m-resolution 32-bit floating point geotiff file of the bathymetry in the study area, derived from the processed EM2040C bathymetry data, using CARIS HIPS and SIPS software. A detailed report on the survey is provided in: Young M, Porskamp P, Murfitt S, Wines S, Tinkler P, Bursic, J., Allan B, Howe S, Whitmarsh S, Pocklington J, Ierodiaconou D 2021. Baseline habitat mapping and enhanced monitoring trials of subtidal and intertidal reef habitats in Victoria’s marine national parks and sanctuaries. Parks Victoria Technical Series 116. This dataset is not to be used for navigational purposes. This dataset is published with the permission of the CEO, Geoscience Australia.
DOI: 10.5281/zenodo.6336095
title: Dust extinction curves: Ferrara (1999) original resolution

description: These datasets are based on the models described in Benson (2018), and are intended to closely match the models run by Ferrara et al. (1999) - they use the same dust grain properties and galactic geometry. Additionally, they are tabulated at the same inclinations, optical depths, wavelengths, and morphologies as in Ferrara et al. (1999). <strong>Dust Properties</strong> Dust grain albedos, scattering asymmetries, and opacities to extinction are taken from Gordon et al. (1997), for either their Milky Way, “MW”, or Small Magellanic Cloud, “SMC”, models (as encoded in each file name), and assume Henyey-Greenstein scattering. <strong>Stellar Geometry</strong> Galactic disks follow exponential profiles in both radial and vertical directions, with the vertical scale height equal to 0.0875 times the radial scale length. Spheroids follow spherical Jaffe (1983) profiles. Note that spheroid radii in this work are listed as the scale radius, <em>r</em><sub>s</sub>, while Ferrara et al. (1999) listed the corresponding effective radius, <em>r</em><sub>e</sub>=<em>r</em><sub>s</sub>/1.16. <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 height. The value of <em>h</em><sub>z</sub> is encoded in each file name.
DOI: 10.5281/zenodo.6336094
title: Dust extinction curves: Ferrara (1999) original resolution

description: These datasets are based on the models described in Benson (2018), and are intended to closely match the models run by Ferrara et al. (1999) - they use the same dust grain properties and galactic geometry. Additionally, they are tabulated at the same inclinations, optical depths, wavelengths, and morphologies as in Ferrara et al. (1999). <strong>Dust Properties</strong> Dust grain albedos, scattering asymmetries, and opacities to extinction are taken from Gordon et al. (1997), for either their Milky Way, “MW”, or Small Magellanic Cloud, “SMC”, models (as encoded in each file name), and assume Henyey-Greenstein scattering. <strong>Stellar Geometry</strong> Galactic disks follow exponential profiles in both radial and vertical directions, with the vertical scale height equal to 0.0875 times the radial scale length. Spheroids follow spherical Jaffe (1983) profiles. Note that spheroid radii in this work are listed as the scale radius, <em>r</em><sub>s</sub>, while Ferrara et al. (1999) listed the corresponding effective radius, <em>r</em><sub>e</sub>=<em>r</em><sub>s</sub>/1.16. <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 height. The value of <em>h</em><sub>z</sub> is encoded in each file name.
DOI: 10.5281/zenodo.6336104
title: AndroCT: Ten Years of App Call Traces in Android

description: A large-scale dataset on the dynamic profiles based on function calls of 35,974 benign and malicious Android apps from 10 historical years (2010 through 2019). Function calls are a commonly used means to model program behaviors, which may contribute to various code analysis approaches to assuring software correctness, reliability, and security. In particular, our dataset includes dynamic profiles of each app resulting from the same-length of time (10 mins) of being exercised by randomly generated inputs on both emulator and real device, enabling interesting and useful app analysis that reason about app behaviors in an evolutionary perspective while informing the differences of app behaviors on different run-time hardware platforms. Since we have 20 yearly datasets associated with 35,974 unique Android apps across the 10 years, profiling these apps took 12,000 hours. Considering the costs of filtering out apps that were originally sampled but that we were unable to profile (due to various reasons such as broken APKs, not being executable because of incompatibility issues, not instrumentable, etc.), we took over two years to produce all these traces. We hope to save future researchers' time in producing such a set of dynamic data to enable their empirical and technical work. ================== Thanks for your interest in our dataset. Collecting this dataset took tremendous computational and human effort. Thus, please observe the following restrictions in using our dataset: - Do not redistribute this dataset without our consent.<br> - Do not make commercial usage of this dataset.<br> - Get a faculty, or someone in a permanent position, to agree and commit to these conditions.<br> - When publishing your work that uses our dataset, please cite the following MSR 2021 data paper. <br> @inproceedings{AndroidCT,<br> title = {AndroCT: Ten Years of App Call Traces in Android},<br> author = {Wen Li, Xiaoqin Fu, and Haipeng Cai},<br> booktitle = {The 18th International Conference on Mining Software Repositories (MSR 2021), Data Showcase Track},<br> year = {2021},<br> }
DOI: 10.5281/zenodo.3632183
title: AndroCT: Ten Years of App Call Traces in Android

description: A large-scale dataset on the dynamic profiles based on function calls of 35,974 benign and malicious Android apps from 10 historical years (2010 through 2019). Function calls are a commonly used means to model program behaviors, which may contribute to various code analysis approaches to assuring software correctness, reliability, and security. In particular, our dataset includes dynamic profiles of each app resulting from the same-length of time (10 mins) of being exercised by randomly generated inputs on both emulator and real device, enabling interesting and useful app analysis that reason about app behaviors in an evolutionary perspective while informing the differences of app behaviors on different run-time hardware platforms. Since we have 20 yearly datasets associated with 35,974 unique Android apps across the 10 years, profiling these apps took 12,000 hours. Considering the costs of filtering out apps that were originally sampled but that we were unable to profile (due to various reasons such as broken APKs, not being executable because of incompatibility issues, not instrumentable, etc.), we took over two years to produce all these traces. We hope to save future researchers' time in producing such a set of dynamic data to enable their empirical and technical work. ================== Thanks for your interest in our dataset. Collecting this dataset took tremendous computational and human effort. Thus, please observe the following restrictions in using our dataset: - Do not redistribute this dataset without our consent.<br> - Do not make commercial usage of this dataset.<br> - Get a faculty, or someone in a permanent position, to agree and commit to these conditions.<br> - When publishing your work that uses our dataset, please cite the following MSR 2021 data paper. <br> @inproceedings{AndroidCT,<br> title = {AndroCT: Ten Years of App Call Traces in Android},<br> author = {Wen Li, Xiaoqin Fu, and Haipeng Cai},<br> booktitle = {The 18th International Conference on Mining Software Repositories (MSR 2021), Data Showcase Track},<br> year = {2021},<br> }
DOI: 10.5281/zenodo.5748597
title: Compound activity data sets for 15 biological targets compiled from the ChEMBL and PubChem databases.

description: Compound activity data sets for the 15 biological targets are deposited, along with structure-activity relationship matrices IDs. Active compounds were extracted from the ChEMBL database and inactive were from the PubChem database. Details of the data sets are described in the original publication. and the summary of the data sets is given in the readme.txt file.
DOI: 10.5281/zenodo.5748596
title: Compound activity data sets for 15 biological targets compiled from the ChEMBL and PubChem databases.

description: Compound activity data sets for the 15 biological targets are deposited, along with structure-activity relationship matrices IDs. Active compounds were extracted from the ChEMBL database and inactive were from the PubChem database. Details of the data sets are described in the original publication. and the summary of the data sets is given in the readme.txt file.
DOI: 10.6084/m9.figshare.19303271
title: Microginin 789 NMR data

description: 1D and 2D NMR data of Microginin 789: 1H,13C, HSQC, HMBC and COSY
DOI: 10.6084/m9.figshare.19303271.v1
title: Microginin 789 NMR data

description: 1D and 2D NMR data of Microginin 789: 1H,13C, HSQC, HMBC and COSY
DOI: 10.21223/ohuheq/yy6hh1
title: 04-Datos-herramientas-de-uso-en-la-agricultura.tab

description: :unav
DOI: 10.13140/rg.2.2.27873.38242
title: Türkiye'de Katma Değer Vergisi ve Özel Tüketim Vergisinin Enflasyon Üzerindeki Etkisi.pdf
DOI: 10.6073/pasta/4c6a5c2382bf376c8872560fc32be14e
title: Water Quality Data (Grab Samples) from the Shark River Slough, Everglades National Park (FCE LTER), May 2001 - ongoing

description: Water quality samples are being collected using ISCO autosamplers at all wetland sites (that is, all sites except TS/Ph-9, 10, and 11). The autosamplers contain 24 1L bottles. Water is sampled by programming the autosamplers to take composite samples once every 3 days. These samples are a composite of four 250mL subsamples drawn every 18 hours (a sampling scheme that captures a dawn, noon, dusk, and midnight sample in every three day composite). The samples are collected every 3-4 weeks and analyzed for total phosphorus (TP), total nitrogen (TN), and salinity. When sites are visited to collect these samples, we also collect a grab sample that is immediately put on ice. A portion of these grab samples is filtered through a Whatman GF/F filter immediately upon return to the lab, and the filtered samples are analyzed for inorganic nutrients such as NO2-, NO3-, NH4+, SRP, and DOC. The unfiltered fraction of these grab samples is analyzed for TP and TN. We use these monthly grab samples to generate relationships between TP and SRP, and between TN and NO2- + NO3- + NH4+. Dissolved nutrients are measured using standard rapid flow analyzer (RFA) techniques. TP is analyzed with a modified Solorzano and Sharp (1980) technique. TN is measured with an ANTEK 9000N analyzer, TOC and DOC are quantified on a Shimadzu TOC Analyzer, and salinity is measured with a YSI conductivity meter. In January 2007 a 6 days interval began for SRS1d, SRS2 & SRS3; the ISCOs did not change their sampling scheduled, they kept collecting water sample every 18 hours and switching bottles every three days; once in the lab, the 3 days was turned into 6 days by combining two bottles into 2 liters container. In addition to the regular water quality monitoring, we use the rain level actuators at all freshwater sites to trigger water sampling after rain events exceed a given threshold of duration and/or intensity. As currently programmed, when the threshold of = 2.5 cm of rain per hour is passed, the autosampler at that site collects a 1000mL sample 30 minutes after the threshold has been reached. Rain event samples are collected, treated, and analyzed as all other water quality samples.
DOI: 10.5281/zenodo.6336062
title: Tyrannus tyrannus decontaminated FSCR

description: .