cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4287190
title: finals_2020_11_339

description: Log and boot files of game 339
DOI: 10.5281/zenodo.4287189
title: finals_2020_11_339

description: Log and boot files of game 339
DOI: 10.5281/zenodo.4287194
title: finals_2020_11_340

description: Log and boot files of game 340
DOI: 10.5281/zenodo.4287193
title: finals_2020_11_340

description: Log and boot files of game 340
DOI: 10.5281/zenodo.4287196
title: finals_2020_11_341

description: Log and boot files of game 341
DOI: 10.5281/zenodo.4287195
title: finals_2020_11_341

description: Log and boot files of game 341
DOI: 10.5281/zenodo.4287198
title: finals_2020_11_342

description: Log and boot files of game 342
DOI: 10.5281/zenodo.4287197
title: finals_2020_11_342

description: Log and boot files of game 342
DOI: 10.5281/zenodo.4287200
title: finals_2020_11_343

description: Log and boot files of game 343
DOI: 10.5281/zenodo.4287199
title: finals_2020_11_343

description: Log and boot files of game 343
DOI: 10.5281/zenodo.4287204
title: finals_2020_11_344

description: Log and boot files of game 344
DOI: 10.5281/zenodo.4287203
title: finals_2020_11_344

description: Log and boot files of game 344
DOI: 10.5281/zenodo.4287206
title: finals_2020_11_345

description: Log and boot files of game 345
DOI: 10.5281/zenodo.4287205
title: finals_2020_11_345

description: Log and boot files of game 345
DOI: 10.5281/zenodo.4287208
title: finals_2020_11_346

description: Log and boot files of game 346
DOI: 10.5281/zenodo.4287207
title: finals_2020_11_346

description: Log and boot files of game 346
DOI: 10.5281/zenodo.4287210
title: finals_2020_11_347

description: Log and boot files of game 347
DOI: 10.5281/zenodo.4287212
title: finals_2020_11_348

description: Log and boot files of game 348
DOI: 10.5281/zenodo.4287209
title: finals_2020_11_347

description: Log and boot files of game 347
DOI: 10.5281/zenodo.4287211
title: finals_2020_11_348

description: Log and boot files of game 348
DOI: 10.5281/zenodo.4287214
title: finals_2020_11_349

description: Log and boot files of game 349
DOI: 10.5281/zenodo.4287216
title: finals_2020_11_350

description: Log and boot files of game 350
DOI: 10.5281/zenodo.4287213
title: finals_2020_11_349

description: Log and boot files of game 349
DOI: 10.5281/zenodo.4287215
title: finals_2020_11_350

description: Log and boot files of game 350
DOI: 10.5281/zenodo.4287219
title: finals_2020_11_351

description: Log and boot files of game 351
DOI: 10.5281/zenodo.4287218
title: finals_2020_11_351

description: Log and boot files of game 351
DOI: 10.5281/zenodo.4287221
title: finals_2020_11_352

description: Log and boot files of game 352
DOI: 10.5281/zenodo.4287220
title: finals_2020_11_352

description: Log and boot files of game 352
DOI: 10.5281/zenodo.4287224
title: finals_2020_11_353

description: Log and boot files of game 353
DOI: 10.5281/zenodo.4287223
title: finals_2020_11_353

description: Log and boot files of game 353
DOI: 10.5281/zenodo.4287226
title: finals_2020_11_354

description: Log and boot files of game 354
DOI: 10.5281/zenodo.4287225
title: finals_2020_11_354

description: Log and boot files of game 354
DOI: 10.5281/zenodo.4287230
title: finals_2020_11_355

description: Log and boot files of game 355
DOI: 10.5281/zenodo.4287229
title: finals_2020_11_355

description: Log and boot files of game 355
DOI: 10.5281/zenodo.4287233
title: finals_2020_11_356

description: Log and boot files of game 356
DOI: 10.5281/zenodo.4287232
title: finals_2020_11_356

description: Log and boot files of game 356
DOI: 10.5281/zenodo.4287236
title: finals_2020_11_357

description: Log and boot files of game 357
DOI: 10.5281/zenodo.4287235
title: finals_2020_11_357

description: Log and boot files of game 357
DOI: 10.5281/zenodo.4287238
title: finals_2020_11_358

description: Log and boot files of game 358
DOI: 10.5281/zenodo.4287237
title: finals_2020_11_358

description: Log and boot files of game 358
DOI: 10.5281/zenodo.4287240
title: finals_2020_11_359

description: Log and boot files of game 359
DOI: 10.5281/zenodo.4287239
title: finals_2020_11_359

description: Log and boot files of game 359
DOI: 10.5281/zenodo.4287242
title: finals_2020_11_360

description: Log and boot files of game 360
DOI: 10.5281/zenodo.4287241
title: finals_2020_11_360

description: Log and boot files of game 360
DOI: 10.5281/zenodo.4287248
title: finals_2020_11_361

description: Log and boot files of game 361
DOI: 10.5281/zenodo.4287247
title: finals_2020_11_361

description: Log and boot files of game 361
DOI: 10.5281/zenodo.4287252
title: finals_2020_11_362

description: Log and boot files of game 362
DOI: 10.5281/zenodo.4287251
title: finals_2020_11_362

description: Log and boot files of game 362
DOI: 10.5281/zenodo.4287254
title: finals_2020_11_363

description: Log and boot files of game 363
DOI: 10.5281/zenodo.4287253
title: finals_2020_11_363

description: Log and boot files of game 363
DOI: 10.5281/zenodo.4287256
title: finals_2020_11_364

description: Log and boot files of game 364
DOI: 10.5281/zenodo.4287255
title: finals_2020_11_364

description: Log and boot files of game 364
DOI: 10.5281/zenodo.4287258
title: finals_2020_11_365

description: Log and boot files of game 365
DOI: 10.5281/zenodo.4287257
title: finals_2020_11_365

description: Log and boot files of game 365
DOI: 10.5281/zenodo.4287260
title: finals_2020_11_366

description: Log and boot files of game 366
DOI: 10.5281/zenodo.4287259
title: finals_2020_11_366

description: Log and boot files of game 366
DOI: 10.5281/zenodo.4287266
title: finals_2020_11_367

description: Log and boot files of game 367
DOI: 10.5281/zenodo.4287265
title: finals_2020_11_367

description: Log and boot files of game 367
DOI: 10.5281/zenodo.4287268
title: finals_2020_11_368

description: Log and boot files of game 368
DOI: 10.5281/zenodo.4287267
title: finals_2020_11_368

description: Log and boot files of game 368
DOI: 10.5281/zenodo.4287270
title: finals_2020_11_369

description: Log and boot files of game 369
DOI: 10.5281/zenodo.4287273
title: finals_2020_11_370

description: Log and boot files of game 370
DOI: 10.5281/zenodo.4050338
title: Dataset for the manuscript "Barium stable isotopes as a fingerprint of biological cycling in the Amazon River Basin" published in Biogeosciences

description: This file contains the dataset of the manuscript accepted for publication in Biogeosciences entitled "Barium stable isotopes as a fingerprint of biological cycling in the Amazon River Basin" by Charbonnier et al. It consists in three spreadsheets: (1) dissolved species concentration and dissolved Ba isotope data on river dissolved load; (2) main characteristics and Ba isotope data of river sediments; (3) compilation of major element and Ba and Li concentration in rocks (compilation made from the GEOROC database) and in the dissolved load of river draining single rock types (compilation made from previously published data and new data).
DOI: 10.5281/zenodo.4287269
title: finals_2020_11_369

description: Log and boot files of game 369
DOI: 10.5281/zenodo.4287272
title: finals_2020_11_370

description: Log and boot files of game 370
DOI: 10.5281/zenodo.4287275
title: finals_2020_11_371

description: Log and boot files of game 371
DOI: 10.5281/zenodo.4287274
title: finals_2020_11_371

description: Log and boot files of game 371
DOI: 10.5281/zenodo.4287279
title: finals_2020_11_372

description: Log and boot files of game 372
DOI: 10.5281/zenodo.4287278
title: finals_2020_11_372

description: Log and boot files of game 372
DOI: 10.5281/zenodo.4287281
title: finals_2020_11_373

description: Log and boot files of game 373
DOI: 10.5281/zenodo.4287280
title: finals_2020_11_373

description: Log and boot files of game 373
DOI: 10.5281/zenodo.4287283
title: finals_2020_11_374

description: Log and boot files of game 374
DOI: 10.5281/zenodo.4287282
title: finals_2020_11_374

description: Log and boot files of game 374
DOI: 10.5281/zenodo.4287285
title: finals_2020_11_375

description: Log and boot files of game 375
DOI: 10.5281/zenodo.4287284
title: finals_2020_11_375

description: Log and boot files of game 375
DOI: 10.5281/zenodo.4287287
title: finals_2020_11_376

description: Log and boot files of game 376
DOI: 10.5281/zenodo.4287286
title: finals_2020_11_376

description: Log and boot files of game 376
DOI: 10.4119/unibi/2946315
title: Interrogations of runway convicts

description: Data concerning escapes from the prison known as Slaveriet in eighteenth-century Copenhagen.
DOI: 10.4119/unibi/2948488
title: Voluntary Work or Coerced Labour? Albania between 1945 and the 1990s
DOI: 10.4119/unibi/2948491
title: Slavery and Resistance in the US South
DOI: 10.4119/unibi/2948482
title: Prosecution of a murderous female slave, Mukden (Quing China), 1796
DOI: 10.5281/zenodo.4287374
title: FT44 Scherer (3) 4 key fagottino: measurements, photos, endoscopic video

description: Dataset of FT44 Scherer (3) 4-key fagottino containing detailed external and internal measurements, photos, and an endoscopic video.
DOI: 10.5281/zenodo.3246271
title: FT44 Scherer (3) 4 key fagottino: measurements, photos, endoscopic video

description: Dataset of FT44 Scherer (3) 4-key fagottino containing detailed external and internal measurements, photos, and an endoscopic video.
DOI: 10.4119/unibi/2948484
title: Interrogation of a runaway convict, Copenhagen 1776
DOI: 10.21227/j0p3-cv63
title: AI Ethics Global Document Collection

description: AI Ethics Global Document Collection
DOI: 10.21227/43z0-d106
title: AI Ethics Global Document Collection

description: AI Ethics Global Document Collection
DOI: 10.21227/fcdb-pa48
title: AI Ethics Global Document Collection

description: AI Ethics Global Document Collection
DOI: 10.21227/a187-1021
title: AI Ethics Global Document Collection

description: AI Ethics Global Document Collection
DOI: 10.34740/kaggle/dsv/1674874
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.12121389
title: o_covid-19.json

description: Facts that was used to synthesize COVID-19 pathogenesis
DOI: 10.6084/m9.figshare.12121389.v2
title: o_covid-19.json

description: Facts that was used to synthesize COVID-19 pathogenesis
DOI: 10.5281/zenodo.4264652
title: SOTorrent Dataset

description: Stack Overflow (SO) is the most popular question-and-answer website for software developers, providing a large amount of code snippets and free-form text on a wide variety of topics. Like other software artifacts, questions and answers on SO evolve over time, for example when bugs in code snippets are fixed, code is updated to work with a more recent library version, or text surrounding a code snippet is edited for clarity. To be able to analyze how content on SO evolves, we built <em>SOTorrent</em>, an open dataset based on the official SO data dump. <em>SOTorrent </em>provides access to the version history of SO content at the level of whole posts and individual text or code blocks. It connects SO posts to other platforms by aggregating URLs from text blocks and comments, and by collecting references from GitHub files to SO posts. Our vision is that researchers will use <em>SOTorrent </em>to investigate and understand the evolution of SO posts and their relation to other platforms such as GitHub. <strong>If you use this dataset in your work, please cite our MSR 2018 paper (BibTex) or our MSR 2019 mining challenge proposal.</strong>
description: The dataset is based on the official Stack Overflow data dump released 2020-06-02 (https://archive.org/details/stackexchange) and the Google BigQuery GitHub data set queried 2020-11-02 and last updated 2020-10-29 according to table info (https://cloud.google.com/bigquery/public-data/github). Please read the license files (LICENSE.md) before using the dataset.
DOI: 10.6084/m9.figshare.12752792
title: WhiteMatterMultisiteProfiles.json

description: See collection description. Nested json.
DOI: 10.6084/m9.figshare.12752828
title: WhiteMatterMultisiteProfiles.mat

description: See collection description. Matlab nested table format.
DOI: 10.6084/m9.figshare.12752792.v1
title: WhiteMatterMultisiteProfiles.json

description: See collection description. Nested json.
DOI: 10.6084/m9.figshare.12752828.v1
title: WhiteMatterMultisiteProfiles.mat

description: See collection description. Matlab nested table format.
DOI: 10.13012/b2idb-6482573_v1
title: Global warming effects on nesting in Prothonotary Warblers

description: Dataset includes temperature data (local average April daily temperatures), first egg dates and reproductive output of Prothonotary Warblers breeding in southernmost Illinois, USA. Also included are arrival dates for warblers returning to breeding grounds from wintering grounds, and global temperature anomaly data for comparison with local temperatures. These data were used in the manuscript entitled "Warmer April Temperatures on Breeding Grounds Promote Earlier Nesting in a Long-Distance Migratory Bird, the Prothonotary Warbler" published in Frontiers in Ecology and Evolution. A rich text file is included with explanations of each variable in the dataset.
DOI: 10.23708/cglfil
title: Informal waste collectors and aggregators space and activities in Da Nang city, Vietnam, COMPOSE project (2019-2021)

description: The system of informal waste collectors and aggregators in Da Nang city (Vietnam) was surveyed in the framework of the COMPOSE project (2019-2021). The social survey based on questionnaire was carried out in the entire area of Da Nang city to identify the location of the aggregator warehouse participating to the informal waste collection and recycling in the city. Then, the collectors and aggregators were interviewed to collect information on the space, architectural characteristic of the warehouse, the neighborhood, the hours of operation, the type of materials collected and on the owners of the warehouse (hometown, the reasons for choosing the job). The surveys were conducted in August 2019 and June 2020. Data anonymization was performed by removing identifiers, generalization (grouping precise values into less precise/larger categories) and finally by aggregating individual records, producing descriptive statistics (frequencies).
DOI: 10.6084/m9.figshare.13275020
title: Oxfordshire Klebsiella pneumoniae bloodstream isolates; Kleborate output

description: Output from Kleborate of 556 invasive K. pneumoniae isolates
DOI: 10.6084/m9.figshare.13275020.v1
title: Oxfordshire Klebsiella pneumoniae bloodstream isolates; Kleborate output

description: Output from Kleborate of 556 invasive K. pneumoniae isolates
DOI: 10.5281/zenodo.4287425
title: Italy landslide dataset for semantic segmentation

description: This database contains images used for the semantic segmentation of landslide scars from a fully convolutional neural network U-Net. The .rar file contains 3 folders: <strong>Image: </strong>104 GeoTIFF 8 bits images of locations with landslide scars. <strong>Masks: </strong>104 PNG masks (scars indicated in white and background in black color). <strong>Slope: </strong>104 GeoTIFF float rasters of slope (in degrees). Also, the "SHAPEFILES_LANDSLIDES.rar" file contains the vector layers of the masked images in .shp format.
DOI: 10.5281/zenodo.4287424
title: Italy landslide dataset for semantic segmentation

description: This database contains images used for the semantic segmentation of landslide scars from a fully convolutional neural network U-Net. The .rar file contains 3 folders: <strong>Image: </strong>104 GeoTIFF 8 bits images of locations with landslide scars. <strong>Masks: </strong>104 PNG masks (scars indicated in white and background in black color). <strong>Slope: </strong>104 GeoTIFF float rasters of slope (in degrees). Also, the "SHAPEFILES_LANDSLIDES.rar" file contains the vector layers of the masked images in .shp format.
DOI: 10.5281/zenodo.4287419
title: New Zealand landslide dataset for semantic segmentation

description: This database contains images used for the semantic segmentation of landslide scars from a fully convolutional neural network U-Net. The .rar file contains 3 folders: <strong>Image: </strong> 51 GeoTIFF 8 bits images of locations with landslide scars. <strong>Masks: </strong>51 PNG masks (scars indicated in white and background in black color). <strong>Slope: </strong>51 GeoTIFF float rasters of slope (in degrees). Also, the "SHAPEFILES_LANDSLIDES.rar" file contains the vector layers of the masked images in .shp format.
DOI: 10.5281/zenodo.4287418
title: New Zealand landslide dataset for semantic segmentation

description: This database contains images used for the semantic segmentation of landslide scars from a fully convolutional neural network U-Net. The .rar file contains 3 folders: <strong>Image: </strong> 51 GeoTIFF 8 bits images of locations with landslide scars. <strong>Masks: </strong>51 PNG masks (scars indicated in white and background in black color). <strong>Slope: </strong>51 GeoTIFF float rasters of slope (in degrees). Also, the "SHAPEFILES_LANDSLIDES.rar" file contains the vector layers of the masked images in .shp format.
DOI: 10.6084/m9.figshare.13275038
title: Oxforshire E. coli bloodstream infection isolates

description: MLST output from 3479 invasive E. coli isolates from Oxfordshire to support the paper Ten years of population-level genomic Escherichia coli and Klebsiella pneumoniae serotype surveillance informs vaccine development for invasive infections https://doi.org/10.1101/2020.07.08.20140707
DOI: 10.6084/m9.figshare.13275011
title: EFFECT OF CULTURAL PRACTICES ON PHYTOPHTHORA FOOT ROT DISEASE IN THE RAINFOREST AREAS OF CAMEROON.xlsx

description: This dataset was used to demonstrate the effect of agronomic and environmental parameters on the intensity of Citrus diease caused by Phytophthora on citrus fruits and in 5 production systems in Cameroon. <br>The choice of species, replacement of ageing trees, prevention of other diseases and pests; and the right balance of production systems can contribute to an PFRD integrated management<br>
DOI: 10.6084/m9.figshare.13275011.v1
title: EFFECT OF CULTURAL PRACTICES ON PHYTOPHTHORA FOOT ROT DISEASE IN THE RAINFOREST AREAS OF CAMEROON.xlsx

description: This dataset was used to demonstrate the effect of agronomic and environmental parameters on the intensity of Citrus diease caused by Phytophthora on citrus fruits and in 5 production systems in Cameroon. <br>The choice of species, replacement of ageing trees, prevention of other diseases and pests; and the right balance of production systems can contribute to an PFRD integrated management<br>
DOI: 10.17632/9v97fbvdh7.1
title: Data for: Energy price reform in Saudi Arabia: Modeling the economic and environmental impacts and understanding the demand response

description: Electricity and gasoline demand models data
DOI: 10.5281/zenodo.4287430
title: NDVI and land cover percentages in the Canton of Geneva

description: Polygon shapefiles containing information relative to the green areas density as NDVI and land cover in two different buffers of 100 m and 500 m around points in the Canton of Geneva. The information about the green areas were taken from a 10 m resolution Landsat-2 image and from the OTEMO Land Cover vector file of the Canton of Geneva.
DOI: 10.5281/zenodo.4287429
title: NDVI and land cover percentages in the Canton of Geneva

description: Polygon shapefiles containing information relative to the green areas density as NDVI and land cover in two different buffers of 100 m and 500 m around points in the Canton of Geneva. The information about the green areas were taken from a 10 m resolution Landsat-2 image and from the OTEMO Land Cover vector file of the Canton of Geneva.
DOI: 10.21227/v5fk-w840
title: z kVA Solar C

description: This dataset is related to a planned paper to be submitted to IEEE Transaction Journal.
DOI: 10.34740/kaggle/dsv/1674959
title: COVID-19 cases by Continent
DOI: 10.5281/zenodo.4285945
title: Data

description: Data
DOI: 10.5281/zenodo.4285944
title: Data

description: Data
DOI: 10.5281/zenodo.4285807
title: Supplementary data to: "Antenna signals generated by dust impacts on spacecraft"

description: Supplementary data to: "Antenna signals generated by dust impacts on spacecraft"
DOI: 10.6084/m9.figshare.10315784.v1
title: Earth Analytics Bootcamp | Final Project Dataset | Precipitation Data for Boulder, CO and San Francisco, CA for 1948 to 2018

description: This dataset contains:<br>1. boulder-monthly-precip-mm-1948-2018.csv: total monthly precipitation (millimeters) for each month and year for Boulder, CO between 1948 and 2018. The data are organized with a row for each for each year (in order from 1948 to 2018) and one column for month (in order from January to December). This file does not contain headers.<br> Original data from U.S. National Oceanic and Atmospheric Administration (NOAA): https://www.esrl.noaa.gov/psd/boulder/Boulder.mm.precip.html<br><br>2. san-franscisco-monthly-precip-mm-1948-2018.csv: total monthly precipitation (millimeters) for each month and year for San Francisco, CA between 1948 and 2018. <br>The data are organized with a row for each for each year (in order from 1948 to 2018) and one column for month (in order from January to December). This file does not contain headers. <br>Original data from the National Weather Service: https://w2.weather.gov/climate/xmacis.php?wfo=mtr
DOI: 10.5281/zenodo.4285806
title: Supplementary data to: "Antenna signals generated by dust impacts on spacecraft"

description: Supplementary data to: "Antenna signals generated by dust impacts on spacecraft"
DOI: 10.6084/m9.figshare.13275032
title: VCF SNPs 120Genomes miRNAs

description: Whole Genome Sequencing dataset (VCF) from 120 European and Asian domestic pigs and wild boars. SNPs mapping to miRNA loci.
DOI: 10.6084/m9.figshare.13275032.v1
title: VCF SNPs 120Genomes miRNAs

description: Whole Genome Sequencing dataset (VCF) from 120 European and Asian domestic pigs and wild boars. SNPs mapping to miRNA loci.
DOI: 10.6084/m9.figshare.5573647.v2
title: Template to provide grant data

description: Template to provide grant data to Europe PMC, notes on second sheet.
DOI: 10.21227/3tyc-y227
title: Recognition of common postures in lambs (ICV-TxLamb)

description: Computer vision in animal monitoring has become a research application in stable or confined conditions.Detecting animals from the top view is challenging due to barn conditions.In this dataset called ICV-TxLamb, images are proposed for the monitoring of lamb inside a barn.This set of data is made up of two categories, the first is lamb (classifies the only lamb), the second consists of four states of the posture of lambs, these are: eating, sleeping, lying down, and normal (standing or without activity ).The added tags have been considered by the natural movements that the lamb makes in the observed scene.
DOI: 10.21227/8e8n-nt68
title: Recognition of common postures in lambs (ICV-TxLamb)

description: Computer vision in animal monitoring has become a research application in stable or confined conditions.Detecting animals from the top view is challenging due to barn conditions.In this dataset called ICV-TxLamb, images are proposed for the monitoring of lamb inside a barn.This set of data is made up of two categories, the first is lamb (classifies the only lamb), the second consists of four states of the posture of lambs, these are: eating, sleeping, lying down, and normal (standing or without activity ).The added tags have been considered by the natural movements that the lamb makes in the observed scene.
DOI: 10.21227/j5ft-be78
title: Recognition of common postures in lambs (ICV-TxLamb)

description: Computer vision in animal monitoring has become a research application in stable or confined conditions.Detecting animals from the top view is challenging due to barn conditions.In this dataset called ICV-TxLamb, images are proposed for the monitoring of lamb inside a barn.This set of data is made up of two categories, the first is lamb (classifies the only lamb), the second consists of four states of the posture of lambs, these are: eating, sleeping, lying down, and normal (standing or without activity ).The added tags have been considered by the natural movements that the lamb makes in the observed scene.