cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4559368
title: SIMBA snow/ice mass balance buoy data and weather station data

description: The data sets here are for a manuscript entitled as "<strong>Inter-annual variation of lake ice composition in the Arctic region: Results from observed high-resolution thermistor string"</strong> The high spatial resolution (2cm) vertical air-snow-ice-water temperature time series have been measured in an Arctic lake during winter seasons 2009-2020. Snow depth, ice thickness as well as the lake ice composition are retrieved from temperature time series. High quality meteorological parameters are available from Sodankylä weather station in the vicinity (12 km) from the lake. The readers may considered to create a few <strong>sub-directories</strong> to save the packed files: <strong>SIMBA_rawdata</strong>\ You can save SIMBA_rawdata.zip here and if you unzip, you will find a number of SIMBA original data files, see readme for details. <strong>SIMBA_rawdata1</strong>\ You can save SIMBA_rawdata1.zip here and if you unzip, you will find a number of SIMBA combined data files, see readme for details. <strong>SIMBA_RESULT</strong>\You can save SIMBA_RESULT.zip here and if you unzip, you will find a number of SIMBA processed data files, see readme for details. <strong>Weather_station_data</strong>\You can save Weather_station_data.zip here and if you unzip, you will find a number of weather station data files, see readme for details. <strong>SIMBA_D&R_all_Years.docx</strong>: This file describes SIMBA deployment for each winter season. There are a few excel file here. Those are lake snow and ice manual observation for 09/10, 10/11, 11/12 and 12/13
DOI: 10.5281/zenodo.4628550
title: Time series of seafloor displacement at GNSS-A sites along the Japan Trench: from March 2011 to June 2020 and before the 2011 Tohoku-oki earthquake

description: <em>DataS1.xlsx</em> contains time series of postseismic seafloor displacements following the 2011 Tohoku-oki earthquake at GNSS-A sites along the Japan Trench with respect to the Eurasian plate of NUVEL-1A model (DeMets et al., 1994), which are derived from the GNSS-A data (Watanabe et al., 2021b) using GARPOS version 1.0.0 (Watanabe et al., 2021c). <em>DataS2.xlsx</em> contains time series of preseismic seafloor displacements before the 2011 Tohoku-oki earthquake at GNSS-A sites along the Japan Trench with respect to the Eurasian plate of NUVEL-1A model (DeMets et al., 1994), which are derived from the GNSS-A data (Watanabe et al., 2021a) using GARPOS version 1.0.0 (Watanabe et al., 2021c). The reference locations of GNSS-A sites are listed in <em>DataS3.xlsx</em>. Note that the precise positions of seafloor acoustic transponders can be available from the GNSS-A dataset (Watanabe et al., 2021a; 2021b).
description: {"references": ["DeMets, C., Gordon, R. G., Argus, D. F., & Stein, S. (1994). Effect of recent revisions to the geomagnetic reversal time scale on estimates of current plate motions. Geophys. Res. Lett., 21, 2191\u20132194. doi:10.1029/94GL02118", "Watanabe, S., Ishikawa, T., Nakamura, Y., & Yokota, Y. (2021a). GNSS-A data obtained at the sites along the Japan Trench before the 2011 Tohoku-oki earthquake (Version 1.0.0). Zenodo, doi:10.5281/zenodo.4528990", "Watanabe, S., Ishikawa, T., Nakamura, Y., & Yokota, Y. (2021b). GNSS-A data obtained at the sites along the Japan Trench from March 2011 to June 2020 (Version 1.0.0). Zenodo, doi:10.5281/zenodo.4529008", "Watanabe, S., Ishikawa, T., Yokota, Y., & Nakamura, Y. (2021c). GARPOS: Analysis tool for GNSS-Acoustic seafloor positioning (Version 1.0.0). Zenodo. doi:10.5281/zenodo.4522027"]}
DOI: 10.5281/zenodo.4762779
title: Dataset for four data assimilation studies with MIDA v1.0

description: Archived datasets for the manuscript “<strong>A Model-Independent Data Assimilation (MIDA) module and its applications in ecology</strong>” submitted in Geoscientific Model Development journal.
DOI: 10.5517/ccdc.csd.cc2cn7s2
title: CCDC 2194204: Experimental Crystal Structure Determination

description: Related Article: Anthony Linden, Alberto Herrera, Romano Dorta|2022|CSD Communication|||
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: 10.6084/m9.figshare.11948619
title: Artifacts for MAESTRO: A Tool for Recommending Stack Overflow Posts for Fixing Runtime Exceptions

description: Artifact package for the paper "<i><b>Recommending Stack Overflow Posts for Fixing Runtime Exceptions using Failure Scenario Matching</b></i>". To appear at the 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2020), November 8-13, 2020, Sacramento, CA, USA.
DOI: 10.7910/dvn/8yvinu
title: MedRed

description: A social media dataset of Reddit posts from health communities with medical entities of two types tagged: symptom and drug names.
DOI: 10.17632/k2xg2s7cg6.1
title: Data for "Neighbourhood dissimilarity consistently attenuates competition stress on tree growth under altered water availability in a natural boreal forest"

description: StandType: three stand types: broadleaf, conifer and their mixtures.
Site: Site No.
Water: water treatments: water addition (A), reduction (R) and ambient control (C).
Spe: species names of tree individuals.
x: x-coordinates of tree individuals
y: y-coordinates of tree individuals.
BAI_1720: Basal area increment between the two measurements in 2017 and 2020.
Hegyi: Neighbourhood Hegyi index.
DroughtD: Neighbourhood drought tolerance dissimilarity.
PhyloD: Neighbourhood phylogenetic dissimilarity.
DOI: 10.6084/m9.figshare.21836403.v1
title: Greenland and Antarctic Ice Sheets Surface Melt Product derived from FY-3 MWRI (2012-2020)

description: Two ice sheets (Greenland Ice Sheet & Antarctic Ice Sheet) surface melt states derived from the Chinese FY-3 MWRI brightness temperature dataset from 2012 to 2020.
DOI: 10.6084/m9.figshare.21836403.v2
title: Greenland and Antarctic Ice Sheets Surface Melt Product derived from FY-3 MWRI (2012-2020)

description: Two ice sheets (Greenland Ice Sheet & Antarctic Ice Sheet) surface melt states derived from the Chinese FY-3 MWRI brightness temperature dataset from 2012 to 2020.
DOI: 10.5281/zenodo.7513426
title: Data for figures in the global streamflow change paper

description: This is the dataset used for generating figures 1-4 in the manuscript of "<strong>Future global streamflow declines likely more severe than previously estimated</strong>"
DOI: 10.5281/zenodo.7393339
title: Witchcraft trials in the Czech lands: Data on persons, places, charges, punishments, and material substances

description: This is the most comprehensive digital dataset of witchcraft trials in the Czech lands since the earliest case in 1491 until as late as 1785. The dataset covers 257 cases. It records the year, the suspects' names, their sex, places of residence (including geographic coordinates), charges, results of the trial, places of interrogation (including geographic coordinates), and the material substances they were charged of using to perform magic. The dataset allows researchers to conduct systematic and quantitative research into early modern withcraft trials, crime and punishment, as well as the imagery of magic and evil-doing. It also allows to include the Czech lands in broader quantitative studies of European witchcraft trials on a large temporal and geographic scale. Five B.A. theses have been written at Masaryk University, Brno, Czech Republic on the basis of this dataset. The dataset does not cover all known trials. Based on data availability, we did our best to cover what was published and reasonably accessible, but we did not perform original archival research. Our very rough estimate is that up to 100 further specific witchcraft trials in the Czech lands could be identified in published material, and archival work could reveal further ca. 250-800 cases.
DOI: 10.5281/zenodo.7393338
title: Witchcraft trials in the Czech lands: Data on persons, places, charges, punishments, and material substances

description: This is the most comprehensive digital dataset of witchcraft trials in the Czech lands since the earliest case in 1491 until as late as 1785. The dataset covers 257 cases. It records the year, the suspects' names, their sex, places of residence (including geographic coordinates), charges, results of the trial, places of interrogation (including geographic coordinates), and the material substances they were charged of using to perform magic. The dataset allows researchers to conduct systematic and quantitative research into early modern withcraft trials, crime and punishment, as well as the imagery of magic and evil-doing. It also allows to include the Czech lands in broader quantitative studies of European witchcraft trials on a large temporal and geographic scale. Five B.A. theses have been written at Masaryk University, Brno, Czech Republic on the basis of this dataset. The dataset does not cover all known trials. Based on data availability, we did our best to cover what was published and reasonably accessible, but we did not perform original archival research. Our very rough estimate is that up to 100 further specific witchcraft trials in the Czech lands could be identified in published material, and archival work could reveal further ca. 250-800 cases.
DOI: 10.5281/zenodo.7513532
title: Global Monthly Gross Primary Production

description: This is global monthly gross primary production from 2001-2016 derived from P model using pyrealm python package. Unit for GPP is gC/m2 day (monthly daily mean value). Detailed description of data can be found in Shen et al. 2023. For detailed description of P model please refer to Wang et al. 2017, Cai and Prentice 2020 and Stocker et al. 2020.
DOI: 10.6084/m9.figshare.21836442
title: covid effects on mensruation

description: dataset for manuscript
DOI: 10.6084/m9.figshare.21836442.v1
title: covid effects on mensruation

description: dataset for manuscript
DOI: 10.21227/85ra-py52
title: Intelligent 5G networks for BLOS UAV networking

description: Although Unmanned Aerial Vehicles (UAVs) have long been recognized as systems to effectively deliver advanced and innovative services, their practical application to Beyond Line-of-Sight (BLOS) use cases is still largely missing due to safety concerns and regulations. Indeed, BLOS applications for UAVs require a reliable infrastructure that is capable of ensuring ubiquitous connectivity, low latency, and high data rates. Despite 5G networks promising to satisfy those requirements, they are not exclusively serving UAVs, but a variety of users and sub-systems that despite sharing the same radio resources (e.g., spectrum) might have opposing demand requirements. How to achieve such coexistence is still unclear, which makes 5G networks for BLOS UAV applications still unreliable.
The goal of this project is to advance 5G technologies for BLOS UAV applications by designing and developing O-BLUE, a framework that combines AI, Open RAN architectures and edge computing to enable and support BLOS UAV applications over 5G networks.
In O-BLUE, UAVs are connected to Ground Control Stations (GCS) via the 5G infrastructure. Moreover, by building on top of the Open RAN architecture proposed by the O-RAN Alliance, O-BLUE leverages Radio Access Network (RAN) Intelligent Controllers (RICs) and AI to adapt 5G network functionalities and parameters according to UAV mobility patterns and changing traffic and channel conditions, so as to ensure stable and low-latency communications between UAVs and GCS.
Our goal is to design, implement and experimentally validate O-BLUE by leveraging the variety of experimental platforms that our team has access to, and eventually disseminate our findings to the community and make publicly available datasets and open-source components developed within the context of this project.
DOI: 10.6084/m9.figshare.20552073
title: Molecular Docking and Dynamic Study of Ethanol Extract of Citrus sinensis as Keap-1 and NMDA inhibitor in Brain Injury

description: This raw data result from extract ethanol Citrus sinensis analysis compound
DOI: 10.6084/m9.figshare.20552073.v2
title: Molecular Docking and Dynamic Study of Ethanol Extract of Citrus sinensis as Keap-1 and NMDA inhibitor in Brain Injury

description: This raw data result from extract ethanol Citrus sinensis analysis compound
DOI: 10.6084/m9.figshare.20552073.v1
title: Molecular Docking and Dynamic Study of Ethanol Extract of Citrus sinensis as Keap-1 and NMDA inhibitor in Brain Injury

description: This raw data result from extract ethanol Citrus sinensis analysis compound
DOI: 10.6084/m9.figshare.21432804.v12
title: EPOS-based Plans for Drones

description: The data is used for training and testing in EPOS-based coordination of drones in scale to complete spatio-temporal sensing tasks. The data is generated via the proposed plan generation strategy.
DOI: 10.6084/m9.figshare.21507840
title: Shenzhen data for HGI

description: Please download it to put in /Data if you want to learn region embeddings for Shenzhen. Note that <strong>this is a sub-sampled dataset for Shenzhen </strong>(first 820 regions), as the entire dataset takes a long time to train.
DOI: 10.6084/m9.figshare.21507840.v2
title: Shenzhen data for HGI

description: Please download it to put in /Data if you want to learn region embeddings for Shenzhen. Note that <strong>this is a sub-sampled dataset for Shenzhen </strong>(first 820 regions), as the entire dataset takes a long time to train.
DOI: 10.6084/m9.figshare.21507840.v1
title: Shenzhen data for HGI

description: Please download it to put in /Data if you want to learn region embeddings for Shenzhen.
DOI: 10.6084/m9.figshare.21836496
title: Sub-sampled dataset for Shenzhen (HGI region embedding example dataset)

description: Please download it to put in /Data if you want to learn region embeddings for Shenzhen. Note that <strong>this is a sub-sampled dataset for Shenzhen</strong> (first 820 regions), as the entire dataset takes a long time to train.
DOI: 10.5281/zenodo.7513574
title: Wikidata CiTO intention annotations

description: Dump using three SPARQL queries without provenance of the CiTO intention annotations collected in Wikidata.
DOI: 10.5281/zenodo.7513573
title: Wikidata CiTO intention annotations

description: Dump using three SPARQL queries without provenance of the CiTO intention annotations collected in Wikidata.
DOI: 10.5519/qd.4nr7u8b7
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (316 records)
DOI: 10.6084/m9.figshare.21836508
title: example_data.zip

description: Example data
DOI: 10.6084/m9.figshare.21836508.v1
title: example_data.zip

description: Example data
DOI: 10.5281/zenodo.7513628
title: Digitization of Hodgson 1853

description: This is a dataset that contains a CSV file with lexical forms recorded by Brian Houghton Hodgson’s 1853 article, ‘Sifán and Hórsók Vocabularies’, published in the <em>Journal of the Asiatic Society of Bengal</em>. The article contains a wordlist of just under 200 entries in seven languages labeled Thochu, Sokpa, Gyarung, Takpa, Horpa, Gyami, and Manyak respectively. These materials were digitalized with the help of Ludwig Adisiswoyo.
DOI: 10.5281/zenodo.7513627
title: Digitization of Hodgson 1853

description: This is a dataset that contains a CSV file with lexical forms recorded by Brian Houghton Hodgson’s 1853 article, ‘Sifán and Hórsók Vocabularies’, published in the <em>Journal of the Asiatic Society of Bengal</em>. The article contains a wordlist of just under 200 entries in seven languages labeled Thochu, Sokpa, Gyarung, Takpa, Horpa, Gyami, and Manyak respectively. These materials were digitalized with the help of Ludwig Adisiswoyo.
DOI: 10.34740/kaggle/dsv/4825179
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.7513631
title: PASTA-ice sea ice image classification: calibration files and training data

description: PASTA-ice is a Python-based classification algorithm for aerial sea-ice images. The data set contains calibration files for the CANON EOS-1D Mark III cameras that were implemented in helicopters and POLAR aircraft of the Alfred-Wegener-Institute. Furthermore, it contains training data of labeled sea ice surfaces observed during RV Polarstern cruise PS106 that can be used to train the implemented random forest classifier. Files with extension "sediments" were extended with exemplary data of sediment-loaden snow at the MOSAiC expedition. The PASTA-ice algorithm is available under: https://github.com/nielsfuchs/pasta_ice
DOI: 10.5281/zenodo.7513653
title: AWI CANON Sea ice image albedo retrieval calibration files

description: The dataset contains calibration data, compiled for a Python based retrieval of a broadband albedo estimate from CANON EOS-1D Mark III cameras deployed as aerial imaging system over Arctic sea ice. It contains information on the relative spectral response function of the camera sensor (RSR_CANON), calibration coefficients to convert spectral albedo in the three RGB color bands into broadband albedo under different sky conditions (spec2broad_params) and calibration coefficients to convert RGB intensity into radiance dependent on exposure settings (Calib_coefficients_14mm_diff_settings).
DOI: 10.5281/zenodo.7513652
title: AWI CANON Sea ice image albedo retrieval calibration files

description: The dataset contains calibration data, compiled for a Python based retrieval of a broadband albedo estimate from CANON EOS-1D Mark III cameras deployed as aerial imaging system over Arctic sea ice. It contains information on the relative spectral response function of the camera sensor (RSR_CANON), calibration coefficients to convert spectral albedo in the three RGB color bands into broadband albedo under different sky conditions (spec2broad_params) and calibration coefficients to convert RGB intensity into radiance dependent on exposure settings (Calib_coefficients_14mm_diff_settings).
DOI: 10.34740/kaggle/dsv/4825260
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.7513664
title: Initial camera matrix values for AWI CANON aerial imaging system

description: The file contains a camera matrix in Agisoft Metashape's format that can be used as initial parameters for a multi view reconstruction of aerial sea ice images recorded with the AWI CANON 14mm wide-angle camera (sensor.awi.de ID 4430).
DOI: 10.5281/zenodo.7513663
title: Initial camera matrix values for AWI CANON aerial imaging system

description: The file contains a camera matrix in Agisoft Metashape's format that can be used as initial parameters for a multi view reconstruction of aerial sea ice images recorded with the AWI CANON 14mm wide-angle camera (sensor.awi.de ID 4430).
DOI: 10.34740/kaggle/dsv/4825427
title: COVID Vaccination in World (updated daily)
DOI: 10.34740/kaggle/dsv/4825336
title: TREMO: A dataset for emotion analysis in Turkish
DOI: 10.5281/zenodo.7511224
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 250m SIN Grid in 2015 (185–361)

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 250m spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 250m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2015 (185–361). <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2015 (001–177)</strong> and <em><strong>click here</strong> to download the MUSES FVC produ</em>ct <strong>in 2016 (001–177)</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2015 (185–361) Spatial Resolution: 250m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 100 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7511223
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 250m SIN Grid in 2015 (185–361)

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 250m spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 250m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2015 (185–361). <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2015 (001–177)</strong> and <em><strong>click here</strong> to download the MUSES FVC produ</em>ct <strong>in 2016 (001–177)</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2015 (185–361) Spatial Resolution: 250m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 100 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7403158
title: Source Data for "Phosphorescent extensophores expose elastic nonuniformity in polymer networks"

description: This source data is for the manuscript "Phosphorescent extensophores expose elastic nonuniformity in polymer networks".
DOI: 10.5281/zenodo.7513748
title: Source Data for "Phosphorescent extensophores expose elastic nonuniformity in polymer networks"

description: This source data is for the manuscript "Phosphorescent extensophores expose elastic nonuniformity in polymer networks".