cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11202226
title: SWIFTIES (Subject and Wearables data for Investigation of Fatiguing Tasks In Extension/flexion of Shoulder/elbow)

description: 32 subjects (17 males, 15 females) performed 8 shoulder and elbow flexion-extension tasks with the dominant arm until fatigue. Tasks were performed at 25% and 45% of the maximum voluntary contraction (MVC) force in a static and dynamic manner. Every combination of movement (static or dynamic) x joint (shoulder or elbow) x load (25% or 45% of MVC Force) was performed by every subject. Subject data includes information on demographic and anthropometrics, rate of perceived exertion (RPE), endurance time of tasks, MVC forces, and loads lifted. Sensor data includes inertial measurement unit (IMU), electromyography (EMG), motion capture (MC) and pressure insole (PI) data.
DOI: 10.5281/zenodo.11202227
title: SWIFTIES (Subject and Wearables data for Investigation of Fatiguing Tasks In Extension/flexion of Shoulder/elbow)

description: 32 subjects (17 males, 15 females) performed 8 shoulder and elbow flexion-extension tasks with the dominant arm until fatigue. Tasks were performed at 25% and 45% of the maximum voluntary contraction (MVC) force in a static and dynamic manner. Every combination of movement (static or dynamic) x joint (shoulder or elbow) x load (25% or 45% of MVC Force) was performed by every subject. Subject data includes information on demographic and anthropometrics, rate of perceived exertion (RPE), endurance time of tasks, MVC forces, and loads lifted. Sensor data includes inertial measurement unit (IMU), electromyography (EMG), motion capture (MC) and pressure insole (PI) data.
DOI: 10.5281/zenodo.11231225
title: SWIFTIES (Subject and Wearables data for Investigation of Fatiguing Tasks In Extension/flexion of Shoulder/elbow)

description: 32 subjects (17 males, 15 females) performed 8 shoulder and elbow flexion-extension tasks with the dominant arm until fatigue. Tasks were performed at 25% and 45% of the maximum voluntary contraction (MVC) force in a static and dynamic manner. Every combination of movement (static or dynamic) x joint (shoulder or elbow) x load (25% or 45% of MVC Force) was performed by every subject. Subject data includes information on demographic and anthropometrics, rate of perceived exertion (RPE), endurance time of tasks, MVC forces, and loads lifted. Sensor data includes inertial measurement unit (IMU), electromyography (EMG), motion capture (MC) and pressure insole (PI) data.
DOI: 10.5281/zenodo.13771675
title: SWIFTIES (Subject and Wearables data for Investigation of Fatiguing Tasks In Extension/flexion of Shoulder/elbow)

description: 32 subjects (17 males, 15 females) performed 8 shoulder and elbow flexion-extension tasks with the dominant arm until fatigue. Tasks were performed at 25% and 45% of the maximum voluntary contraction (MVC) force in a static and dynamic manner. Every combination of movement (static or dynamic) x joint (shoulder or elbow) x load (25% or 45% of MVC Force) was performed by every subject. Subject data includes information on demographic and anthropometrics, rate of perceived exertion (RPE), endurance time of tasks, MVC forces, and loads lifted. Sensor data includes inertial measurement unit (IMU), electromyography (EMG), motion capture (MC) and pressure insole (PI) data.
DOI: 10.5281/zenodo.13773233
title: SWIFTIES (Subject and Wearables data for Investigation of Fatiguing Tasks In Extension/flexion of Shoulder/elbow)

description: 32 subjects (17 males, 15 females) performed 8 shoulder and elbow flexion-extension tasks with the dominant arm until fatigue. Tasks were performed at 25% and 45% of the maximum voluntary contraction (MVC) force in a static and dynamic manner. Every combination of movement (static or dynamic) x joint (shoulder or elbow) x load (25% or 45% of MVC Force) was performed by every subject. Subject data includes information on demographic and anthropometrics, rate of perceived exertion (RPE), endurance time of tasks, MVC forces, and loads lifted. Sensor data includes inertial measurement unit (IMU), electromyography (EMG), motion capture (MC) and pressure insole (PI) data.
DOI: 10.5281/zenodo.15172815
title: SWIFTIES (Subject and Wearables data for Investigation of Fatiguing Tasks In Extension/flexion of Shoulder/elbow)

description: 32 subjects (17 males, 15 females) performed 8 shoulder and elbow flexion-extension tasks with the dominant arm until fatigue. Tasks were performed at 25% and 45% of the maximum voluntary contraction (MVC) force in a static and dynamic manner. Every combination of movement (static or dynamic) x joint (shoulder or elbow) x load (25% or 45% of MVC Force) was performed by every subject. Subject data includes information on demographic and anthropometrics, rate of perceived exertion (RPE), endurance time of tasks, MVC forces, and loads lifted. Sensor data includes inertial measurement unit (IMU), electromyography (EMG), motion capture (MC) and pressure insole (PI) data.
DOI: 10.34740/kaggle/dsv/11323564
title: e-IPO Indonesia Data - Investment
DOI: 10.15468/dl.bd444h
title: Occurrence Download

description: A dataset containing 1485 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dasyatis pastinaca (Linnaeus, 1758)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen, Material sample)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 1485 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010044-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21338/cron3w1e01
title: CRONOS3 Wave 1 edition 1.0
DOI: 10.15468/dl.fg7h99
title: Occurrence Download

description: A dataset containing 8841 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cervus elaphus Linnaeus, 1758",
 "Geometry POLYGON((-4.47763888888889 56.7401388888889, -2.79986111111111 56.7401388888889, -2.79986111111111 57.4134722222222, -4.47763888888889 57.4134722222222, -4.47763888888889 56.7401388888889))",
 "CoordinateUncertaintyInMeters is 0,101",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8841 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010045-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.24432/c5dk6r
title: HTRU2
DOI: 10.6084/m9.figshare.28465688
title: Identifying high-spin hydroxyl-coordinated Fe³⁺N₄ as the active centre for acidic oxygen reduction using molecular model catalysts

description: Here, we provide the raw data for all curves and data points presented in the figures of this article, along with the atomic coordinates of the optimized computational models for each structure discussed, available in a VASP-compatible file format.
DOI: 10.15485/1571527
title: Pan-arctic river bank erosion and accretion, and planform metrics measured over intervals ranging from 1973 to 2016

description: This dataset provides the tabular summary of analysis of 17 reaches of 15 Arctic rivers for river bank erosion and accretion rates, as well as, river channel properties such as channel width, bank curvature, and the aspect/orientation of the river banks. These rivers include the: Chandalar River, Alaska, Colville River, Alaska; Indigirka River, Russia; Kolyma River, Russia; Koyukuk River, Alaska; Lena River, Alaska; Noatak River, Alaska; Ob River, Russia; Pechora River, Russia; Tanana River, Alaska, Selawik River, Alaska; Taz River, Russia; Yana River, Russia; Yenisei River, Russia; and the Yukon River, Alaska. The dataset was generated from a total of 129 images including: Landsat, higher resolution satellite imagery, and aerial photography over time periods ranging from the 1970s and 2016. A full list of the image dates, row and path (for Landsat), and pixel resolutions is provided in the dataset. Masks for the Chandalar River, Tanana River, and Yukon at Holy Cross were obtained from Brown et al. (2020). The masks were analyzed using the Spatially Continuous Riverbank Erosion and Accretion Measurements (SCREAM) software detailed in Rowland et al. 2016. The masks used in this analysis can be found an accompanying dataset (doi:10.15485/1571527).In files with “summary” in the name, the data is provided at a pixel level, where each mapped bank pixel has an associated erosion or accretion value, a channel width, a curvature value, and an aspect each river and time period will have an individual file. Files with “Segments” in name provide data that is averaged along segments of the rivers. These data are consolidated into a single file each for the erosion and accretion measurements. These segments are approximately 10 channel widths in length. In addition to erosion and accretion rates, the segment-based results include area measurements of erosion and accretion, islands, and channels. Revisions 2023:-Data added for the Koyukuk River for time periods of 1978-2012, 1978-2018, and 2012-2018. ---Data added from the Chandalar River, Tanana River, and Yukon River at Holy Cross based on masks obtained from Brown et al. (2020).-Updated the values for Drainage area and river slope, see methods below-Added values for meant topographic slope for upstream contributing area, long term averaged annual maximum monthly flow, average annual maximum monthly flow for the time period of erosion record, and added the river slope extracted from the Lin et al. (2020) data product.-Add field for River Planform Multi threaded (M) or Single threaded-Added ‘ConsolidatedErosionSegments.csv’ which provides the same data as AllRiversErosionSegments.csv rebinned with averages along river segments based on upstream drainage area instead of channel segments based on lengths set to approximately 10 channel widths.
DOI: 10.25346/s6/ylxabh
title: Routines to Process Data and Make Figures for Local Accel Radial Diffusion Electrons

description: Routines used to process the data and make the figures
DOI: 10.26022/ieda/331273
title: Upper crustal velocity structure of Santorini volcano and the surrounding region, Hellenic volcanic arc (Heath et al., 2019)

description: This data set consists of a 3-D tomographic model of the P-wave seismic velocity structure of the upper 4 km of the crust of Santorini caldera and the surrounding region. The model was derived from active-source data acquired during the PROTEUS 3-D seismic tomography experiment conducted during Langseth cruise MGL1521 in 2015 (chief scientists Emilie Hooft, Doug Toomey, & Paraskevi Nomikou). The model and results are described in Heath et al. (2019). The data was collected using a dense amphibious array of &gt;14,300 marine sound sources from a 6,600 cubic inch 36-component air gun array towed at 12-m depth that were recorded on 156 short-period marine and land seismometers, covering an area 120 km by 45 km. Average shot spacing was ~150 m along ENE-WSW oriented shot lines spaced at 1–2-km intervals and included shot-receiver offsets up to ~115 km. A three-dimensional, iterative tomographic technique (Toomey et al., 1994) was used to invert over 200,000 Pg refraction arrival times to constrain isotropic slowness within the upper crust. The data file is in SEG-Y format with UTM coordinates (zone 35N) and with P-wave velocity on a grid that is spaced 200 m horizontally and 50 m vertically. This model is NOT masked in regions of poor ray coverage and poor resolution. This data set was generated as part of the project called Collaborative research: Crustal magma plumbing of the Santorini volcanic system. Funding was provided by NSF grants OCE14-59794.
DOI: 10.5067/2e096jv59pk7
title: MERRA-2 instM_3d_asm_Np: 3d,Monthly mean,Instantaneous,Pressure-Level,Assimilation,Assimilated Meteorological Fields V5.12.4
DOI: 10.5067/g519shckwqv6
title: IceBridge L4 Sea Ice Freeboard, Snow Depth, and Thickness, Version 1
DOI: 10.5281/zenodo.14902704
title: Dataset of relative seismic velocity variations (dv/v) of R66E3 Raspberry Shake and groundwater level variations of BSS002NNZL borehole from 2022/04/28 to 2025/02/04

description: Dataset of relative seismic velocity variations (dv/v) of R66E3 Raspberry Shake and groundwater level variations of BSS002NNZL borehole from 2022/04/28 to 2025/02/04.

A Raspberry Shake RS3D, a three-components geophone (station R66E3 and network code AM) with a natural frequency of 4.5 Hz (electronically extended to 0.5 Hz), is installed in the technical room located 8 m from the BSS002NNZL borehole (a groundwater monitoring borehole), in the town of La Trinité, Martinique. 

Seismic recordings for station R66E3 (network AM: https://doi.org/10.7914/SN/AM) are collected from the Raspberry Shake data center (https://data.raspberryshake.org/fdsnws/). The raw continuous seismic recordings and relative velocity variations are processed by using MATLAB (https://mathworks.com).

This dataset contains the resulting 2-3 Hz frequency range relative velocity variations data. 

The dataset also contains daily mean groundwater level data (in altitude and pressure) of BSS002NNZL borehole. The borehole is equipped with a PARATRONIC SNP pressure sensor with data recording every minutes. The probe resolution is ±1 mm.

Rainfall and air temperature are available close to the site thanks to the French climatic network operated by Météo-France (meteo.data.gouv.fr). Daily rainfall (from Morne des Esses station) and daily air temperature data (from Spoutourne station) are also provided in the dataset.
DOI: 10.5281/zenodo.4139695
title: LimnoSat-US: A Remote Sensing Dataset for U.S. Lakes from 1984-2020

description: LimnoSat-US is an analysis-ready remote sensing database that includes reflectance values spanning 36 years for 56,792 lakes across &gt; 328,000 Landsat scenes. The database comes pre-processed with cross-sensor standardization and the effects of clouds, cloud shadows, snow, ice, and macrophytes removed. In total, it contains over 22 million individual lake observations with an average of 393 +/- 233 (mean +/- standard deviation) observations per lake over the 36 year period. The data and code contained within this repository are as follows: <em>HydroLakes_DP.shp: </em>A shapefile containing the deepest points for all U.S. lakes within HydroLakes. For more information on the deepest point see https://doi.org/10.5281/zenodo.4136754 and Shen et al (2015). <em>LakeExport.py</em>: Python code to extract reflectance values for U.S. lakes from Google Earth Engine. <em>GEE_pull_functions.py: </em>Functions called within LakeExport.py <em>01_LakeExtractor.Rmd:</em> An R Markdown file that takes the raw data from LakeExport.py and processes it for the final database. <em>SceneMetadata.csv:</em> A file containing additional information such as scene cloud cover and sun angle for all Landsat scenes within the database. Can be joined to the final database using LandsatID. <em>srCorrected_us_hydrolakes_dp_20200628: </em>The final LimnoSat-US database containing all cloud free observations of U.S. lakes from 1984-2020. Missing values for bands not shared between sensors (Aerosol and TIR2) are denoted by -99. dWL is the dominant wavelength calculated following Wang et al. (2015). pCount_dswe1 represents the number of high confidence water pixels within 120 meters of the deepest point. pCount_dswe3 represents the number of vegetated water pixels within 120 meters and can be used as a flag for potential reflectance noise. All reflectance values represent the median value of high confidence water pixels within 120 meters. The final database is provided in both as a .csv and .feather formats. It can be linked to SceneMetadata.cvs using LandsatID. All reflectance values are derived from USGS T1-SR Landsat scenes.
description: {"references": ["Shen, Z., Yu, X., Sheng, Y., Li, J., & Luo, J. (2015). A Fast Algorithm to Estimate the Deepest Points of Lakes for Regional Lake Registration. PLOS ONE, 10(12), e0144700. https://doi.org/10.1371/journal.pone.0144700", "Wang, S., Li, J., Shen, Q., Zhang, B., Zhang, F., & Lu, Z. (2015). MODIS-Based radiometric color extraction and classification of inland water with the forel-ule scale: A case study of lake Taihu. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(2), 907\u2013918. https://doi.org/10.1109/JSTARS.2014.2360564"]}
DOI: 10.5281/zenodo.7048407
title: Mounded Site Boundaries

description: The dataset contains multi-period mounded site boundaries, mainly from the Khabur Basin. Please note the dataset is solely based on a desktop survey of CORONA imagery (https://corona.cast.uark.edu/). Therefore, no accuracy test was performed on the ground. Some polygons may be connected to each other if sites were considerably close together. Projection: WGS 84 / UTM zone 37N (EPSG: 32637)
DOI: 10.6073/pasta/bfcb6628794b8ba1fb1159b9b75e3f58
title: Marcell Experimental Forest daily precipitation, 1961 - ongoing

description: This data publication contains daily precipitation data collected from 1961-ongoing at the Marcell Experimental Forest (MEF) in Itasca County, Minnesota, which is operated and maintained by the USDA Forest Service, Northern Research Station. The data come from seven peatland watersheds instrumented for hydrologic monitoring.
DOI: 10.7284/102705
title: Expendable Probe data collected during research cruise MGL1111 using a Sippican MK21 instrument system onboard the platform RV Marcus G. Langseth

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.1594/ieda/322014
title: Processed Temperature, Salinity, and Current Measurement Data from the Amundsen Sea acquired during the Nathaniel B. Palmer expedition NBP0901 (2009)

description: This data set was derived from data acquired during Nathaniel B. Palmer expedition NBP0901 conducted in 2009 (Chief Scientist: Dr. Stan Jacobs; Investigator(s): Dr. Stan Jacobs and Dr. Bruce Huber). These data files are of Matlab Binary format and include Current Measurement, Salinity, and Temperature data and were processed after data collection. Data were acquired as part of the project(s): Collaborative International Research: Amundsen Sea Influence on West Antarctic Ice Sheet Stability and Sea Level Rise, Shedding dynamic light on iron limitation: The interplay of iron limitation and dynamic irradiance conditions in governing the phytoplankton distribution in the Ross Sea, and Collaborative Research: Sampling the ocean - sea ice interaction in the Pacific center of the Antarctic Dipole, and funding was provided by NSF grant(s): OPP06-32282. This data was cited by Assmann et al., 2013.
DOI: 10.25392/leicester.data.11854713.v1
title: SuperDARN Heppner-Maynard Boundaries

description: SuperDARN Heppner-Maynard Boundary latitudes for the Northern Hemisphere for 2011 and 2015. Determined using the traditional latitude determination condition and all available high and polar latitude radar data. Data files provide date, time and the midnight meridian value of the Heppner-Maynard Boundary.
DOI: 10.5067/5eskgqtzg7fo
title: MERRA-2 instM_2d_asm_Nx: 2d,Monthly mean,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4
DOI: 10.5067/terra+aqua/ceres/syn1degday_l3.004a
title: CERES Level 3 SYN1DEG-DAYTerra+Aqua HDF4 file - Edition 4A
DOI: 10.5285/48fc3d1e8ada405c8486ada522dae9e8
title: ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from the CryoSat-2 satellite on a monthly grid (L3C), v2.0

description: This dataset provides a Climate Data Record of Sea Ice Thickness for the SH polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite at Level 3C (L3C). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project. It provides daily sea ice thickness data gridded on a Lambeth Azimuthal Equal Area grid for the period November 2010 to April 2017. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly considers the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information.
DOI: 10.5676/dwd_gpcc/fd_m_v7_100
title: GPCC Full Data Reanalysis Version 7.0 at 1.0°: Monthly Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data
title: Gridded Monthly Totals

description: This is the centennial GPCC Full Data Reanalysis of monthly global land-surface precipitation based on the 75,000 stations world-wide that feature record durations of 10 years or longer. This product contains the monthly totals on a regular grid with a spatial resolution of 1.0° x 1.0° latitude by longitude. Precipitation anomalies at the stations are interpolated and then superimposed on the GPCC Climatology V2015 in the corresponding resolution (DOI: 10.5676/DWD_GPCC/CLIM_M_V2015_100). The temporal coverage of the dataset ranges from January 1901 until December 2013. The GPCC Full Data Reanalysis is the most accurate in situ precipitation reanalysis data set of GPCC. Moreover it supports regional climate monitoring, model validation, climate variability analysis and water resources assessment studies.
description: General user recommendations: Users are referred to following gridded Global Precipitation Climate Centre (GPCC) products: GPCC Climatology 1951-2000 (GPCC_CLIM) with high representativeness, for application as a reference, and for utilization of the anomaly interpolation method. GPCC Full Data Reanalysis (GPCC_FD) with high accuracy, for, e.g., verification of models, or for analysis of historic global precipitation, or for research concerning the global water cycle, e.g., trend and teleconnection analyses. GPCC Monitoring Product (GPCC_MP) with high availability and reasonable timeliness, for applications like calibration of satellite data, or early annual reporting. GPCC First Guess Product (GPCC_FG) with high timeliness, to be applied for, e.g., drought monitoring.
DOI: 10.6073/pasta/cddd3985350334b876cd7d6d1a5bc7bf
title: Daily averaged weather timeseries (air temperature, pressure, wind speed, wind direction, precipitation, sky cover) at Palmer Station, Antarctica combining manual observations (1989 - Dec 12, 2003) and PALMOS automatic weather station measurements (Dec 13, 2003 - March 2019).

description: Weather data acquisition was originally by manual observation and continued with an automated system installed in Nov 2001. Measurements began shifting from manual to automated observations in June 2003 until the manual observations were ended on December 12, 2003. Data are collected, compiled, and distributed by the US Antarctic polar contractor. Electronic distributed occurs monthly from Palmer station via internet and are available at University of Wisconsin weather archive: ftp://amrc.ssec.wisc.edu/pub/palmer/climatology/
DOI: 10.7289/v56971m6
title: Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Version 2.3 (Monthly)

description: The Global Precipitation Climatology Project (GPCP) consists of monthly satellite-gauge and associated precipitation error estimates and covers the period January 1979 to the present. The general approach is to combine the precipitation information available from each of several satellite and in situ sources into a final merged product, taking advantage of the strengths of each data type: passive Microwave estimates are based on SSMI/SSMIS data; infrared precipitation estimates are included, using GOES data and POES data; as well as other low earth orbit data and insitu observations. Data are provided on a 2.5 degree grid.