cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6623970
title: The down-sampled displacements and source models of the 2021 Mw7.0 Maduo earthquake

description: 1)The down-sampled LOS displacements from Sentinel-1 and ALOS-2 satellite; 2) the distributed slip source models of the 2021 Mw7.0 Maduo earthquake.
DOI: 10.1594/pangaea.917723
title: Elevation and age determination of Bone Batang

description: HLC from Mann et al. 2016 PPB:-0.500.07
DOI: 10.5281/zenodo.1265188
title: Mridangam Stroke Dataset

description: The Mridangam Stroke dataset is a collection of 7162 audio examples of individual strokes of the Mridangam in various tonics. The dataset comprises of 10 different strokes played on Mridangams with 6 different tonic values. 

<strong>Audio content</strong>

The dataset provides audio examples for each of the strokes. There are six different tonics and ten different stroke labels.

The audio examples were recorded from a professional Carnatic percussionist in a semi-anechoic studio conditions by Akshay Anantapadmanabhan using SM-58 microphones and an H4n ZOOM recorder. The audio was sampled at 44.1 kHz and stored as 16 bit wav files. The dataset can be used for training models for each Mridangam stroke. 

<strong>Metadata</strong>

The whole dataset is organized by the tonic, into 6 packs. Each audio file is named as, 

<pre><code>&lt;StrokeName&gt;_&lt;Tonic&gt;_&lt;InstanceNumber&gt;.wav
&lt;Tonic&gt; = {B, C, Csh, D, Dsh, E}
&lt;StrokeName&gt; = {Bheem, Cha, Dheem, Dhin, Num, Ta, Tha, Tham, Thi, Thom}</code></pre>

<strong>Using this dataset</strong>

A detailed description of the Mridangam and its strokes can be found in the following paper. A part of the dataset was used in the paper. Please cite it if you use the dataset in your work.


Akshay Anantapadmanabhan, Ashwin Bellur, Hema A. Murthy, "Modal analysis and transcription of strokes of the mridangam using non-negative matrix factorization," in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), pp.181-185, May 2013


http://hdl.handle.net/10230/25756

We are interested in knowing if you find our datasets useful! If you use our dataset please email us at mtg-info@upf.edu and tell us about your research.

<strong>Contact</strong>

If you have any questions or comments about the dataset, please feel free to write to us: 

Akshay Anantapadmanabhan (akshay.anantapadmanabhan@gmail.com)

 

http://compmusic.upf.edu/mridangam-stroke-dataset
description: {"references": ["Akshay Anantapadmanabhan, Ashwin Bellur, Hema A. Murthy, \"Modal analysis and transcription of strokes of the mridangam using non-negative matrix factorization,\" in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), pp.181-185, May 2013"]}
DOI: 10.5281/zenodo.3939792
title: A Large Scale PeMS Traffic Speed Dataset

description: This repository is a traffic speed data set collected by California Freeway Performance Measurement System (PeMS). In this data set, it has 11160 time series corresponding to <strong>11160</strong> sensors/locations. In three data files (i.e., <em>pems-4w.csv</em>, <em>pems-8w.csv</em>, and <em>pems-12w.csv</em>), each time series is indeed a time series with <strong>288</strong> (5-minute) time points per day during the first <strong>4 weeks</strong> (PeMS-4W), first <strong>8 weeks</strong> (PeMS-8W), and first <strong>12 weeks</strong> (PeMS-12W) of 2018, respectively. Note that the original data was downloaded from PeMS system with 30-second traffic speed records. Our data is a subset of file <em>speed.h5</em> created by article Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting and its original link is available at here. Our research work on this data set is: Xinyu Chen, Yixian Chen, Nicolas Saunier, Lijun Sun (2021). Scalable low-rank tensor learning for spatiotemporal traffic data imputation. Transportation Research Part C: Emerging Technologies, 129: 103226. [DOI] [preprint] [data] [Python code]
DOI: 10.5281/zenodo.6111982
title: Earthquake catalogue for the Taupō region: 2010–2019

description: This deposit contains the earthquake catalogue described in "A Decade of Earthquake Activity at Taupō Volcano, New Zealand" by Illsley-Kemp et al., published in Volcanica: https://doi.org/10.30909/vol.05.02.335348


If you use this dataset please cite this paper appropriately


Events that have been identified as false detections, caused by distance large magnitude earthquakes are flagged by event_type='other event'
DOI: 10.5281/zenodo.5770338
title: Responses of Surface Evaporative Fluxes in Montane Cloud Forests to Climate Change Scenarios

description: CL_surfobs_raw.mat and LHC_nodew_new_raw.mat are the analyzed CLM simulation output with atmospheric observations in Chi-Lan and Lien-Hua-Chih as input forcings. CLatm_LHC_prec*.mat are the analyzed CLM simulation output in sensitivity tests for the rainfall pattern. CL_*_transform_raw.mat are the analyzed CLM simulation output in CTL simulation and climate change sensitivity tests. Fig_*.m are matlab code files to reproduce figures in the article. Fig_10_ttest.m and Fig_10_LE_p_value.mat are the t-test for the decrease of latent heat flux in the diurnal cycle under climate change scenario and the resulting p-value. Fig_quantile.m and Fig_3_5_6_7_8_9_10_quantile.mat are to obtain first and third quantile of the changes of canopy water and surface heat fluxes in the diurnal cycle under climate change scenarios.
DOI: 10.5281/zenodo.3601614
title: datasets for "VLF Transmitters and Lightning Generated Whistlers 2: Diffusion of Radiation Belt Electrons"

description: Supporting information for "VLF Transmitters and Lightning Generated Whistlers 2: Diffusion of Radiation Belt Electrons," submitted to Journal of Geophysical Research Space Physics. Diffusion coefficients for selected values of L and energy due to Very Low Frequency (VLF) transmitters and lightning generated whistlers (LGW), as well as Da0a0 and energy drag rates |dE/dt|/E from Coulomb collisions. Also provided are precipitation lifetimes, which include Da0a0 from plasmaspheric hiss but do not account for energy drag. Calculations are presented for high and low-density plasmasphere models, for all four combinations of ducted or nonducted VLF and LGW waves.
DOI: 10.1594/pangaea.56198
title: Thickness and oceanographic properties of surface water and sea ice from the Laptev Sea
DOI: 10.1594/pangaea.882289
title: Label-free stimulated Raman imaging of foraminifera
DOI: 10.1594/pangaea.938973
title: Ground-penetrating radar from Kingsbury Pond, Maine, USA

description: We collected ground-penetrating radar (GPR) at Kingsbury Pond, Kingsbury Plantation, Maine, USA on three occasions from 2017-2019 in order to attempt to quantify sediment volume and delineate sedimentary structure. Data was collected using a Geophysical Survey Systems Incorporated (GSSI) 100 MHz radar antenna and SIR-3000 and SIR-4000 control units. One dataset (2017-07-25) was collected in the hull of a wooden canoe, both others (2018-03-03 and 2019-03-09) were collected by towing the antenna across lake ice. Data includes radar profiles (DZT format), metadata (DZX format), and location data with 3 m uncertainty (DZG format containing NMEA 0183 strings). File formats are proprietary to GSSI radar systems but can be accessed using free software.
DOI: 10.5281/zenodo.2565717
title: Evaluation of Materials for Asphalt Mixture Performance, Semi-Circular Bend Laboratory Tests

description: A study was conducted to evaluate the repeatability of the Flexibility Index of asphalt mixtures obtained according to AASHTO TP-124-16.  Three asphalt concrete samples were mixed and compacted using the Superpave Gyratory Compactor in one laboratory.  The samples were then cut to specific dimensions for semi-circular bend testing based on the AASHTO Specifications at a single laboratory using a dedicated cutting equipment.  The samples were randomized and distributed equally among three different testing labs.

The process was repeated three times and in some instances the rate of loading was varied.

This experiment allowed to study the repeatability of the the Flexibility Index
description: This work was funded by the Utah Department of Transportation
DOI: 10.5281/zenodo.3378263
title: Observation of very short period atmospheric gravity waves in the lower Ionosphere using Very Low Frequency waves

description: This is the VLF frequency data recorded at PARI station owned by Prof Morris Cohen, at Georgia Institute of Technology, Atlanta, USA. Data is for six transmitter signals, DHO, NAA, NAU, NLK, NPM, NML with both amplitude and Phase
DOI: 10.5281/zenodo.3356916
title: Image dataset

description: This is the e-commerce image dataset for classification purpose. <strong>Data Set Characteristics: </strong>Real <strong>Number of Instances: </strong>20000 <strong>Area:</strong> Computer science <strong>Number of classes: </strong>2 (Speakers and apparels) <strong>Number of Attributes: </strong>1 <strong>Associated Tasks:</strong> Classification This dataset is collected from an Indian e-commerce platform.<br>
DOI: 10.5281/zenodo.4896171
title: Urban Green Spaces of Shanghai province without ChongMing district

description: Polygons of Urban Green Spaces in Shanghai Province. Polygons have been collected using 静态地图API The projection is New Beijing / Gauss-Kruger zone 21 - EPSG:4576 The dataset contains all 1467626 polygons
DOI: 10.1594/pangaea.786867
title: Sea-ice thickness, snow depth, freeboard, scattering layer thickness, and sea-ice type at sea ice station PS78/212-1
DOI: 10.5281/zenodo.3949320
title: Wideband VLF data observed in New Zealand on 26 August 2018

description: Wideband VLF data observed at Halfway Bush, Dunedin, New Zealand on 26th August 2018.
DOI: 10.5281/zenodo.5211472
title: PPG Diary Pilot Study 1 Data

description: The following data are provided from the PPG Diary 1 Study. <em>Definition: PPG - photoplethysmogram</em> <strong>Versions:</strong> <strong>Preliminary Subsets v.0.1: </strong>Three subsets are provided: (i) a one-hour recording of simultaneous red and infrared PPG signals; (ii) a one-minute recording of infrared PPG signal; (iii) a recording of a single pulse wave, acquired using infrared PPG. Each recording was acquired from the same subject during sleep. The recordings are provided in Matlab ® format. <strong>v.1.1 - Complete Dataset: </strong>The complete dataset is provided in the Matlab ® file named <em>ppg_diary_pilot_conv_data.mat</em>. The contents of the file are described in the README file named <em>ppg_diary_pilot_study_data_README.txt </em>. In addition, the Matlab ® codes used to analyse the dataset are also provided: <em>ppg_diary_pilot1_analysis.m</em> (which is the main function), and <em>PulseAnalyse </em>(v.1.2beta, which is called by the main function). Instructions on how to use the codes to analyse the dataset are provided here. <strong>v.1.2 - including the Submitted Manuscript</strong>: The submitted manuscript is available here. <strong>Further Information</strong> Further information of the PPG Diary Project, and the data provided here, is available at: https://peterhcharlton.github.io/ppg-diary/
description: Published to accompany the publication: Charlton P.H. et al, "Acquiring wearable photoplethysmography data in daily life: the PPG Diary Pilot Study' [under review]
DOI: 10.5281/zenodo.4522315
title: Systematic literature review - Climate Change Adaptation to Hydrohazards

description: Database underpinning systematic literature review conducted under: "Are We Doing ‘Systems’ Research? An Assessment of Methods for Climate Change Adaptation to Hydrohazards in a Complex World" (https://doi.org/10.3390/su11041163)
DOI: 10.1594/pangaea.889787
title: KOSMOS 2014 mesocosm study: physical oceanography, PAR, pH and oxygen
DOI: 10.5281/zenodo.3890240
title: Data set: Can ocean community production and respiration be determined by measuring high-frequency oxygen profiles from autonomous floats?

description: Relevant autonomous float data for Gordon et al. (2020). Following a similar structure to the Argo network's "synthetic" profile files, one file per float is produced with all relevant variables (temperature, salinity, chlorophyll, backscatter, dissolved oxygen) on a common depth and time grid. The Electro-Magnetic Autonomous Profiling Explorer (EM-APEX) floats were deployed in the northern Gulf of Mexico in May 2017 - see Shay et al. (2019) for more information. The data published here contains a timestamp for each data point. Another version of this data which contains some additional variables is hosted on GRIIDC, but does not contain a timestamp for each data point, but rather for each profile.
description: Name of Funder: Gulf of Mexico Research Initiative, Grant Agreement No. / Award No.: GoMRI-V-487
DOI: 10.5281/zenodo.3924682
title: Penobscot Interpretation Dataset

description: We have seen in the past years the flourishing of machine and deep learning algorithms in several applications such as image classification and segmentation, object detection and recognition, among many others. This was only possible, in part, because datasets like ImageNet - with +14 million labeled images - were created and made publicly available, providing researches with a common ground to compare their advances and extend the state-of-the-art. Although we have seen an increasing interest in machine learning in geosciences as well, we will only be able to achieve a significant impact in our community if we collaborate to build such a common basis. This is even more difficult when it comes to the Oil & Gas industry, in which confidentiality and commercial interests often hinder the sharing of datasets to others. In this letter, we present the Penobscot interpretation dataset, our contribution to the development of machine learning in geosciences, more specifically in seismic interpretation. The Penobscot 3D seismic dataset was acquired in the Scotian shelf, offshore Nova Scotia, Canada. The data is publicly available and comprises pre- and pos-stack data, 5 horizons and well logs of 2 wells. However, for the dataset to be of practical use for our tasks, we had to reinterpret the seismic, generating 7 horizons separating different seismic facies intervals. The interpreted horizons were used to generated +100,000 labeled images for inlines and crosslines. To demonstrate the utility of our dataset, results of two experiments are presented. <strong>Dataset contents</strong> Crosslines: Classes: 7 Slices used for training: 289 Records per class for training: 16706 Slices used for testing: 192 Records per class for testing: 1000 Inlines: Classes: 7 Slices used for training: 358 Records per class for training: 14988 Slices used for testing: 238 Records per class for testing: 1000
DOI: 10.5281/zenodo.2555731
title: Microplastic

description: This FTIR hyperspectral image shows an environmental plankton sample which has been spiked with microplastics in the size range between 10 and 200 µm. The added particles are one of the following polymer types:


	polyethylene
	polypropylene
	polystyrene
	poly(methyl methacrylate)
	polyacrylonitrile


This hyperspectral image has been used as a source for training data for the creation of random decision forest classifiers. For a closer description of the dataset and the sample preparation see Hufnagl <em>et al.</em> (2019).

 

If you reuse this dataset please cite

 

Hufnagl, B., Steiner, D., Renner, Löder, M. G. J., Laforsch, C. and Lohninger, H. <em>A Methodology for the Fast Identification and Monitoring of Microplastics in</em><em> Environmental Samples using Random Decision Forest Classifiers,</em> Analytical Methods, 2019, DOI:10.1039/C9AY00252A
description: Funding was provided by Deutsche Forschungsgemeinschaft (DFG) –project number 391977956–SFB 135 and the German Federal Ministry of Education and Research (project PLAWES, grant 03F0789A
description: {"references": ["Hufnagl, B., Steiner, D., Renner, L\u00f6der, M. G. J., Laforsch, C. and Lohninger, H. A Methodology for the Fast Identification and Monitoring of Microplastics in Environmental Samples using Random Decision Forest Classifiers, Analytical Methods, 2019, DOI:10.1039/C9AY00252A"]}
DOI: 10.5281/zenodo.6697343
title: CoFly-WeedDB: A UAV image dataset for weed detection and species identification

description: The CoFly-WeedDB contains 201 RGB images (~436MB) from the attached camera of DJI Phantom Pro 4 from a cotton field in Larissa, Greece during the first stages of plant growth. The RGB images were collected while the Unmanned Aerial Vehicle (UAV) was performing a coverage mission over the field's area. During the designed mission, the camera angle was adjusted to -87°, vertically with the field. The flight altitude and speed of the UAV were equal to 5m and 3m/s, respectively, aiming to provide a close and clear view of the weed instances. All images have been annotated by expert agronomists using the LabelMe annotation tool, providing the exact boundaries of 3 types of common weeds in this type of crop, namely (i) Johnson grass, (ii) Field bindweed, and (iii) Purslane. The dataset can be used alone and in combination with other datasets to develop AI-based methodologies for automatic weed segmentation and classification purposes.
description: This research has been financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH - CREATE - INNOVATE (T1EDK-00636).
DOI: 10.5281/zenodo.6412365
title: Supporting Information for 'forceX and forceR: a mobile setup and R package to measure and analyse a wide range of animal closing forces'

description: <strong>Supporting Information of 'forceX and forceR: a mobile setup and R package to measure and analyse a wide range of animal closing forces'</strong> This dataset contains the Supporting Information of the publication Rühr PT & Blanke A <strong>(2022)</strong>: 'forceX and forceR: a mobile setup and R package to measure and analyse a wide range of animal closing forces'. doi: 10.1111/2041-210X.13909. It includes validation measurements the forceX setups (1 Ruehr Blanke 2022 validation measurements.zip) all CAD files to build the forceX setup (3D-printed or metal-turned) (2 Ruehr Blanke 2022 forceX CAD files.zip) forceX assembly instructions in HTML format, including schematics of custom electronics (3 Ruehr Blanke 2022 forceX Assembly instructions.html) forceX assembly instructions as video (4 Ruehr Blanke 2022 forceX assembly video 03.mp4) R code that produced all validation-related figures used in the original publication and that functions as a forceR v.1.0.13 example workflow (5 Ruehr Blanke 2022 forceR_workflow_example.R) Python code to take videos of force measurements using the forceX camera module (6 Ruehr Blanke 2022 forceX_RPi_camera_code.py) bundled version of forceR v.1.0.15 (forceR_1.0.15.tar.gz) The CAD files and assembly instructions are also available on Thingiverse. The forceR package is available on CRAN (stable version) and GitHub (development version).
DOI: 10.5281/zenodo.4117913
title: ritwik1111/MHW: notebook releases

description: Jupyter notebooks and data for calculating MHW charateristics from SST datasets.
DOI: 10.5281/zenodo.59507
title: Crowdsourcing Thesaurus

description: Thesaurus used for text mining analysis on a corpus about digital libraries and crowdsourcing. It contains ideologies, taxonomies and motivations.

Analysis were used for a French article : Andro, M. (2016). Bibliothèques numériques et crowdsourcing : analyses bibliométriques et text mining
DOI: 10.5281/zenodo.1246868
title: Wideband Vlf Data Observed In New Zealand During The Period 07-08 September 2017

description: Wideband VLF data observed in New Zealand during the period 07-08 September 2017.
DOI: 10.5281/zenodo.5877712
title: Datasets used on the analysis of Mediterranean Mass mortality events during the 2015-2019 period

description: This upload contains three datasets in CSV files and a PDF file with the specific description of the CSV files. These data was used for the analysis of the mass mortality events reported during the period 2015-2019 across the Mediterranean. The datasets are 1) a CSV file with the data used for the description of the spatial-temporal, depth and biological patterns of mortality observed in the Mediterranean Sea in the 2015-2019 period; 2) a CSV file with the data used to conduct the analyses on the relationship between marine heatwaves (MHW) days found on the surface (averaged per monitored area and year) and the corresponding mass mortality incidence of benthic organisms; 3) a CSV file with the data used to conduct the analyses on the relationship between in-situ MHW days (averaged per monitored area, depth and year) and the corresponding mass mortality incidence. Data were obtained through benthic community field surveys conducted by 33 research teams from 11 Mediterranean countries. Surveys covered thousands of kms of coastline, spanning 13º of latitude (32 °S to 45 °N) and 40º of longitude (-5°W to 35°E) in the Mediterranean Sea. The dataset provides the most updated inventory of mass mortality events records for benthic species between 2015-2019 in the region. The surveys were conducted in 142 monitoring areas. Monitoring areas were considered as geographic areas (10-25 km coastline, e.g., a marine protected area and the nearby coast) sharing common environmental features. In situ temperature conditions datasets base consists of high frequency (hourly) time series obtained using HOBO data loggers (accuracy ± 0.21°C) set-up at standard depths along rocky walls by divers, generally every 5 m from the surface to 40 m depth.This dataset as in the case of the mortality was assembled under the T-MEDNet initiative (www.t-mednet.org). Satellite derived sea surface temperature (SST) across the Mediterranean Sea was obtained from CMEMS (https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=SST_MED_SST_L4_REP_OBSERVATIONS_010_021). The data consists of daily (night-time), gap free, optimally interpolated foundation SST at ~4 km resolution from AVHRR with improved accuracy and stability over the 1982-2019 period
DOI: 10.5281/zenodo.4495066
title: Do not use

description: Do not use