cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4060018
title: Continental Splitted Non-IID Image Classification Dataset

description: A non-IID dataset with images from Flickr and labels from Open Image Dataset. The dataset is split into parts from three continents, North America, Europe, and Asia, between which the data turned out to be non-IID, with same objects looking different. The images in the dataset were cropped from original images with the help of bounding boxes in Open Image Dataset.
DOI: 10.5281/zenodo.582659
title: Predictive And Sensory Signals Systematically Lower Peak Forces In The Exploration Of Softer Objects

description: An object’s softness is stereotypically judged by pressure movements indenting the surface [1]. In exploration without movement constraints, participants repeat such indentation movements. We investigated how people modulate executed peak forces for different indentations depending on stimulus softness. Participants performed a 2AFC discrimination task for stimulus pairs from one of 4 softness categories. We assumed that movement control at different exploration moments is based on variations in the predictive and sensory signals available. We manipulated availability of predictive signals on softness category, by presenting either stimuli of the same category in a blocked fashion (high predictability) or by randomly mixing stimuli from different categories (low predictability). Effects of sensory signals were examined by contrasting first and last indentation, as sensory signals are hardly available when initiating exploration but gathered during exploration. The results show that participants systematically apply lower forces when sensory or predictive signals indicate softer objects as compared to harder objects. We conclude that softness exploration can be considered as a sensorimotor control loop, in which predictive and sensory signals determine movement control. Further, the results indicate a high importance of predictive processes throughout the entire exploration, as effects of predictive signals maintain in the last indentation.

<strong>Lezkan</strong>, A. & <strong>Drewing</strong>, K. (2015). Predictive and sensory signals systematically lower peak forces in the exploration of softer objects. World Haptics Conference, 2015 IEEE (pp. 69-74). IEEE.

The Zip file contains all data relative to the publication. For each participant code and each session exists a *txt and

A description of the variables is contained in the file VARIABLE_CODES.txt
DOI: 10.5281/zenodo.55374
title: Aircraft Parameters

description: Aircraft parameters of same planes
DOI: 10.5281/zenodo.570527
title: Wp2 T2.4 Media T03 - Scene 5

description: Raw media files from scene 5 of Pilot 01 for Immersia TV project.
DOI: 10.5281/zenodo.848741
title: Reference Data For Splicify

description: This is data.tar.gz with reference data to run Splicify.
DOI: 10.5281/zenodo.46392
title: Who International Clinical Trials Registry Platform (Ictrp), April 2015

description: The World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) dataset, retrieved in April 2015.

At the time of writing, the WHO ICTRP does not have any way for the general public to retrieve their complete dataset. They provided special access to us (ClinicalTrials.gov) to retrieve the data, and gave permission for us to make the data publicly available.

We distinguish records (a trial as registered in a specific registry) and variants (different versions of a record within that registry). Only the EU Clinical Trials Register (EUCTR) has multiple variants for some records, one for each member state where the trial was registered.

The dataset consists of 320,790 variants of 285,177 unique records from sixteen registries. Variants were retrieved one-at-a-time over the course of the first week of April, as requests took ~ 2 seconds each to resolve. A list of non-ClinicalTrials.gov records was provided by the WHO, and a list of ClinicalTrials.gov records was retrieved from ClinicalTrials.gov.
description: These data are referenced in one manuscript under review and one in preparation that will be published open access. We hope it will also be useful to others.
DOI: 10.5281/zenodo.832877
title: Observed Monthly N2O Emission Dataset Used For Model Carlibaration And Validation

description: The N<sub>2</sub>O emission dataset for calibration sites was extracted from the published figures and tables using GetData Graph Digitizer version 2.24; the other information such as biome, geographic location, experimental period, soil organic carbon content, soil pH and soil texture was selected from corresponding literature. If the data related to soil was not avaliable, we extracted them from the soil database(IGBP-DIS)
DOI: 10.5281/zenodo.13148473
title: Binary black-hole simulation SXS:BBH:1828

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.13148474
title: Binary black-hole simulation SXS:BBH:1828

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.5068253
title: twitter Dataset

description: The WE1S <code>twitter</code> dataset contains 5,024,756 tweets posted to Twitter between December 6th, 2013 and June 30th, 2019. The dataset is divided into subcollections based on the query terms "humanities", "liberal arts", "stem", "science", and "science-es" (that is a query for the presence of either "science" or "sciences"). Subcollections can be identified in the dataset from the value of the <code>metapath</code> property. The number of tweets in each subcollections is as follows: humanities: 1,705,038 liberal-arts: 7,663 stem: 865,156 science: 2,089,985 science-es: 356,914 The tweets are distributed over the following date range: 2013: 16,335 2014: 862,746 2015: 1,711,823 2016: 947,561 2017: 976,971 2018: 3,24,133 2019: 185,187 Collectively, the tweets represent the work of 1,886,739 distinct usernames. Each tweet's mentions, hashtags, and links are recorded, as well the number of likes and retweets. Unlike most other WE1S datasets, the Twitter dataset does not contain extracted features. Instead, it contains the original text of the tweet (the value of the <code>content</code> property, along with a <code>tidy_tweet</code> property, which contains the text of the tweet after preprocessing. Tweets were preprocessed using a modified form of the WE1S preprocessing algorithm. Details can be found in the WE1S Tweet-Suite repository. <em>(See WE1S Research Materials Overview for the relation between the project's "datasets" and "collections.")</em>
description: The data has been archived in jsonl format (each json document is delimited by a line break).
DOI: 10.5281/zenodo.34847
title: Raw Data From Parlnet V2.4

description: This archive contains raw data collected by version 2.4 (December 2015) of the parlnet repository.

The MD5 sum of the archive is 2bab1d756cf9a1ed0bb3851814eb4262.

The code behind this data dump is at https://github.com/briatte/parlnet – please refer to it for the full list of data sources, which might have additional conditions for reuse than the license of this archive.
description: the code that parses the committees of the French lower chamber will download 54 files that are currently missing from the data dump. This bug will be fixed in the next raw data release.
DOI: 10.5281/zenodo.4817403
title: MeMAD Knowledge Graph

description: The MeMAD Knowledge Graph implements the EBU Core ontology and contains structured descriptions of more than 90k Radio and TV programs as well as more than 100k parts (segments) from 100 channels made available by INA (France) and Yle (Finland). This represents more than 64k hours of content in French, Finnish and Swedish. The dataset contains: the MeMAD ontology that extends the EBU Core ontology the MeMAD controlled vocabularies represented in SKOS that interlink the programs genres, themes and the person roles using and extending the referenced EBU controlled vocabularies a number of graphs encapsulating the legacy metadata coming from the INA Legal Deposit, the INA Professional Archive and the Yle archive a graph encapsulating the automatic multimodal content analysis performed on some of those programs: this includes results from automatic speech recognition (ASR), extracting and disambiguating named entities from the ASR, face recognition from the video frames, machine translation of the ASR and visual deep captions generation
DOI: 10.5281/zenodo.5111989
title: GPRChinaTemp1km: 1 km monthly mean air temperature for China from January 1951 to December 2020

description: GPRChinaTemp1km is a new high-resolution (1-km) monthly gridded air temperature dataset for China from January 1951 to December 2020. The dataset includes monthly mean air temperature covering the main land area of China during 1951-2020, which was interpolated by the Gaussian process regression (GPR) method based on the meteorological station data. The monthly gridded temperature dataset was evaluated by the observed values of the meteorological stations from the China Meteorological Data Service Centre. The dataset is in GeoTIFF format in the WGS84 (EPSG:4326) coordinate system. The unit of the data is degree Celsius (°C).
DOI: 10.1594/pangaea.934056
title: Crosshole ground penetrating radar data collected in clayey till with sand occurrences

description: The data was collected in November, 2015 and consists of crosshole ground penetrating radar (GPR) data collected between two boreholes 3.367 m apart and down to approximately 8 m depth. The equipment used to collect the data was Sensors & Software pulseEKKO PRO equiped with 1000 V transmitter. The time window used is 340 ns, sampled every 0.4 ns, resulting in 850 samples per trace. Every trace is stacked 64 times to increase signal-to-noise ratio. Antennae frequency is 100 MHz.Both Zero-Offset Profiling (ZOP) data and Multiple-Offset Gather (MOG) data, with corresponding Calibration files, are available, both as raw data, but also picked travel times and amplitudes of the signal. The GPR data contains information on the one- and two-dimensional changes in electromagnetic properties between the boreholes.
DOI: 10.5281/zenodo.1209073
title: Changes In Gene Expression During Germination Reveal Pea Genotypes With Either 'Quiescence' Or 'Escape' Mechanisms Of Waterlogging Tolerance

description: Waterlogging causes germination failure in pea (<em>Pisum sativum</em> L.). Three genotypes (BM-3, NL-2 and Kaspa) contrasting in ability to germinate in waterlogged soil were exposed to different durations of waterlogging. Whole genome RNAseq was employed to capture differentially expressing genes. The ability to germinate in waterlogged soil was associated with testa colour and testa membrane integrity as confirmed by electrical conductivity measurements. Among the most differentially regulated genes, upregulated gene tyrosine protein kinase responsible for metabolic regulation and downregulated LOX5 involved in fat metabolism indicated energy preservation in tolerant Kaspa, while in the other tolerant NL-2 subtilase family protein and PNC2 involved in protein and fat metabolism respectively showed upregulated expression suggesting energy utilization during waterlogging. By contrast, in sensitive genotype BM-3 high upregulation was recorded for the kunitz-type trypsin/protease inhibitor whose role is blocking the activity of protein metabolism leading to excessive lipid metabolism causing membrane leakage and subsequent seed damage. Pathway analyses based on gene ontologies showed seed storage protein metabolism as upregulated in tolerant genotypes and downregulated in the sensitive genotype. Understanding the tolerance mechanism provides a platform to breed for adaptation to waterlogging stress at germination in pea.
description: This is the BM3 dataset. The KSP dataset can be found at 10.5281/zenodo.1250569. The NLL dataset can be found at 10.5281/zenodo.1252493.
description: {"references": ["Zaman, M. S. U., Malik, A. I., Erskine, W., & Kaur, P. (2018). Changes in gene expression during germination reveal pea genotypes with either 'quiescence' or 'escape' mechanisms of waterlogging tolerance. Plant Cell Environ. doi:10.1111/pce.13338"]}
DOI: 10.5281/zenodo.254485
title: Training Material For De Novo Transcriptome Reconstruction From Rna-Seq Data

description: The data provided here are part of a Galaxy tutorial that analyzes RNA-seq data from a study published by Wu et al., 2014 (DOI:10.1101/gr.164830.113). The goal of this study was to investigate "the dynamics of occupancy and the role in gene regulation of the transcription factor Tal1, a critical regulator of hematopoiesis, at multiple stages of hematopoietic differentiation." To this end, RNA-seq libraries were constructed from multiple mouse cell types including G1E - a GATA-null immortalized cell line derived from targeted disruption of GATA-1 in mouse embryonic stem cells - and megakaryocytes. This RNA-seq data was used to determine differential gene expression between G1E and megakaryocytes and later correlated with Tal1 occupancy. This dataset (GEO Accession: GSE51338) consists of biological replicate, paired-end, polyA selected RNA-seq libraries. Because of the long processing time for the large original files, we have downsampled the original raw data files to include only reads that align to chromosome 19 and a subset of interesting genomic loci identified by Wu et al.
description: {"references": ["Afgan, E et al. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. 44, W3\u2013W10 (2016).", "Wu, W et al. Dynamic shifts in occupancy by TAL1 are guided by GATA factors and drive large-scale reprogramming of gene expression during hematopoiesis. 24, 1945\u20131962 (2014)."]}
DOI: 10.5281/zenodo.1069439
title: Glucosinolate and Desulfoglucosinolate NMR Data and Structures

description: <sup>1</sup>H, <sup>13</sup>C, <sup>15</sup>N NMR spectra, NMR parameters, and structures of a set of 31 glucosinolates or desulfoglucosinolates
DOI: 10.5281/zenodo.1202212
title: Duhumbi immaterial culture

description: <strong>Short description: </strong>This collection of videos, audio and photo files displays Duhumbi aspects of immaterial culture between 2012 and 2017. This includes songs and dance, <em>dünchang</em>, <em>mani tam</em> riddles, picnics, stories and tales, and the famous <em>Azhi Lamu</em> dance. All these immaterial cultural practices have seen a rapid decline with the advent of electricity, television and mobile phones to the area. <em>Mani tam</em> are hardly practiced anymore, the longer stories are only told during <em>losar</em>, and more traditional songs and dances during special occasions such as community festivals, marriages and <em>dünchang</em> parties are often quickly replaced by the latest Bollywood hit songs. This material is made freely available to everyone for informative or scientific purposes as long as the source (this DOI) / the collectors are properly credited. Please note that use of the material for commercial purposes <em><strong>of any kind</strong>, which includes conversion into commercial audio-visual media (documentaries etc.), storage and dissemination through sites that require registration & payment for access, or sites that rely on advertisement (including YouTube) </em>is <strong>not</strong> permitted without <strong>specific written consent</strong> from the speakers and their community, obtained through the collectors of the material. By downloading our material, you agree to these restrictions. This data set falls under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license. This license lets you remix, tweak, and build upon this work non-commercially, as long as you credit us and license your new creations under the identical terms. License Deed on https://creativecommons.org/licenses/by-nc-sa/4.0/. Legal Code on https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode. Tim Bodt: bodttim (at) gmail (dot) com
DOI: 10.5281/zenodo.159676
title: Fdm 3D Printing Specimens Scan - Parts A--C

description: Dataset from experiment on infill and printing orientation for its influence on surface quality, object stability and geometrical fidelity. FDM 3D printed specimens ("dogbone") with ABS plastics, scanned on a Canon LiDE 210 scanning device with resolutions between 600 and 4800 DPI. Supplemental Material.
DOI: 10.1594/pangaea.905933
title: Processed Sub Bottom Profiler (SBP) data around Tristan da Cunha

description: Sub bottom profiler (SBP) aka sediment echosounder data. Sediment echosounder measurements were conducted continuously by means of Teledyne PARASOUND DS3 (P70) parametric sediment echosounder during both R/V MARIA S. MERIAN cruises, MSM20-2 (Jegen et al., 2015) and MSM24, until the shutdown of the system due to technical reasons on cruise MSM24. The system's beam width is 4.5° along-track and 5.0° across-track. The primary high frequency signal (PHF) with a frequency of about 18 kHz was recorded for water-column investigations while the secondary low frequency signal (SLF) with a frequency of 4 kHz is used to image the shallow sub-seafloor. This selection of four PARASOUND profiles were converted into SEG-Y data by using the PS32segy tool (Hanno Keil, University of Bremen, Germany). Afterwards, the ReflexW software57 (Sandmeier, 2012) was used to low-pass filter the data and to mute the water column.
DOI: 10.5281/zenodo.1239584
title: Twitter Data Selfies

description: Information for Twitter Data Selfies
DOI: 10.5281/zenodo.1294892
title: Life Events On Twitter

description: This dataset contains tweets about two types of life event: weddings and births of a child.<br>
It is build very unbalanced with the purpose to simulate a social network timeline, in this case a Twitter account. In fact, on someone's timeline is hard to find contents about user's personal wedding or child births.

This dataset contains 5836 tweets, taken from 44 different accounts: 161 about wedding, 135 about a birth of a child.

It has two colums:


	TweetID, which contains the ID of the tweet
	Label, which contains the classification. Possible values:
	
		WEDDING if the post is about a wedding
		BIRTH if the post is about a birth of a child
		NONE if the post is neither about a wedding or a birth of a child
DOI: 10.5281/zenodo.55719
title: Recordings For Loudness Analysis Of The Music Mixes For Comparison Of Wave Field Synthesis, Surround, And Stereo

description: Mat files of live recordings of the music mixes for the comparison of wave field synthesis, surround, and stereo listening test. The recordings were performed at different levels and were analyzed with a loudness model afterwards for adjusting the levels. For details, see

C. Hold, H. Wierstorf, A. Raake, The Difference Between Stereophony and Wave Field Synthesis in the Context of Popular Music, in 140th AES Convention, 2016.
DOI: 10.5281/zenodo.823688
title: Deep Learning Methods For Unsupervised Acoustic Modeling Using Gmm Posteriograms  (System #1)

description: System combination of autoencoder and GMM-DNN features.
DOI: 10.5281/zenodo.4300969
title: Dataset - Lithium content in Indonesia

description: Dataset - Lithium content in Indonesia The following tables contains datasets of Lithium content at various locations in Indonesia. This dataset was compiled from sevaral sources as described in column "Sources".
DOI: 10.5281/zenodo.4525237
title: PharmKG: A Dedicated Knowledge Graph Benchmark for Biomedical Data Mining

description: Biomedical knowledge graphs, which can help with the understanding of complex biological systems and pathologies, have begun to play a critical role in medical practice and research. However, challenges remain in their embedding and use due to their complex nature and the specific demands of their construction. Existing studies often suffer from problems such as sparse and noisy datasets, insufficient modeling methods, and non-uniform evaluation metrics. In this work,<strong> </strong>we established a comprehensive knowledge graph (KG) system for the biomedical field in an attempt to bridge the gap. Here we introduced PharmKG, a multi-relational, attributed biomedical knowledge graph, composed of more than 500,000 individual interconnections between genes, drugs, and diseases, with 29 relation types over a vocabulary of ~8,000 disambiguated entities. Each entity in PharmKG is attached with heterogeneous, domain-specific information obtained from multi-omics data, i.e. gene expression, chemical structure, and disease word embedding while preserving the semantic and biomedical features. For baselines, we offered 9 state-of-the-art knowledge graph embedding (KGE) approaches and a new biological, intuitive, graph neural network-based KGE method that uses a combination of both global network structure and heterogeneous domain features. Based on the proposed benchmark, we conducted extensive experiments to assess these KGE models using multiple evaluation metrics. Finally, we discussed our observations across various downstream biological tasks and provide insights and guidelines for how to use a knowledge graph in biomedicine. We hope that the unprecedented quality and diversity of PharmKG will lead to advances in biomedical knowledge graph construction, embedding, and application.
description: [Update New Version]: We have updated the PharmKG-8k dataset we used in the paper, including the training/validation/test set. If you found this dataset useful for your research, please cite our paper: PharmKG: A Dedicated Knowledge Graph Benchmark for Biomedical Data Mining.
DOI: 10.5281/zenodo.51472
title: Dataset For Anomaly Detection Using Inter-Arrival Curves For Real-Time Systems

description: The dataset shows the input files and detailed results for the experiments discussed in the paper. A README file provide more details on the data.
DOI: 10.5281/zenodo.57523
title: Data Set From Molisan Regional Seismic Network Events

description: Abstract:

<em>After the earthquake occurred in Molise (Central Italy) on 31st October 2002<br>
(Ml 5.4, 29 people dead), the local Servizio Regionale per la Protezione Civile<br>
to ensure a better analysis of local seismic data, through a convention with<br>
the Istituto Nazionale di Geofisica e Vulcanologia (INGV), promoted the design<br>
of the Regional Seismic Network (RMSM) and funded its implementation. The 5<br>
stations of RMSM worked since 2007 to 2013 collecting a large amount of seismic<br>
data and giving an important contribution to the study of seismic sources<br>
present in the region and the surrounding territory. This work reports about<br>
the dataset containing all triggers collected by RMSM since July 2007 to March<br>
2009, including actual seismic events; among them, all earthquakes events<br>
recorded in coincidence to Rete Sismica Nazionale Centralizzata (RSNC) of INGV<br>
have been marked with S and P arrival timestamps. Every trigger has been<br>
associated to a spectrogram defined into a recorded time vs. frequency domain.<br>
The main aim of this structured dataset is to be used for further analysis with<br>
data mining and machine learning techniques on image patterns associated to the<br>
waveforms.</em>

Link arXiv: http://arxiv.org/abs/1607.02607