cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3666920
title: 1000 Disease Ontology terms and their Wikidata mappings to 17 mostly Indian languages and English

description: This dataset contains the result of a SPARQL query run on the Wikidata Query Service on 13 February 2020 around 22:25 UTC. They are archived here as a means to determine progress with the coverage of disease-related terms in languages other than English, particularly in languages of India. The SPARQL query was for Wikidata items for concepts that have a Disease Ontology ID (P699) sorted by number of sitelinks optionally with their Wikidata label in English optionally with their Wikipedia article title in English optionally with their Wikidata label in Hindi, Bangla and Swahili optionally with their Wikidata label in Marathi, Telugu, Eastern Punjabi, Western Punjabi, Gujarathi, Maithili, Kannada, Odia, Bhojpuri, Tamil, Nepali, Urdu, Malayalam, Esperanto is contained in the file SPARQL.txt, whereas the results are available in several formats, as provided by the Wikidata Query Service: query.csv query.tsv<br> query.html query.json.txt (Zenodo produced an error upon trying to upload the file as query.json, so I renamed it, which worked fine). A simplified version of the SPARQL query can also be fed into the TABernacle tool that represents the live data in a way that facilitates editing the missing pieces.
DOI: 10.5281/zenodo.3666921
title: 1000 Disease Ontology terms and their Wikidata mappings to 17 mostly Indian languages and English

description: This dataset contains the result of a SPARQL query run on the Wikidata Query Service on 13 February 2020 around 22:25 UTC. They are archived here as a means to determine progress with the coverage of disease-related terms in languages other than English, particularly in languages of India. The SPARQL query was for Wikidata items for concepts that have a Disease Ontology ID (P699) sorted by number of sitelinks optionally with their Wikidata label in English optionally with their Wikipedia article title in English optionally with their Wikidata label in Hindi, Bangla and Swahili optionally with their Wikidata label in Marathi, Telugu, Eastern Punjabi, Western Punjabi, Gujarathi, Maithili, Kannada, Odia, Bhojpuri, Tamil, Nepali, Urdu, Malayalam, Esperanto is contained in the file SPARQL.txt, whereas the results are available in several formats, as provided by the Wikidata Query Service: query.csv query.tsv<br> query.html query.json.txt (Zenodo produced an error upon trying to upload the file as query.json, so I renamed it, which worked fine). A simplified version of the SPARQL query can also be fed into the TABernacle tool that represents the live data in a way that facilitates editing the missing pieces.
DOI: 10.26300/q3h4-7s93
title: Data for "Constraining Ammonia Emissions in Traffic-Derived Plumes Utilizing Nitrogen Stable Isotopes"
DOI: 10.5281/zenodo.3666933
title: Supplemental Material of Relationships between Economic, Legal, Social, and Global Risks with the Success in International Construction Projects at Caribbean Islands with British Influence

description: Suplemental Material consisting on: 1. Instrument for collecting data and, 2. Survey results of the study.
DOI: 10.6084/m9.figshare.3761562.v1388
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5281/zenodo.3666825
title: Sampling in Software Engineering Research — Supplementary Material

description: Representative sampling appears rare in software engineering research. Not all studies need representative samples, but a general lack of representative sampling undermines a scientific field. This study therefore investigates the state of sampling in recent, high-quality software engineering research. The key findings are: (1) random sampling is rare; (2) sophisticated sampling strategies are very rare; (3) sampling, representativeness and randomness do not appear well-understood. To address these problems, the paper synthesizes existing knowledge of sampling into a succinct primer and proposes extensive guidelines for improving the conduct, presentation and evaluation of sampling in software engineering research. It is further recommended that while researchers should strive for more representative samples, disparaging non-probability sampling is generally capricious and particularly misguided for predominately qualitative research.
DOI: 10.5281/zenodo.3666826
title: Sampling in Software Engineering Research Supplementary Material

description: Representative sampling appears rare in software engineering research. Not all studies need representative samples, but a general lack of representative sampling undermines a scientific field. This study therefore investigates the state of sampling in recent, high-quality software engineering research. The key findings are: (1) random sampling is rare; (2) sophisticated sampling strategies are very rare; (3) sampling, representativeness and randomness do not appear well-understood. To address these problems, the paper synthesizes existing knowledge of sampling into a succinct primer and proposes extensive guidelines for improving the conduct, presentation and evaluation of sampling in software engineering research. It is further recommended that while researchers should strive for more representative samples, disparaging non-probability sampling is generally capricious and particularly misguided for predominately qualitative research.
DOI: 10.5519/qd.unii5tif
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.21227/q89g-6g78
title: GAN based synthesized audios

description: With the development of audio synthesis techniques, the most state-of-art synthesis methods are based on Generative Adversarial Network(GAN)。 To imporve the detection algorithm todiscriminate genuine audio from spoofed audio produced using GAN basedaudio synthesisshcemes, we make this public dataset.
DOI: 10.5281/zenodo.3666936
title: Variation in the microbiota across different developmental stages of Aedes albopictus is affected by ampicillin exposure

description: KEGG Orthology groups predicted for bacteria of different groups
DOI: 10.5281/zenodo.3666935
title: Variation in the microbiota across different developmental stages of Aedes albopictus is affected by ampicillin exposure

description: KEGG Orthology groups predicted for bacteria of different groups
DOI: 10.26182/5e45f60e4a7fd
title: Amborella pangenome
DOI: 10.6084/m9.figshare.11845551.v9
title: Simulated zero-crossing wave period (3-hourly, 150a) from FIO-ESM v2.0 1pctCO2 experiment r1i1p1f1

description: Simulated zero-crossing wave period (3-hourly, 150a) from FIO-ESM v2.0 1pctCO2 experiment (CO2 prescribed to increase at 1% per year) r1i1p1f1, which is branch from Jan 1, 301 of piControl experiment. The grid, named gx1v6, is the displaced pole (the North Pole displaced to the Greenland) grid with 1.1 degree in longitude and 0.27-0.54 degree in latitude.
DOI: 10.6085/aa/cblx00_xxxitv2xlsr03_20190321.40.1
title: (:unkn)
DOI: 10.21227/dqgj-9144
title: Transients and faults in transformer and phase angel regulators

description: The dataset contains internal faults in power transformer and phase angel regulators in an interconnected system. It also has 6 other power system transients which include magnetising inrush, sympathetic inrush, external faults with CT saturation, capacitor switching, non-linear load switching, and ferroresonance. There are 88128 internal fault files and 12780 files of other transient disturbances. The faults and transients are simulated in PSCAD. The files are in text format.
DOI: 10.7910/dvn/fs7746/vsyf32
title: pH_Calculation_20200213.docx

description: pH calculation details
DOI: 10.25403/upresearchdata.12735278
title: Distinguishing between intended and perceived emotions in a 'danced -based' physical theatre perfomance

description: These figures and tables display the data discussed in the dissertation, tilted: "Distinguishing between intended and perceived emotions in a 'dance-based' Physical Theatre performance". The data was collected using a Mobile Application that was specifically designed for this study. The aim of this study was to determine whether audience members could perceive and distinguish three emotions (anger, fear, and disgust) that were portrayed in a 'dance-based' Physical Theatre performance. There were two performances. The first performance consisted of regular theatre goers, and the second performance consisted of non-regular theatre goers. All the audience members were invited to watch and participate in this study.
DOI: 10.25403/upresearchdata.12735278.v1
title: Distinguishing between intended and perceived emotions in a 'danced -based' physical theatre perfomance

description: These figures and tables display the data discussed in the dissertation, tilted: "Distinguishing between intended and perceived emotions in a 'dance-based' Physical Theatre performance". The data was collected using a Mobile Application that was specifically designed for this study. The aim of this study was to determine whether audience members could perceive and distinguish three emotions (anger, fear, and disgust) that were portrayed in a 'dance-based' Physical Theatre performance. There were two performances. The first performance consisted of regular theatre goers, and the second performance consisted of non-regular theatre goers. All the audience members were invited to watch and participate in this study.
DOI: 10.5281/zenodo.3666974
title: Research on the Relationship of Ions Content with TNF-α and TGF-β Expression in BALF of Silica-induced Rats

description: All data of this article.
DOI: 10.5281/zenodo.3666975
title: Research on the Relationship of Ions Content with TNF-α and TGF-β Expression in BALF of Silica-induced Rats

description: All data of this article.
DOI: 10.21227/hdjj-ne38
title: CONFLICT SCENARIOS IN SMART HOMES

description: This is a repository of 104 smart home conflict scenarios, which were designated as conflict by actual human users. In other words, humans consider the scenarios below to be conflicts in a smart home environment. To see how to use this repository, and how the repository was collected, please read the following paper:Fereshteh Jadidi Miandashti, Mohammad Izadi, Ali Asghar Nazari Shirehjini, and Shervin Shirmohammadi, “An Empirical Approach to Modeling User-System Interaction Conflicts in Smart Homes”, IEEE Trans. on Human-Machine Systems, 2020.Please note that the scenarios in our repository help identify what is conflict from the users’ perspective. They do not tell us how to handle those conflicts. In other words, the cases below are about conflict detection, not conflict resolution.This repository can help designers of Smart Homes understand what rules (system behaviors) were perceived by users as conflict, so they can design appropriate conflict detection and conflict resolution modules for their Smart Home system. For example, in one scenario, the user might open the window to let in the fresh air, but the user has forgotten that his pet bird is roaming free in the room and might escape from the window! The system knows the latter fact and closes the window immediately. Our Smart Home users considered this scenario to be a conflict. A designer might come across a scenario similar to this. In this case, the designer can use our repository to (1) understand that his/her scenario, which is very similar to one of the scenarios in our repository, is indeed considered a conflict by smart home users; hence the designer can investigate it subjectively or with some well-known techniques, and (2) design appropriate conflict detection and resolution rules for it in order to increase user satisfaction. Of course, our repository does not contain all possible conflict scenarios in a smart home, but it gives a fairly good starting point.
DOI: 10.25345/c5cx07
title: MassIVE MSV000084955 - GNPS - CCE 2017 Functional Metabolomics (Native Spray - Iron Addition)
title: Function Metabolomics (Native Spray + Metal Addition) of selecteted seawater samples (PPL extracts) from the California Current Ecosystems collected during 1706 LTER cruise.
DOI: 10.17632/frngk6skym.1
title: Data for: Understanding the Government’s Attempt to Transform Attitudes towards a Critical Resource: Gold Monetization in India
DOI: 10.5281/zenodo.3968202
title: SemEval-2020 Task 3: Graded Word Similarity in Contex

description: For this tasks we ask participants to build systems that try to predict the effect that context has in human perception of similarity of words. We have seen very interesting work that uses local context to predict <strong>discrete</strong> changes in meaning: the different senses of a polysemous word. However context also has more subtle, <strong>continuous</strong> (<strong>graded</strong>) effects on meaning, even for words not necessarily considered polysemous. In order to be able to look at these effects we are building several datasets where we ask annotators to score how similar a pair of words are after they have read a short paragraph (which contains the two words). Each pair is scored within two of these paragraphs, allowing us to look at changes in similarity ratings due to context
DOI: 10.5281/zenodo.3666999
title: BE PFM of BiFeO3 film

description: Band excitation piezoresponse force microscopy on epitaxial BiFeO<sub>3</sub> thin film of 100 nm thickness.
DOI: 10.5281/zenodo.3667000
title: BE PFM of BiFeO3 film

description: Band excitation piezoresponse force microscopy on epitaxial BiFeO<sub>3</sub> thin film of 100 nm thickness.
DOI: 10.21227/4dz0-xv55
title: Transfer Learning CNN American Sign Language

description: This dataset contains the images used in the paper "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time". M. E. Morocho Cayamcela and W. Lim, "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time," 2019 International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA, 2019, pp. 100-104.
DOI: 10.21227/mrrt-9b47
title: Transfer Learning CNN American Sign Language

description: This dataset contains the images used in the paper "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time". M. E. Morocho Cayamcela and W. Lim, "Fine-tuning a pre-trained Convolutional Neural Network Model to translate American Sign Language in Real-time," 2019 International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA, 2019, pp. 100-104.
DOI: 10.5281/zenodo.3666991
title: jl_spectra_2_structure dataset

description: This is the dataset for publication "Infrared Spectroscopy Data- and Physics-driven Machine Learning for Characterizing Surface Microstructure of Complex Materials"
DOI: 10.5281/zenodo.3666992
title: jl_spectra_2_structure dataset

description: This is the dataset for publication "Infrared Spectroscopy Data- and Physics-driven Machine Learning for Characterizing Surface Microstructure of Complex Materials"
DOI: 10.7910/dvn/fs7746/wmgq3e
title: pH_Calculation.docx

description: Details of pH calculation
DOI: 10.11577/1599287
title: Viscosity-adjustable grease matrices for serial nanocrystallography

description: Please check the README file for more information about the dataset.
DOI: 10.5519/qd.lygqtmbm
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.7910/dvn/fs7746/emtlvg
title: Calculation of pH for fogcloud droplets.docx

description: Calculation of pH for fogcloud droplets
DOI: 10.6084/m9.figshare.11845551.v11
title: Simulated zero-crossing wave period (3-hourly, 150a) from FIO-ESM v2.0 1pctCO2 experiment r1i1p1f1

description: Simulated zero-crossing wave period (3-hourly, 150a) from FIO-ESM v2.0 1pctCO2 experiment (CO2 prescribed to increase at 1% per year) r1i1p1f1, which is branch from Jan 1, 301 of piControl experiment. The grid, named gx1v6, is the displaced pole (the North Pole displaced to the Greenland) grid with 1.1 degree in longitude and 0.27-0.54 degree in latitude.
DOI: 10.17632/8zz27rhffh.1
title: Fig. 5. FTIR spectrum of the biosurfactant.

description: FTIR spectrum of the biosurfactant.
DOI: 10.17632/47t98n2wkc.1
title: Data for: Monitoring of growth, digestion enzyme activity, immune response and water quality parameters of Golden crucian carp, (Carassius auratus) in zero-water exchange tanks of biofloc systems

description: Basic data
DOI: 10.7910/dvn/fs7746/y0ngfc
title: Calculation of pH for fogcloud droplets.pdf

description: Calculation of pH for fogcloud droplets
DOI: 10.17632/rkykkng499.1
title: Data for: Naturalized flow regime of the regulated Peace River, Canada, during the spring breakup of the ice cover

description: Naturalized flows of the regulated Peace River during the ice breakup period, as observed and as calculated by different methods, are tabulated for the years 1972-2016.
DOI: 10.5281/zenodo.3667019
title: Superárboles de Ezcurra y Nesbitt

description: Dos topologías con relaciones filogenéticas basadas en Ezcurra o Nesbitt (además de varias modificaciones en especies particulares por posiciones controversiales o no estar en ninguna de estas hipótesis).
DOI: 10.5281/zenodo.3667018
title: Superárboles de Ezcurra y Nesbitt

description: Dos topologías con relaciones filogenéticas basadas en Ezcurra o Nesbitt (además de varias modificaciones en especies particulares por posiciones controversiales o no estar en ninguna de estas hipótesis).
DOI: 10.21227/wn80-9232
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.— Number of tweets : 363,755,255 tweets
DOI: 10.17632/dsyxm93ws6.1
title: Data for: Does SNORD116 mediate aspects of psychosis in Prader-Willi syndrome?

description: Anonymized dataset of 540 typically developing individuals genotyped for 5 SNPs within the SNORD116 gene and phenotyped for schizotypal and autism spectrum personality traits. (AQ and SPQ-brief).
DOI: 10.5281/zenodo.3667008
title: GRIST Mesh Files

description: This entry contains the validated GRIST mesh files for daily model development. The quasi-uniform mesh from Grid level 4 to 8 based on icosahedron bisection is presented, from ~4 degree (480 km) to 0.25 degree (30 km). The grid is optimized by the CCVT/SCVT technique.
description: {"references": ["Zhang, Y., J. Li, R. Yu, S. Zhang, Z. Liu, J. Huang, and Y. Zhou, A Layer-Averaged Nonhydrostatic Dynamical Framework on an Unstructured Mesh for Global and Regional Atmospheric Modeling: Model Description, Baseline Evaluation, and Sensitivity Exploration. Journal of Advances in Modeling Earth Systems, 2019. 11(6): p. 1685-1714."]}
DOI: 10.5281/zenodo.3667007
title: GRIST Mesh Files

description: This entry contains the validated GRIST mesh files for daily model development. The quasi-uniform mesh from Grid level 4 to 8 based on icosahedron bisection is presented, from ~4 degree (480 km) to 0.25 degree (30 km). The grid is optimized by the CCVT/SCVT technique.
description: {"references": ["Zhang, Y., J. Li, R. Yu, S. Zhang, Z. Liu, J. Huang, and Y. Zhou, A Layer-Averaged Nonhydrostatic Dynamical Framework on an Unstructured Mesh for Global and Regional Atmospheric Modeling: Model Description, Baseline Evaluation, and Sensitivity Exploration. Journal of Advances in Modeling Earth Systems, 2019. 11(6): p. 1685-1714."]}
DOI: 10.5282/ubm/data.178
title: Cold pool driven convective initiation: using causal graph analysis to determine what convection permitting models are missing

description: The data in this folder comprises all data necessary to produce the Figures presented in our paper (Hirt et al, 2020, in review, Quarterly Journal of the Royal Meteorological Society). Corresponding Jupyter notebooks, which were used to analyse and plot the data, are available at https://github.com/HirtM/cold_pool_driven_convection_initiation. The datasets are netcdf files and should contain all relevant metadata. cp_aggregates2*: These datasets contain different variables of cold pool objects. For each variable, several different statistics are available, e.g. the average/median/some percentile over the area of each cold pool object. Note that the data does not contain tracked cold pools. Any sequence of cold pool indices is hence meaningless. Each cold pool index does not only have information about its cold pool, but also its edges (see mask dimension). P_ci_* These datasets contain information on convection initiation within cold pool areas, cold pool edge areas or no cold pool areas. No single cold pool objects are identified here. prec_* As P_ci_*, but for precipitation. synoptic_conditions_variables.nc This dataset contains domain averaged (total domain, not cold pool objects) timeseries of selected variables. The selected variables were chosen in order to describe the synoptic and diurnal conditions of the days of interest. This dataset is used for the causal regression analysis. All the data here is derived from the ICON-LEM simulation conducted within HDCP2: http://hdcp2.eu/index.php?id=5013 Heinze, R., Dipankar, A., Carbajal Henken, C., Moseley, C., Sourdeval, O., Trömel, S., Xie, X., Adamidis, P., Ament, F., Baars, H., Barthlott, C., Behrendt, A., Blahak, U., Bley, S., Brdar, S., Brueck, M., Crewell, S., Deneke, H., Di Girolamo, P., Evaristo, R., Fischer, J., Frank, C., Friederichs, P., Göcke, T., Gorges, K., Hande, L., Hanke, M., Hansen, A., Hege, H.-C., Hoose, C., Jahns, T., Kalthoff, N., Klocke, D., Kneifel, S., Knippertz, P., Kuhn, A., van Laar, T., Macke, A., Maurer, V., Mayer, B., Meyer, C. I., Muppa, S. K., Neggers, R. A. J., Orlandi, E., Pantillon, F., Pospichal, B., Röber, N., Scheck, L., Seifert, A., Seifert, P., Senf, F., Siligam, P., Simmer, C., Steinke, S., Stevens, B., Wapler, K., Weniger, M., Wulfmeyer, V., Zängl, G., Zhang, D. and Quaas, J. (2016): Large-eddy simulations over Germany using ICON: A comprehensive evaluation. Q.J.R. Meteorol. Soc., doi:10.1002/qj.2947 M.Hirt, 9 Jan 2020
DOI: 10.21227/56w7-hb91
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Below is the quick overview of this dataset.— Number of tweets : 161,502 tweets
DOI: 10.6084/m9.figshare.11845551.v12
title: Simulated zero-crossing wave period (3-hourly, 150a) from FIO-ESM v2.0 1pctCO2 experiment r1i1p1f1

description: Simulated zero-crossing wave period (3-hourly, 150a) from FIO-ESM v2.0 1pctCO2 experiment (CO2 prescribed to increase at 1% per year) r1i1p1f1, which is branch from Jan 1, 301 of piControl experiment. The grid, named gx1v6, is the displaced pole (the North Pole displaced to the Greenland) grid with 1.1 degree in longitude and 0.27-0.54 degree in latitude.