cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/jqeq-zd15
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 11,106,444This dataset includes CSV files which contain the tweet IDs. The tweets have been collected by the LSTM model deployed here at sentiment.live. The model monitors the real-time Twitter feed for corona virus-related tweets. As per the Twitter Developer Policy, it is not possible for me to provide information other than the Tweet IDs (this dataset has been completely re-designed on March 20, 2020, to comply with data sharing policies set by Twitter). Note: This dataset should be solely used for non-commercial research purpose (ignore every other LICENSE category given in this page).Schema of the CSV files: First column: tweet ID, Second column: Sentiment score for the particular tweet.Files details (time: GMT+5:45):corona_tweets_01.csv: 831,327 tweets (March 20, 2020 1:37 AM - March 20, 2020 10:28 AM)corona_tweets_02.csv: 870,924 tweets (March 20, 2020 10:31 AM - March 20, 2020 9:43 PM)corona_tweets_03.csv: 773,729 tweets (March 20, 2020 9:49 PM - March 21, 2020 9:25 AM)corona_tweets_04.csv: 1,233,340 tweets (March 21, 2020 9:27 AM - March 22, 2020 7:46 AM)corona_tweets_05.csv: 1,782,157 tweets (March 22, 2020 7:50 AM - March 23, 2020 9:08 AM)corona_tweets_06.csv: 1,771,295 tweets (March 23, 2020 9:11 AM - March 24, 2020 11:35 AM)corona_tweets_07.csv: 1,479,651 tweets (March 24, 2020 11:42 AM - March 25, 2020 11:43 AM)corona_tweets_08.csv: 1,272,592 tweets (March 25, 2020 11:47 AM - March 26, 2020 12:46 PM)corona_tweets_09.csv: 1,091,429 tweets (March 26, 2020 12:51 PM - March 27, 2020 11:53 AM)To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [1] has been appended as the second column. New databases will be added to this dataset every day. Bookmark this page for further updates. [1] https://textblob.readthedocs.io/en/dev/
DOI: 10.21227/knbw-5s90
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 12,278,457This dataset includes CSV files which contain the tweet IDs. The tweets have been collected by the LSTM model deployed here at sentiment.live. The model monitors the real-time Twitter feed for corona virus-related tweets. As per the Twitter Developer Policy, it is not possible for me to provide information other than the Tweet IDs (this dataset has been completely re-designed on March 20, 2020, to comply with data sharing policies set by Twitter). Note: This dataset should be solely used for non-commercial research purpose (ignore every other LICENSE category given in this page).Schema of the CSV files: First column: tweet ID, Second column: Sentiment score for the particular tweet.Files details (time: GMT+5:45):corona_tweets_01.csv: 831,327 tweets (March 20, 2020 01:37 AM - March 20, 2020 10:28 AM)corona_tweets_02.csv: 870,924 tweets (March 20, 2020 10:31 AM - March 20, 2020 09:43 PM)corona_tweets_03.csv: 773,729 tweets (March 20, 2020 09:49 PM - March 21, 2020 09:25 AM)corona_tweets_04.csv: 1,233,340 tweets (March 21, 2020 09:27 AM - March 22, 2020 07:46 AM)corona_tweets_05.csv: 1,782,157 tweets (March 22, 2020 07:50 AM - March 23, 2020 09:08 AM)corona_tweets_06.csv: 1,771,295 tweets (March 23, 2020 09:11 AM - March 24, 2020 11:35 AM)corona_tweets_07.csv: 1,479,651 tweets (March 24, 2020 11:42 AM - March 25, 2020 11:43 AM)corona_tweets_08.csv: 1,272,592 tweets (March 25, 2020 11:47 AM - March 26, 2020 12:46 PM)corona_tweets_09.csv: 1,091,429 tweets (March 26, 2020 12:51 PM - March 27, 2020 11:53 AM)corona_tweets_10.csv: 1,172,013 tweets (March 27, 2020 11:56 AM - March 28, 2020 01:59 PM)To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [1] has been appended as the second column. New databases will be added to this dataset every day. Bookmark this page for further updates. [1] https://textblob.readthedocs.io/en/dev/
DOI: 10.5281/zenodo.3686671
title: User Stories made by Users Workshop Data Set

description: In order to enable members of a socio-technical evolutionary-teal organization to design their technical component, we conducted a workshop that structures the collaboration between technical trained participants and non-trained participants. The workshop aims to transform "vague needs" into technical descriptions in the form of user stories. The workshop is the second part of series of workshops all limited to two hours. It uses the methods of <em>Design Thinking</em> and <em>Participatory Design</em>. The workshop has been recorded in video and this data set contains a textual German transcript, transcripts of the moderation cards that have been created during the workshop, invitations of the participants, additional material needed to conduct the workshop (timetable, moderation concept, etc.), and material used during the workshop by the participants (leaflets, slides, etc.). We hope that the material can be used to (a) comprehend the interpretation used in our qualitative research, (b) to adapt the workshop model by other volunteers of our case study Viva con Agua de St. Pauli e.V. (https://www.vivaconagua.org/), and (c) investigate other interesting research questions.
description: Sometimes the data will contain the term "WASHEthno". This is an internal short name for the study that produces this workshop and thus also the current data.
DOI: 10.5281/zenodo.3731927
title: Forest structure database for plantation forests over China-CPSDv0

description: A country-wide synthetic structure database for plantation forests over China was developed by surveying more than 600 peer-reviewed literatures using a meta-analysis protocol. This new database covers tree species, mean tree age, mean tree height, stand density, canopy coverage, diameter at breast height, as well as the associated ancillary <em>in-situ</em> topographical and soil properties. Totally 594 published studies concerning diverse forest structure parameters were compiled for 46 tree species over China. For the convenience of users, the data is stored in the format of EXCEL, and the file name is CPSDv0-final.xlsx. Blanks in the EXCEL file indicate no available records.
DOI: 10.25345/c57t33
title: MassIVE MSV000085178 - GNPS-MSMS-Chooser-[PF076-01-95]
title: Subset of pure isolated natural products isolated by Pierre-Fabre laboratories from diverse plant species
DOI: 10.5281/zenodo.3731935
title: Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants

description: original daily data for 'Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants'
DOI: 10.5281/zenodo.3731936
title: Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants

description: original daily data for 'Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants'
DOI: 10.5281/zenodo.3724679
title: The effect of renewable and nuclear energy consumption on decoupling economic growth from CO2 emissions in Spain

description: This study examines the relationship between renewable and nuclear energy consumption, carbon dioxide emissions and economic growth by using the Granger causality and non-linear impulse response function in a business cycle in Spain. We estimate the threshold vector autoregression (TVAR) model on the basis of annual data from the period 1970‒2018, which are disaggregated into quarterly data. Our analysis reveals that economic growth and CO<sub>2</sub> emissions are positively correlated during expansions but not during recessions. Moreover, we find that rising nuclear energy consumption leads to decreased CO<sub>2</sub> emissions during expansions, while the impact of increasing renewable energy consumption on emissions is negative but insignificant. In addition, there is a positive feedback between nuclear energy consumption and economic growth, but unidirectional positive causality running from renewable energy consumption to economic growth in upturns. Our findings do indicate that both nuclear and renewable energy consumption contribute to a reduction in emissions; however, the rise in economic activity, leading to a greater increase in emissions, offsets this positive impact of green energy. Therefore, a decoupling of economic growth from CO<sub>2</sub> emissions is not observed. These results demand some crucial changes in legislation targeted at reducing emissions, as green energy alone is insufficient to reach this goal.
DOI: 10.5281/zenodo.3724680
title: The effect of renewable and nuclear energy consumption on decoupling economic growth from CO2 emissions in Spain

description: This study examines the relationship between renewable and nuclear energy consumption, carbon dioxide emissions and economic growth by using the Granger causality and non-linear impulse response function in a business cycle in Spain. We estimate the threshold vector autoregression (TVAR) model on the basis of annual data from the period 1970‒2018, which are disaggregated into quarterly data. Our analysis reveals that economic growth and CO<sub>2</sub> emissions are positively correlated during expansions but not during recessions. Moreover, we find that rising nuclear energy consumption leads to decreased CO<sub>2</sub> emissions during expansions, while the impact of increasing renewable energy consumption on emissions is negative but insignificant. In addition, there is a positive feedback between nuclear energy consumption and economic growth, but unidirectional positive causality running from renewable energy consumption to economic growth in upturns. Our findings do indicate that both nuclear and renewable energy consumption contribute to a reduction in emissions; however, the rise in economic activity, leading to a greater increase in emissions, offsets this positive impact of green energy. Therefore, a decoupling of economic growth from CO<sub>2</sub> emissions is not observed. These results demand some crucial changes in legislation targeted at reducing emissions, as green energy alone is insufficient to reach this goal.
DOI: 10.15468/6kmquj
title: Dolichogenidea fernandeztrianai sp. nov. (Hymenoptera: Braconidae, Microgastrinae) from Iran

description: This dataset contains the digitized treatments in Plazi based on the original journal article Abdoli, P., Talebi, A. A., Farahani, S. (2019): Dolichogenidea fernandeztrianai sp. nov. (Hymenoptera: Braconidae, Microgastrinae) from Iran. J. Agr. Sci. Tech. 21 (3): 647-658, DOI: http://doi.org/10.5281/zenodo.3732008
DOI: 10.15468/qs9far
title: First Record Of Pseudepipona Kazenasi Kurzenko, 1974 (Hymenoptera: Vespidae) From Mongolia

description: This dataset contains the digitized treatments in Plazi based on the original journal article Abasheev, R. Yu. (2019): First Record Of Pseudepipona Kazenasi Kurzenko, 1974 (Hymenoptera: Vespidae) From Mongolia. Far Eastern Entomologist 397: 13-15, DOI: 10.25221/fee.397.3
DOI: 10.15468/sgm2sp
title: Another Angolan Namib endemic species: a new Nucras Gray, 1838 (Squamata: Lacertidae) from south-western Angola

description: This dataset contains the digitized treatments in Plazi based on the original journal article Branch, William R., Conradie, Werner, Pinto, Pedro Vaz, Tolley, Krystal A. (2019): Another Angolan Namib endemic species: a new Nucras Gray, 1838 (Squamata: Lacertidae) from south-western Angola. Amphibian & Reptile Conservation 13 (2): 82-95, DOI: http://doi.org/10.5281/zenodo.3731977
DOI: 10.5281/zenodo.3732020
title: Datos ambientales, tamaños cerebros, script Proyecto FONDECYT 1170815

description: Bases de datos ambientales, poligonos de distribución, tamaños cerebrales recopilados durante el proyecto Fondecyt 1170815
DOI: 10.5281/zenodo.3732021
title: Datos ambientales, tamaños cerebros, script Proyecto FONDECYT 1170815

description: Bases de datos ambientales, poligonos de distribución, tamaños cerebrales recopilados durante el proyecto Fondecyt 1170815
DOI: 10.5281/zenodo.3725790
title: Dataset - Learning to Measure Static Friction Coefficient in Cloth Contact

description: Dataset for: Learning to Measure the Static Friction Coefficient in Cloth Contact
DOI: 10.5281/zenodo.3725791
title: Dataset - Learning to Measure Static Friction Coefficient in Cloth Contact

description: Dataset for: Learning to Measure the Static Friction Coefficient in Cloth Contact
DOI: 10.21227/a7ac-9d53
title: This is a Test of the System

description: Hello World
DOI: 10.21227/rd3n-dh28
title: This is a Test of the System

description: Hello World
DOI: 10.21227/spv3-vc39
title: This is a Test of the System

description: Hello World
DOI: 10.21227/6wf6-0923
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 12,278,457This dataset includes CSV files which contain the tweet IDs. The tweets have been collected by the LSTM model deployed here at sentiment.live. The model monitors the real-time Twitter feed for corona virus-related tweets. As per the Twitter Developer Policy, it is not possible for me to provide information other than the Tweet IDs (this dataset has been completely re-designed on March 20, 2020, to comply with data sharing policies set by Twitter). Note: This dataset should be solely used for non-commercial research purpose (ignore every other LICENSE category given in this page).Schema of the CSV files: First column: tweet ID, Second column: Sentiment score for the particular tweet.Files details (time: GMT+5:45):corona_tweets_01.csv: 831,327 tweets (March 20, 2020 01:37 AM - March 20, 2020 10:28 AM)corona_tweets_02.csv: 870,924 tweets (March 20, 2020 10:31 AM - March 20, 2020 09:43 PM)corona_tweets_03.csv: 773,729 tweets (March 20, 2020 09:49 PM - March 21, 2020 09:25 AM)corona_tweets_04.csv: 1,233,340 tweets (March 21, 2020 09:27 AM - March 22, 2020 07:46 AM)corona_tweets_05.csv: 1,782,157 tweets (March 22, 2020 07:50 AM - March 23, 2020 09:08 AM)corona_tweets_06.csv: 1,771,295 tweets (March 23, 2020 09:11 AM - March 24, 2020 11:35 AM)corona_tweets_07.csv: 1,479,651 tweets (March 24, 2020 11:42 AM - March 25, 2020 11:43 AM)corona_tweets_08.csv: 1,272,592 tweets (March 25, 2020 11:47 AM - March 26, 2020 12:46 PM)corona_tweets_09.csv: 1,091,429 tweets (March 26, 2020 12:51 PM - March 27, 2020 11:53 AM)corona_tweets_10.csv: 1,172,013 tweets (March 27, 2020 11:56 AM - March 28, 2020 01:59 PM)To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [1] has been appended as the second column. New databases will be added to this dataset every day. Bookmark this page for further updates. [1] https://textblob.readthedocs.io/en/dev/
DOI: 10.15468/hy8wnh
title: Protected Areas - Global Register of Introduced and Invasive Species - Garden Route National Park, South Africa

description: The Protected Areas -Global Register of Introduced and Invasive Species (PA-GRIIS) presents validated checklists of introduced (alien) and invasive alien species at a site level. The primary intention of PA-GRIIS is to provide checklists of introduced (alien) and invasive species present on designated protected areas (such as National Parks, Ramsar sites- Wetlands of International importance, World Heritage Sites (natural and mixed), Marine protected areas etc.) and other areas of biodiversity significance (such as Important Plant Areas (IPA), Important Bird Areas (IBA) etc.), as well as buffer zones around these areas. Areas surrounding protected areas and other areas of high biodiversity significance can serve as an invasion source of alien and invasive species propagules. The establishment of buffer zones and the management of alien and invasive species within these areas is a key management strategy in the prevention of introduction and control/management of biological invasions. In the case of islands buffer zones. Checklists are living entities, especially for biological invasions given the growing nature of the problem. PA -GRIIS checklists are based on the GRIIS published methodology (Pagad et al 2018) and supported by the Integrated Publishing Tool of the Global Biodiversity Information Infrastructure (GBIF) that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the PA -GRIIS project will present close to 100 exemplar checklists of introduced (alien) and invasive species in a selection of protected areas and other areas of biodiversity significance This annotated checklist is of introduced (alien) and invasive alien species known to occur in the nationally designated Garden Route National Park, South Africa
DOI: 10.5281/zenodo.3732034
title: COVID-19 vaccine candidates: Prediction and validation of 174 novel SARS-CoV-2 epitopes

description: Datasets used in "COVID-19 vaccine candidates: Prediction and validation of 174 novel SARS-CoV-2 epitopes" SARS-CoV-2 peptides predicted to be binders to 11 HLA allotypes. Selected peptides have been measured in a stability assay revealing potential SARS-CoV-2 vaccine targets. File containing all predictions from tested tools. (Please note that not all tools use same measure.)
DOI: 10.15468/bg1jte
title: Protected Areas - Global Register of Introduced and Invasive Species - Golden Gate Highlands National Park, South Africa

description: The Protected Areas -Global Register of Introduced and Invasive Species (PA-GRIIS) presents validated checklists of introduced (alien) and invasive alien species at a site level. The primary intention of PA-GRIIS is to provide checklists of introduced (alien) and invasive species present on designated protected areas (such as National Parks, Ramsar sites- Wetlands of International importance, World Heritage Sites (natural and mixed), Marine protected areas etc.) and other areas of biodiversity significance (such as Important Plant Areas (IPA), Important Bird Areas (IBA) etc.), as well as buffer zones around these areas. Areas surrounding protected areas and other areas of high biodiversity significance can serve as an invasion source of alien and invasive species propagules. The establishment of buffer zones and the management of alien and invasive species within these areas is a key management strategy in the prevention of introduction and control/management of biological invasions. In the case of islands buffer zones. Checklists are living entities, especially for biological invasions given the growing nature of the problem. PA -GRIIS checklists are based on the GRIIS published methodology (Pagad et al 2018) and supported by the Integrated Publishing Tool of the Global Biodiversity Information Infrastructure (GBIF) that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the PA -GRIIS project will present close to 100 exemplar checklists of introduced (alien) and invasive species in a selection of protected areas and other areas of biodiversity significance This annotated checklist is of introduced (alien) and invasive alien species known to occur in the nationally designated Golden Gate Highlands National Park, South Africa
DOI: 10.15468/ehko7c
title: Protected Areas - Global Register of Introduced and Invasive Species - Kalahari Gemsbok National Park, South Africa

description: The Protected Areas -Global Register of Introduced and Invasive Species (PA-GRIIS) presents validated checklists of introduced (alien) and invasive alien species at a site level. The primary intention of PA-GRIIS is to provide checklists of introduced (alien) and invasive species present on designated protected areas (such as National Parks, Ramsar sites- Wetlands of International importance, World Heritage Sites (natural and mixed), Marine protected areas etc.) and other areas of biodiversity significance (such as Important Plant Areas (IPA), Important Bird Areas (IBA) etc.), as well as buffer zones around these areas. Areas surrounding protected areas and other areas of high biodiversity significance can serve as an invasion source of alien and invasive species propagules. The establishment of buffer zones and the management of alien and invasive species within these areas is a key management strategy in the prevention of introduction and control/management of biological invasions. In the case of islands buffer zones. Checklists are living entities, especially for biological invasions given the growing nature of the problem. PA -GRIIS checklists are based on the GRIIS published methodology (Pagad et al 2018) and supported by the Integrated Publishing Tool of the Global Biodiversity Information Infrastructure (GBIF) that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the PA -GRIIS project will present close to 100 exemplar checklists of introduced (alien) and invasive species in a selection of protected areas and other areas of biodiversity significance This annotated checklist is of introduced (alien) and invasive alien species known to occur in the nationally designated Kalahari Gemsbok National Park, South Africa
DOI: 10.15468/xo0zad
title: Protected Areas - Global Register of Introduced and Invasive Species - Karoo National Park, South Africa

description: The Protected Areas -Global Register of Introduced and Invasive Species (PA-GRIIS) presents validated checklists of introduced (alien) and invasive alien species at a site level. The primary intention of PA-GRIIS is to provide checklists of introduced (alien) and invasive species present on designated protected areas (such as National Parks, Ramsar sites- Wetlands of International importance, World Heritage Sites (natural and mixed), Marine protected areas etc.) and other areas of biodiversity significance (such as Important Plant Areas (IPA), Important Bird Areas (IBA) etc.), as well as buffer zones around these areas. Areas surrounding protected areas and other areas of high biodiversity significance can serve as an invasion source of alien and invasive species propagules. The establishment of buffer zones and the management of alien and invasive species within these areas is a key management strategy in the prevention of introduction and control/management of biological invasions. In the case of islands buffer zones. Checklists are living entities, especially for biological invasions given the growing nature of the problem. PA -GRIIS checklists are based on the GRIIS published methodology (Pagad et al 2018) and supported by the Integrated Publishing Tool of the Global Biodiversity Information Infrastructure (GBIF) that jointly enable ongoing improvements and updates to expand their taxonomic coverage and completeness. Phase 1 of the PA -GRIIS project will present close to 100 exemplar checklists of introduced (alien) and invasive species in a selection of protected areas and other areas of biodiversity significance This annotated checklist is of introduced (alien) and invasive alien species known to occur in the nationally designated Karoo National Park, South Africa