cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/9dea9n
title: A new species of Rhododendron (Ericaceae) from Guizhou, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Dai, Xiao-Yong, Yang, Cheng-Hua, Yang, Bing, Chen, Pu, Ma, Yong-Peng (2020): A new species of Rhododendron (Ericaceae) from Guizhou, China. PhytoKeys 146: 53-59, DOI: http://dx.doi.org/10.3897/phytokeys.146.51342, URL: http://dx.doi.org/10.3897/phytokeys.146.51342
DOI: 10.21227/azzm-6z81
title: Corona Virus (COVID-19) Geolocation-based Sentiment Data

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation data was extracted from the tweets which mentioned anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". Complying with Twitter's data sharing 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 with an exact location that contained any of the previously mentioned keywords.Note: I started sharing the IDs of the tweets that contained the exact location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs (above 50 million tweets) shared in the Corona Virus (COVID-19) Tweets dataset.If you need the geolocation-based data starting March 20, 2020, then use the Corona Virus (COVID-19) Tweets dataset and hydrate the IDs while adding the following condition:if data["coordinates"] is true; use longitude, latitude = data["coordinates"]["coordinates"]The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-april29.* will contain tweet ID and sentiment data of the tweets that were tweeted between April 28, 2020, and April 29, 2020.
DOI: 10.15468/akbkg3
title: A new species and a new record of Liparis sect. Decumbentes (Malaxidinae, Orchidaceae) from Peru

description: This dataset contains the digitized treatments in Plazi based on the original journal article Damian, Alexander, Salazar, Gerardo A., Rimarachin, Leyda (2020): A new species and a new record of Liparis sect. Decumbentes (Malaxidinae, Orchidaceae) from Peru. PhytoKeys 146: 37-46, DOI: http://dx.doi.org/10.3897/phytokeys.146.47229, URL: http://dx.doi.org/10.3897/phytokeys.146.47229
DOI: 10.15468/dc28xw
title: Jasminum parceflorum (Oleaceae), a new species from southern Yunnan, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Zhang, Kai, Wu, Mingsong, Pan, Bo, Zhou, Lianxuan, Zhang, Dianxiang (2020): Jasminum parceflorum (Oleaceae), a new species from southern Yunnan, China. PhytoKeys 146: 109-115, DOI: http://dx.doi.org/10.3897/phytokeys.146.49625, URL: http://dx.doi.org/10.3897/phytokeys.146.49625
DOI: 10.15468/rszdkk
title: Gymnosiphon syceorosensis (Burmanniaceae), the second new species for the Philippines

description: This dataset contains the digitized treatments in Plazi based on the original journal article Nickrent, Daniel L. (2020): Gymnosiphon syceorosensis (Burmanniaceae), the second new species for the Philippines. PhytoKeys 146: 71-87, DOI: http://dx.doi.org/10.3897/phytokeys.146.48321, URL: http://dx.doi.org/10.3897/phytokeys.146.48321
DOI: 10.15468/sv9n33
title: A new species of Eriobotrya (Rosaceae) from Yunnan Province, China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Chen, Su-Fang, Meng, Kai-Kai, Guo, Xi-Bing, Zhao, Wan-Yi, Liao, Wen-Bo, Fan, Qiang (2020): A new species of Eriobotrya (Rosaceae) from Yunnan Province, China. PhytoKeys 146: 61-69, DOI: http://dx.doi.org/10.3897/phytokeys.146.50728, URL: http://dx.doi.org/10.3897/phytokeys.146.50728
DOI: 10.15468/vxw26g
title: Michaelmoelleria (Gesneriaceae), a new lithophilous dwelling genus and species with zigzag corolla tube from southern Vietnam

description: This dataset contains the digitized treatments in Plazi based on the original journal article Wen, Fang, Xin, Zi-Bing, Fu, Long-Fei, Li, Shu, Su, Lan-Ying, Maciejewski, Stephen, Huang, Zhang-Jie, Do, Truong Van, Wei, Yi-Gang (2020): Michaelmoelleria (Gesneriaceae), a new lithophilous dwelling genus and species with zigzag corolla tube from southern Vietnam. PhytoKeys 146: 89-107, DOI: http://dx.doi.org/10.3897/phytokeys.146.49731, URL: http://dx.doi.org/10.3897/phytokeys.146.49731
DOI: 10.15468/cuvqm4
title: Lectotypification of the name Melastoma candidum f. albiflorum and its taxonomic status

description: This dataset contains the digitized treatments in Plazi based on the original journal article Zhang, Xinjian, Dai, Jin-Hong, Liu, Xiaozhou, Li, Zihua, Lee, Shiou Yih, Zhou, Renchao, Tan, Guangwen (2020): Lectotypification of the name Melastoma candidum f. albiflorum and its taxonomic status. PhytoKeys 146: 47-52, DOI: http://dx.doi.org/10.3897/phytokeys.146.49929, URL: http://dx.doi.org/10.3897/phytokeys.146.49929
DOI: 10.5519/qd.82t7wzf3
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1001 records)
DOI: 10.34725/dvn/doskis/pfplih
title: CleanedSeedlingDistributionSurvivalData.xlsx

description: Cleaned Data and Documentation for Survival Data 2019
DOI: 10.34725/dvn/doskis/7feakf
title: MergedDataFoodTreesEndline_Diversity2019.xlsx

description: Merged and Cleaned Data for Food Trees Diversity Data and End-line Data 2019
DOI: 10.34725/dvn/doskis/gqamxl
title: Cleaned2019DiversityData.xlsx

description: Cleaned Data and Documentation for Food Trees Diversity Data 2019
DOI: 10.34725/dvn/doskis/uzuzs4
title: FoodTreesDiversityRichnessAnalysis2019.Rmd

description: R Script for Cleaning Food Trees Diversity Data
DOI: 10.21227/gqj6-ph42
title: Corona Virus (COVID-19) Geolocation-based Sentiment Data

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation data was extracted from the tweets which mentioned anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". Complying with Twitter's data sharing 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 with an exact location that contained any of the previously mentioned keywords.Note: I started sharing the IDs of the tweets that contained the exact location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs (above 50 million tweets) shared in the Corona Virus (COVID-19) Tweets dataset.If you need the geolocation-based data starting March 20, 2020, then use the Corona Virus (COVID-19) Tweets dataset and hydrate the IDs while adding the following condition:data = json.loads(data) if data["coordinates"]: longitude, latitude = data["coordinates"]["coordinates"]The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-april29.* will contain tweet ID and sentiment data of the tweets that were tweeted between April 28, 2020, and April 29, 2020.
DOI: 10.5519/qd.gh6rrvow
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.3819025
title: Simple Dataset for Proof Method Recommendation in Isabelle/HOL

description: Recently, a growing number of researchers have applied machine learning to assist users of interactive theorem provers. However, the expressive nature of underlying logics and esoteric structures of proof documents impede machine learning practitioners, who often do not have much expertise in formal logic, let alone Isabelle/HOL, from applying their tools and expertise to theorem proving. In this data description, we present a simple dataset that contains data on over 400k proof method applications in the Archive of Formal Proofs along with over 100 extracted features for each in a format that can be processed easily without any knowledge about formal logic. Our simple data format allows machine learning practitioners to try machine learning tools to predict proof methods in Isabelle/HOL, even if they are unfamiliar with theorem proving.
description: The corresponding dataset description paper is under review at the 13th Conference on Intelligent Computer Mathematics (CICM2020). The preprint is available at arXiv.org (https://arxiv.org/abs/2004.10667)
DOI: 10.5281/zenodo.3819026
title: Simple Dataset for Proof Method Recommendation in Isabelle/HOL

description: Recently, a growing number of researchers have applied machine learning to assist users of interactive theorem provers. However, the expressive nature of underlying logics and esoteric structures of proof documents impede machine learning practitioners, who often do not have much expertise in formal logic, let alone Isabelle/HOL, from applying their tools and expertise to theorem proving. In this data description, we present a simple dataset that contains data on over 400k proof method applications in the Archive of Formal Proofs along with over 100 extracted features for each in a format that can be processed easily without any knowledge about formal logic. Our simple data format allows machine learning practitioners to try machine learning tools to predict proof methods in Isabelle/HOL, even if they are unfamiliar with theorem proving.
description: The corresponding dataset description paper is under review at the 13th Conference on Intelligent Computer Mathematics (CICM2020). The preprint is available at arXiv.org (https://arxiv.org/abs/2004.10667)
DOI: 10.5519/qd.0lfd92bn
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1212 records)
DOI: 10.5519/qd.gwsjuslm
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (845 records)
DOI: 10.25919/5eb8bca5c02d5
title: Parkes observations for project PX500 semester 2020APRS_01

description: This proposal relates to time purchased by the Chinese Academy of Sciences for Parkes follow-up confirmation and timing of FAST discoveries. As the observing time has been purchased this proposal (and the related PX501) does not require TAC grading. The primary reason for submitting a proposal is to ensure an outreach statement and that the proposal is entered into OPAL for the data archive to access. The Chinese team have two time requests. The time scheduled for the first, relating to this proposal, will be allocated in blocks of 24 hours and the data will become available in the data archive with an 18 month embargo period. The second type of time will be scheduled in shorter blocks and the data archived with a 10 year embargo.
DOI: 10.3886/e119367
title: Replication data for: Public Goods Provision and Sanctioning in Privileged Groups

description: In public-good provision, privileged groups enjoy the advantage that some of their members find it optimal to supply a positive amount of the public good. However, the inherent asymmetric nature of these groups may make the enforcement of cooperative behavior through informal sanctioning harder to accomplish. In this article, the authors experimentally investigate public-good provision in normal and privileged groups with and without decentralized punishment. The authors find that compared to normal groups, privileged groups are relatively ineffective in using costly sanctions to increase everyone's contributions. Punishment is less targeted toward strong free riders, and they exhibit a weaker increase in contributions after being punished. Thus, the authors show that privileged groups are not as privileged as they initially seem.
DOI: 10.3886/e119367v1
title: Replication data for: Public Goods Provision and Sanctioning in Privileged Groups

description: In public-good provision, privileged groups enjoy the advantage that some of their members find it optimal to supply a positive amount of the public good. However, the inherent asymmetric nature of these groups may make the enforcement of cooperative behavior through informal sanctioning harder to accomplish. In this article, the authors experimentally investigate public-good provision in normal and privileged groups with and without decentralized punishment. The authors find that compared to normal groups, privileged groups are relatively ineffective in using costly sanctions to increase everyone's contributions. Punishment is less targeted toward strong free riders, and they exhibit a weaker increase in contributions after being punished. Thus, the authors show that privileged groups are not as privileged as they initially seem.
DOI: 10.25919/5eb8c1afc4174
title: Parkes observations for project P1052 semester 2020APRS_01

description: After five decades of study, the physics of radio wave emission and propagation in the pulsar magnetosphere remains poorly understood. This is largely due to the wide variety of dynamic phenomena observed in pulsar signals that are neither predicted nor explained by current theory, the limited window of the pulsar spectrum that previously could be studied simultaneously, and the biased sample of the pulsar population that has been studied to date. To address these limitations, we have developed pioneering statistical methods that provide new interpretive insights and enable us to study the dynamics of the radio pulsar signal on short time scales (e.g. drifting and quasi-periodic sub-pulse structure, transitions between orthogonally polarized modes of emission, nulling, etc.) even when individual pulses cannot be detected. Using our novel methods and the ultra-wide bandwidth receiver at Parkes, we will undertake a large-scale survey of pulsar radio emission statistics and explore two previously inaccessible regions where pulsar flux densities are typically much lower: the pulsar spectrum above 2 GHz, and the recycled pulsar population. Measuring the instantaneous bandwidth of impulsive emission events will yield new constraints on the physical conditions in the pulsar magnetosphere, such as the spatial scale of strong turbulence in the magnetospheric plasma. The breadth of our sample, from millisecond pulsars to magnetars, will enable us to study the evolution of emission and propagation physics over four orders of magnitude in magnetospheric size and seven orders of magnitude in magnetic field strength.
DOI: 10.25919/5eb8c26bca28c
title: Parkes observations for project P885 semester 2020APRS_03

description: We propose to observe the magnetars 1E 1547.0-5408 and PSR J1622-4950 approximately weekly, to track their rotation, flux density, and polarisation, as we have long been doing through this project. The revolutionary UWL capabilities promise new opportunities to disentangle still mysterious radio emission mechanisms in magnetars. This promise is supported by the recent follow up of XTE J1810-197, again a radio magnetar after 10 years dormant, for which our observations with the UWL receiver are providing unique and tantalizing measurements of its radio spectrum and polarisation.
DOI: 10.25345/c5211v
title: MassIVE MSV000085392 - HE_piericidin_5_strains_plus_F2_plus_medium
title: The samples were obtained from 5 potential piericidin actinomyces by acetone extracting. The sample F2 is a pure compound isolated from the 00300 strain with MW 460 [M+H]+
DOI: 10.21227/xtsr-en30
title: Corona Virus (COVID-19) Geolocation-based Sentiment Data

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation data was extracted from the tweets which mentioned anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". Complying with Twitter's data sharing 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 with an exact location that contained any of the previously mentioned keywords.Note: I started sharing the IDs of the tweets that contained the exact location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs (above 50 million tweets) shared in the Corona Virus (COVID-19) Tweets dataset.If you need the geolocation-based data starting March 20, 2020, then use the Corona Virus (COVID-19) Tweets dataset and hydrate the IDs while adding the following condition:data = json.loads(data) if data["coordinates"]: longitude, latitude = data["coordinates"]["coordinates"]The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-april29.* will contain tweet ID and sentiment data of the tweets that were tweeted between April 28, 2020, and April 29, 2020.
DOI: 10.3886/e114723v1-24257
title: Replication data for: Who Really Benefits from Consumption Tax Cuts? Evidence from a Large VAT Reform in France

description: This paper evaluates the incidence of a large cut in value-added taxes (VATs) for French sit-down restaurants in 2009. In contrast to previous studies, which only focus on the price effects of VAT reforms, we estimate the effects of the VAT cut on four groups: workers, firm owners, consumers, and suppliers of material goods. Using a difference-in-differences strategy on firm-level data, we find that: firm owners pocketed more than 55 percent of the VAT cut; consumers, sellers of material goods, and employees shared the remaining windfall with consumers benefiting the least; and the employment effects were limited.
DOI: 10.3886/e119361
title: Public communication by research institutes compared across countries and sciences

description: Leading academic institutions, governments, and funders of research across the world have spent the last few decades fretting publicly about the need for scientists and research organisations to engage more widely with the public and be open about their research. While a global literature asserts that public communication has changed from a virtue to a duty for scientists in many countries and disciplines, our knowledge about what research institutions are doing and what factors drive their ‘going public’ is very limited. Here we present the first cross-national study of N=2,030 research institutes within universities and large scientific organisations in Brazil, Germany, Italy, Japan, the Netherlands, Portugal, the United Kingdom, and the United States of America. We find that institutes embrace communication with non-peers and do so through a variety of public events and traditional news media – less so through new media channels – and we find variation across countries and sciences, yet these are less evident than we expected. Country and disciplinary cultures contribute to the level of this communication, as do the resources that institutes make available for the effort; institutes with professionalised staff show higher activity online. Future research should examine whether a real change in the organisational culture is happening or whether this activity and resource allocation is merely a means to increase institutional visibility.
DOI: 10.3886/e119361v1
title: Public communication by research institutes compared across countries and sciences

description: Leading academic institutions, governments, and funders of research across the world have spent the last few decades fretting publicly about the need for scientists and research organisations to engage more widely with the public and be open about their research. While a global literature asserts that public communication has changed from a virtue to a duty for scientists in many countries and disciplines, our knowledge about what research institutions are doing and what factors drive their ‘going public’ is very limited. Here we present the first cross-national study of N=2,030 research institutes within universities and large scientific organisations in Brazil, Germany, Italy, Japan, the Netherlands, Portugal, the United Kingdom, and the United States of America. We find that institutes embrace communication with non-peers and do so through a variety of public events and traditional news media – less so through new media channels – and we find variation across countries and sciences, yet these are less evident than we expected. Country and disciplinary cultures contribute to the level of this communication, as do the resources that institutes make available for the effort; institutes with professionalised staff show higher activity online. Future research should examine whether a real change in the organisational culture is happening or whether this activity and resource allocation is merely a means to increase institutional visibility.
DOI: 10.5281/zenodo.3818347
title: UPLC-QTOF/MS non-targeted metabolomic data of male Eucommia ulmoides Oliv. flower core collections

description: The upload files include five xlsx. worksheets,respectively,the metabolite annotations and peak intensities in samples under ESI+ & ESI- mode,the normalized ion intensity matrix under the ESI+ & ESI- mode and the list of voucher specimen samples for 22 male<em> E. ulmoides</em> flower core collections.
DOI: 10.21227/3r4e-ch18
title: Data of heating meters from residential buildings in Tomsk (Russia) for statistical modeling of the thermal characteristics of buildings

description: The large variability of system and types of heating load is a feature of the commercial metering of thermal energy. Heating consumption depends on many factors, for example, wall and roof material, floors number, system (opened and closed) etc. The daily data from heating meters in the residential buildings are presented in this dataset for comparing the thermal characteristics. These data are supplemented by floors number, wall material and year of construction, as well as data on average daily outdoor temperatures. Energy consumed by the building during the heating season may be an indicator of the heating supply of building. At the fixed comfortable temperature inside rooms (24 Celsius degrees) the thermal energy consumed by the building was measured. The smaller one, the better a quality of thermal protection, and the more efficiency of heating. This statistics can be useful for management to increase the energy efficiency of residential buildings.
DOI: 10.21227/55jf-9v60
title: Data of heating meters from residential buildings in Tomsk (Russia) for statistical modeling of the thermal characteristics of buildings

description: The large variability of system and types of heating load is a feature of the commercial metering of thermal energy. Heating consumption depends on many factors, for example, wall and roof material, floors number, system (opened and closed) etc. The daily data from heating meters in the residential buildings are presented in this dataset for comparing the thermal characteristics. These data are supplemented by floors number, wall material and year of construction, as well as data on average daily outdoor temperatures. Energy consumed by the building during the heating season may be an indicator of the heating supply of building. At the fixed comfortable temperature inside rooms (24 Celsius degrees) the thermal energy consumed by the building was measured. The smaller one, the better a quality of thermal protection, and the more efficiency of heating. This statistics can be useful for management to increase the energy efficiency of residential buildings.