cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4136003
title: Dataset supporting - On the Problem of Modeling the Boat Wake Climate; the Florida Intracoastal Waterway - by Forlini et al., submitted to JGR-Ocean

description: This dataset comprises of 9 .txt file containing water levels data (m) necessary to reconstruct the wakes observations for all the instruments (Acoustic Doppler Velocimeter) deployed during the field experiment.
DOI: 10.5281/zenodo.4136002
title: Dataset supporting - On the Problem of Modeling the Boat Wake Climate; the Florida Intracoastal Waterway - by Forlini et al., submitted to JGR-Ocean

description: This dataset comprises of 9 .txt file containing water levels data (m) necessary to reconstruct the wakes observations for all the instruments (Acoustic Doppler Velocimeter) deployed during the field experiment.
DOI: 10.25387/g3.13146365
title: Supplemental Material for Ayers, Sherman, and Gallagher, 2020

description: Supplemental Figure, tables and data files
DOI: 10.25387/g3.13146365.v1
title: Supplemental Material for Ayers, Sherman, and Gallagher, 2020

description: Supplemental Figure, tables and data files
DOI: 10.6084/m9.figshare.12369188
title: Fig-1-revisSciR

description: Fig 1-SciRe-Maïza et al.
DOI: 10.6084/m9.figshare.13148597
title: Cellular events of acute, resolvingor progressive COVID-19 in SARS-CoV-2 1infected non-human primates

description: Raw data on blood and BAL in animals before and after infection with SARS-COV2<br>
DOI: 10.6084/m9.figshare.7392275
title: Stakeholder - Business Intelligence

description: Leximancer textual analysis of the Business Intelligence stakeholder group as part of the PhD Thesis - The socioethical implications of body worn computers: An Ethnography' now available at https://ro.uow.edu.au/theses1/853
DOI: 10.6084/m9.figshare.11808147
title: Figure 5

description: Fig 5-SciRe-Maïza et al.
DOI: 10.6084/m9.figshare.11808147.v1
title: Figure 5

description: Fig 5-SciRe-Maïza et al.
DOI: 10.5519/qd.eyh8k2o2
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (7 records)
DOI: 10.6084/m9.figshare.11808207
title: Figure 6

description: Fig 6-SciRe-Maïza et al.
DOI: 10.6084/m9.figshare.11808207.v1
title: Figure 6

description: Fig 6-SciRe-Maïza et al.
DOI: 10.6073/pasta/21a28cfb55afeae56a1ef4ef9c8f5b6a
title: Niwot plant functional traits from 2008 to 2018

description: Globally, human activities are altering environmental conditions through changes to disturbance regimes, climate, and primary productivity. Attempts to generalize changes in biodiversity in response to altered environmental conditions have had mixed success and the mechanisms that causes differences in responses are poorly understood. These contingent responses represent one of the largest obstacles to synthesis in community ecology and global change biology. Over the past decade, much progress has been made in resolving these ecological contingencies by shifting from a taxonomic perspective on community assembly and global change to a focus on functional traits. Functional traits are any morphological, physiological, or phenological characteristic of a species linked to fitness and have proven to be effective for understanding species interactions, biogeographic processes, and environmental change. Between 2008 and 2018, we measured plant height, specific leaf area, leaf size, chlorophyll content, stomatal conductance, leaf dry matter content, and leaf chemical composition (nitrogen, carbon, δ13C, δ15N) on 2689 individual plants from 141 species (not all traits on all individuals or species). These measurements were collected to capture intraspecific trait variation among the key habitat types on Niwot Ridge and to examine how species traits respond to global change in the ITEX experiment.
DOI: 10.6084/m9.figshare.13148018
title: R0169_20170506a_videos

description: Rat 0169, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.25387/g3.13146539
title: Supplemental Material for Jones et al., 2020

description: Supplemental Materials
DOI: 10.6084/m9.figshare.9933206
title: Maïza-et-al-G1G2 synaptosome interactome

description: G1G2 synaptosome interactome
DOI: 10.6084/m9.figshare.9933206.v1
title: Maïza-et-al-G1G2 synaptosome interactome

description: G1G2 synaptosome interactome
DOI: 10.6084/m9.figshare.9933314
title: Maïza-et-al-G1G2 synaptosome interactome-normalized

description: G1G2 synaptosome interactome-normalized
DOI: 10.6084/m9.figshare.9933314.v1
title: Maïza-et-al-G1G2 synaptosome interactome-normalized

description: G1G2 synaptosome interactome-normalized
DOI: 10.6084/m9.figshare.9933326
title: Maïza-et-al-SAB

description: Maïza-et-al-SAB
DOI: 10.21227/v8vy-ay29
title: ExoNet Database: Wearable Camera Images of Human Locomotion Environments

description: Abstract: Advances in computer vision and artificial intelligence are allowing researchers to develop environment recognition systems for powered lower-limb exoskeletons and prostheses. However, small-scale and private training datasets have impeded the widespread development and dissemination of image classification algorithms for classifying human walking environments. To address these limitations, we developed “ExoNet” - the first open-source, large-scale hierarchical database of high-resolution wearable camera images of human locomotion environments. Unparalleled in scale and diversity, ExoNet contains over 5.6 million RGB images of different indoor and outdoor real-world walking environments, which were collected using a lightweight wearable camera system throughout the summer, fall, and winter seasons. Approximately 923,000 images in ExoNet were human-annotated using a 12-class hierarchical labelling architecture. Available publicly through IEEE DataPort, ExoNet offers an unprecedented communal platform to train, develop, and compare next-generation image classification algorithms for human locomotion environment recognition. Besides the control of powered lower-limb exoskeletons and prostheses, applications of ExoNet could extend to humanoids and autonomous legged robots.Reference: Laschowski B, McNally W, Wong A, and McPhee J. (2020). ExoNet Database: Wearable Camera Images of Human Locomotion Environments. Frontiers in Robotics and Artificial Intelligence. Under Review.
DOI: 10.6084/m9.figshare.13148018.v1
title: R0169_20170506a_videos

description: Rat 0169, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.9933326.v1
title: Maïza-et-al-SAB

description: Maïza-et-al-SAB
DOI: 10.5523/bris.37pg6mv6x35r12b98aoq4blcgs
title: Data from ACE & Self harm Sri Lanka (10-2020)

description: Data collected as part of the hospital case control study investigating the association between adverse childhood experiences and self-poisoning in Sri Lanka https://bmjopen.bmj.com/content/9/8/e027766
DOI: 10.6084/m9.figshare.13148612
title: data.xlsx

description: This file contains information on the genotype, characteristics, eating habits and family history of cancer of each research object.<br><b></b><i></i><sub></sub><sup></sup><br><br><br><br><br>
DOI: 10.6084/m9.figshare.13148612.v2
title: data.xlsx

description: This file contains information on the genotype, characteristics, eating habits and family history of cancer of each research object.<br><b></b><i></i><sub></sub><sup></sup><br><br><br><br><br>
DOI: 10.6084/m9.figshare.13148612.v1
title: data.xlsx

description: This file contains information on the genotype, characteristics, eating habits and family history of cancer of each research object.<br><b></b><i></i><sub></sub><sup></sup><br><br><br><br><br>
DOI: 10.5281/zenodo.4139735
title: Dataset associated to Bioinspired electro-permeable glycans on carbon: Fouling control for sensing in complex matrices

description: This dataset is associated to the publication "Bioinspired electro-permeable glycans on carbon: Fouling control for sensing in complex matrices" performed in Trinity College, Dublin, Ireland. The dataset contains raw data associated to the measures contained in the article: X ray photoelectron spectroscopy, Atomic force microscopy, cyclic voltammetries. This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) grant No. 13/CDA/2213. AM and JAB gratefully acknowledge support from the School of Chemistry and the Irish Research Council Grant No. GOIPG/2014/399, respectively. EW is grateful for support by the Undergraduate Research Bursary Program of the Royal Society of Chemistry and Nuffield Foundation. Use of the XPS of Prof. I. V. Shvets and C. McGuinness provided under SFI Equipment Infrastructure funds. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 799175 (HiBriCarbon). The results of this publication reflect only the authors’ view and the Commission is not responsible for any use that may be made of the information it contains.
DOI: 10.5281/zenodo.4139734
title: Dataset associated to Bioinspired electro-permeable glycans on carbon: Fouling control for sensing in complex matrices

description: This dataset is associated to the publication "Bioinspired electro-permeable glycans on carbon: Fouling control for sensing in complex matrices" performed in Trinity College, Dublin, Ireland. The dataset contains raw data associated to the measures contained in the article: X ray photoelectron spectroscopy, Atomic force microscopy, cyclic voltammetries. This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) grant No. 13/CDA/2213. AM and JAB gratefully acknowledge support from the School of Chemistry and the Irish Research Council Grant No. GOIPG/2014/399, respectively. EW is grateful for support by the Undergraduate Research Bursary Program of the Royal Society of Chemistry and Nuffield Foundation. Use of the XPS of Prof. I. V. Shvets and C. McGuinness provided under SFI Equipment Infrastructure funds. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 799175 (HiBriCarbon). The results of this publication reflect only the authors’ view and the Commission is not responsible for any use that may be made of the information it contains.
DOI: 10.6084/m9.figshare.13148012
title: R0312_20191120a_videos

description: Rat 0312, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13148012.v1
title: R0312_20191120a_videos

description: Rat 0312, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.5281/zenodo.4139861
title: Dataset associated to Tailored glycosylated anode surfaces: Addressing the exoelectrogen bacterial community via functional layers for microbial fuel cell applications

description: This file contains the dataset associated to the published research article "Tailored glycosylated anode surfaces: Addressing the exoelectrogen bacterial community via functional layers for microbial fuel cell applications". The dataset contains Atomic Force Microscopy, electrochemistry, Microbial Fuel Cells power output and water contact angle raw data from their relative instruments. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 799175 (HiBriCarbon). The results of this publication reflect only the authors' view and the Commission is not responsible for any use that may be made of the information it contains. This publication has also emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213. The authors also thank the France-Ireland PHC ULYSSES programme for support, project 36028UB. JAB acknowledges support from the Irish Research Council under Grant No. GOIPG/2014/399.
DOI: 10.5281/zenodo.4139860
title: Dataset associated to Tailored glycosylated anode surfaces: Addressing the exoelectrogen bacterial community via functional layers for microbial fuel cell applications

description: This file contains the dataset associated to the published research article "Tailored glycosylated anode surfaces: Addressing the exoelectrogen bacterial community via functional layers for microbial fuel cell applications". The dataset contains Atomic Force Microscopy, electrochemistry, Microbial Fuel Cells power output and water contact angle raw data from their relative instruments. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 799175 (HiBriCarbon). The results of this publication reflect only the authors' view and the Commission is not responsible for any use that may be made of the information it contains. This publication has also emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213. The authors also thank the France-Ireland PHC ULYSSES programme for support, project 36028UB. JAB acknowledges support from the Irish Research Council under Grant No. GOIPG/2014/399.
DOI: 10.5281/zenodo.4139871
title: Black-hole neutron-star binary simulation SXS:BHNS:0010

description: Simulation of a black-hole neutron-star binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.4139870
title: Black-hole neutron-star binary simulation SXS:BHNS:0010

description: Simulation of a black-hole neutron-star binary system evolved by the SpEC code.
DOI: 10.5066/p9essb67
title: Sensor Data from Monitoring the Cooling of the 2014-2015 Lava Flow and Hydrothermal System at Holuhraun, Iceland

description: This data release is a companion to Dundas et al., NNNN. Additional description of the methods and rationale for data collection is provided there. The primary data are from several categories of data-logging sensors described in detail below. Sixteen images are also included as part of this data release. These document the sensor locations as described in Dundas et al. (NNNN).
DOI: 10.5517/ccdc.csd.cc1mys1d
title: CCDC 1518164: Experimental Crystal Structure Determination

description: Related Article: Chen YANG|2016|CSD Communication|||
description: Related Article: Kai Li, Glenna So Ming Tong, Jia Yuan, Chensheng Ma, Lili Du, Chen Yang, Wai-Ming Kwok, David Lee Phillips, Chi-Ming Che|2020|Inorg.Chem.|59|14654|doi:10.1021/acs.inorgchem.0c01192
DOI: 10.5517/ccdc.csd.cc1mys2f
title: CCDC 1518165: Experimental Crystal Structure Determination

description: Related Article: Chen YANG|2016|CSD Communication|||
description: Related Article: Kai Li, Glenna So Ming Tong, Jia Yuan, Chensheng Ma, Lili Du, Chen Yang, Wai-Ming Kwok, David Lee Phillips, Chi-Ming Che|2020|Inorg.Chem.|59|14654|doi:10.1021/acs.inorgchem.0c01192
DOI: 10.5517/ccdc.csd.cc1mys3g
title: CCDC 1518166: Experimental Crystal Structure Determination

description: Related Article: Chen YANG|2016|CSD Communication|||
description: Related Article: Kai Li, Glenna So Ming Tong, Jia Yuan, Chensheng Ma, Lili Du, Chen Yang, Wai-Ming Kwok, David Lee Phillips, Chi-Ming Che|2020|Inorg.Chem.|59|14654|doi:10.1021/acs.inorgchem.0c01192
DOI: 10.5517/ccdc.csd.cc23gb31
title: CCDC 1950182: Experimental Crystal Structure Determination

description: Related Article: Ryuji Kyan, Kohei Sato, Nobuyuki Mase, Tetsuo Narumi|2020|Angew.Chem.,Int.Ed.|59|19031|doi:10.1002/anie.202008631
description: Related Article: Tetsuo Narumi|2020|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc252c9y
title: CCDC 1998269: Experimental Crystal Structure Determination

description: Related Article: Kai Li, Glenna So Ming Tong, Jia Yuan, Chensheng Ma, Lili Du, Chen Yang, Wai-Ming Kwok, David Lee Phillips, Chi-Ming Che|2020|Inorg.Chem.|59|14654|doi:10.1021/acs.inorgchem.0c01192
DOI: 10.5281/zenodo.4139881
title: Black-hole neutron-star binary simulation SXS:BHNS:0008

description: Simulation of a black-hole neutron-star binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.4139880
title: Black-hole neutron-star binary simulation SXS:BHNS:0008

description: Simulation of a black-hole neutron-star binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.4139080
title: WinoST: Evaluating Gender Bias in Speech Translation

description: WinoST is a challenge set for evaluating gender bias in speech translation. WinoST is the speech version of WinoMT (Stanovsky et al., 2019) which is an MT challenge set and both follow an evaluation protocol to measure gender accuracy. WinoST consists of 3888 speech audios in English plus a text file with the the text of these audios. For further details, please refer to the publication entitled "Evaluating Gender Bias in Speech Translation" (Costa-jussà et al., 2020). Also cite this publication if using this corpus.
description: IMPORTANT: The corpus is distributed under the MIT License, but recordings can't be used for speech synthesis, text to speech, voice conversion, or other applications where the speaker's voice is imitated or reproduced. This work is supported in part by the Spanish Ministerio de Ciencia e Innovación through the postdoctoral senior grant Ramón y Cajal.
description: {"references": ["(Costa-juss\u00e0 et al., 2020) Evaluating Gender Bias in Speech Translation, ARXIV.org, 2020", "(Stanovsky et al., 2019) Evaluating Gender Bias in Machine Translation, ACL, 2019"]}
DOI: 10.5281/zenodo.4139079
title: WinoST: Evaluating Gender Bias in Speech Translation

description: WinoST is a challenge set for evaluating gender bias in speech translation. WinoST is the speech version of WinoMT (Stanovsky et al., 2019) which is an MT challenge set and both follow an evaluation protocol to measure gender accuracy. WinoST consists of 3888 speech audios in English plus a text file with the the text of these audios. For further details, please refer to the publication entitled "Evaluating Gender Bias in Speech Translation" (Costa-jussà et al., 2020). Also cite this publication if using this corpus.
description: IMPORTANT: The corpus is distributed under the MIT License, but recordings can't be used for speech synthesis, text to speech, voice conversion, or other applications where the speaker's voice is imitated or reproduced. This work is supported in part by the Spanish Ministerio de Ciencia e Innovación through the postdoctoral senior grant Ramón y Cajal.
description: {"references": ["(Costa-juss\u00e0 et al., 2020) Evaluating Gender Bias in Speech Translation, ARXIV.org, 2020", "(Stanovsky et al., 2019) Evaluating Gender Bias in Machine Translation, ACL, 2019"]}
DOI: 10.5281/zenodo.4139890
title: Black-hole neutron-star binary simulation SXS:BHNS:0009

description: Simulation of a black-hole neutron-star binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.4139889
title: Black-hole neutron-star binary simulation SXS:BHNS:0009

description: Simulation of a black-hole neutron-star binary system evolved by the SpEC code.
DOI: 10.21227/tfwk-v385
title: Test submission 6

description: Fixed errors. Used clustering and FBprophet on 5 clusters. Removed continuous growth trend and set to flat.
DOI: 10.5281/zenodo.4139894
title: Las características de anuncios de alquiler en la ciudad de Barcelona de plataforma habitaclia.

description: El dataset contiene los datos numéricos, binarios y textuales más relevantes recopilados de cada uno de los anuncios de una ciudad dada, en este caso Barcelona: Precio, Titulo de anuncio, Superficie, Número de habitaciones, Número de baños, Barrio, Descripción completa, Amueblamiento (sí/no), Calefacción (sí/no), Aire acondicionado (sí/no), Ascensor (sí/no), Detalles de distribución y Características adicionales. Aunque los datos sobre calefacción, aire acondicionado, etc, también se recopilan dentro de la variable “features_detail” para tener el dato consistente y separar las características de más interés en las variables independientes directamente. Al momento de realización de scraping hay alrededor de 13.000 anuncios.
DOI: 10.5281/zenodo.4139893
title: Las características de anuncios de alquiler en la ciudad de Barcelona de plataforma habitaclia.

description: El dataset contiene los datos numéricos, binarios y textuales más relevantes recopilados de cada uno de los anuncios de una ciudad dada, en este caso Barcelona: Precio, Titulo de anuncio, Superficie, Número de habitaciones, Número de baños, Barrio, Descripción completa, Amueblamiento (sí/no), Calefacción (sí/no), Aire acondicionado (sí/no), Ascensor (sí/no), Detalles de distribución y Características adicionales. Aunque los datos sobre calefacción, aire acondicionado, etc, también se recopilan dentro de la variable “features_detail” para tener el dato consistente y separar las características de más interés en las variables independientes directamente. Al momento de realización de scraping hay alrededor de 13.000 anuncios.
DOI: 10.5281/zenodo.4129774
title: [RDF Triples] Courses given at the Vrije Universiteit Amsterdam 2020/2021

description: This data set is published in Turtle format using triples. The dataset contains all the Courses and their information at the Vrije Universiteit Amsterdam for the university year 2020/2021. This information was gathered from the Vrije Universiteit Amsterdam online study guide A new vocabulary 'vu' was needed as some vocabularies did not allow full expression of the datas et. You can use SPARQL in order to fetch data from this dataset, the property variables one can user are: vu:offeredByFaculty This property will return the faculty the course belongs to as a vu:<strong>FacultyName</strong>. vu:taughtBy This property will return the professors who teach that course as a vu:<strong>ProfessorName</strong>. vu:courseContent This property returns what a course is about as a string. vu:courseLevel This property returns the course level (between 100 and 600) as an integer. vu:courseObjective This property returns the objective of a course as a string. vu:literature This property returns the required literature of a course as a string. vu:recommendedBackground This poperty returns the recommended background of a course as a string. vu:targetAudience This property returns the target audience of a course as a string. vu:teachingMethods This property returns the teaching methods of a course as a string. These are the by us created property variables. There are also some re-used variables which are: vuc:<strong>CourseID</strong> rdf:type teach:Course This returns all courses when used in sparql. dbo:language This property returns the language in which a course is given as a dbr:<strong>LanguageName</strong> teach:academicTerm This property is used in order to return the academic term in which a course is given as a string. teach:courseTitle This property returns the name of a course as a string. teach:ects This property returns the number of European credits one receives for a course as an integer. teach:grading This property returns the grading method of a course as a string. This data set can be used in order to find specific information about courses without knowing the exact course name or code. For example, you can fetch all courses that have 3 credits and are in English, given at the faculty of Science. Therefore it becomes much easier for students that want to follow courses outside of their major/master, which also fit their requirements. In a normal situation, a student would need to search through all 2064 courses given at the VU to find a course that they like.