cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10814380
title: Data supporting: "Calcium-driven In Silico Inactivation of a Human Olfactory Receptor"

description: In this repository we deposited trajectories and input files for the paper "Calcium-driven In Silico Inactivation of a Human Olfactory Receptor".

The data is organised as follow:

 

DATA:

CA / NA / NO_IONS / NEUTRAL



centroid.pdb                                         # centroid calculated with GMX

step5_input.gro                                         # input file from CHARMM GUI

topol.top                                         # topol file from CHARMM GUI

MDPs                                         # folder containing mdp files from CHARMM GUI

toppar                                         # folder containing topology files from CHARMM GUI                


 

TRJs:

CA / NA / NO_IONS / NEUTRAL



ref.pdb                                           # reference pdb file

trj1.xtc                                           # trajectory from replica 1

trj2.xtc                                           # trajectory from replica 2

trj3.xtc                                           # trajectory from replica 3

trj4.xtc                                           # trajectory from replica 4

trj5.xtc                                           # trajectory from replica 5

trj6.xtc                                          # trajectory from replica 6 (NEUTRAL only)
DOI: 10.6084/m9.figshare.25436845
title: Citizen science helps to fill distribution gaps, and describe the forest and wild area types used by the black snail Macrocyclis peruvianus (Gastropoda, Macrocyclidae) - supplementary dataset <i>2</i>

description: supplementary dataset 2 for the paper entitled "Citizen science helps to fill distribution gaps, and describe the forest and wild area types used by the black snail Macrocyclis peruvianus (Gastropoda, Macrocyclidae)"
DOI: 10.6084/m9.figshare.25436845.v1
title: Citizen science helps to fill distribution gaps, and describe the forest and wild area types used by the black snail Macrocyclis peruvianus (Gastropoda, Macrocyclidae) - supplementary dataset <i>2</i>

description: supplementary dataset 2 for the paper entitled "Citizen science helps to fill distribution gaps, and describe the forest and wild area types used by the black snail Macrocyclis peruvianus (Gastropoda, Macrocyclidae)"
DOI: 10.48329/q14s-rt16
title: CPRD GOLD March 2024

description: The CPRD Gold database contains longitudinal routinely-collected electronic health records (EHR data) from UK primary care practices using Vision® general practice patient management software. The database captures information on demographic characteristics; diagnoses and symptoms; drug exposures; vaccination history; laboratory tests; and referrals to hospital and specialist care. Access to anonymised data from CPRD is subject to a full licence agreement containing detailed terms and conditions of use. Anonymised patient datasets can be extracted for researchers against specific study specifications, following protocol approval. Further information is available at https://www.cprd.com/data-access.
DOI: 10.6084/m9.figshare.25436956
title: Raw data for Rolleman et al. (2024): Common camas (<i>Camassia quamash</i>) response across an urban-rural gradient in coastal oak meadows in Greater Victoria, Canada

description: The raw data used in the analysis for <i>Common camas (Camassia quamash) response across an urban-rural gradient in coastal oak meadows in Greater Victoria, Canada</i> by Rolleman et al. (2024). See the Methods section in the research article for detailed statistical methods for how the raw data was analyzed.
DOI: 10.6084/m9.figshare.25436956.v1
title: Raw data for Rolleman et al. (2024): Common camas (<i>Camassia quamash</i>) response across an urban-rural gradient in coastal oak meadows in Greater Victoria, Canada

description: The raw data used in the analysis for <i>Common camas (Camassia quamash) response across an urban-rural gradient in coastal oak meadows in Greater Victoria, Canada</i> by Rolleman et al. (2024). See the Methods section in the research article for detailed statistical methods for how the raw data was analyzed.
DOI: 10.5281/zenodo.10839704
title: Data from: "Correlates of mid-winter pregnancy and early reproductive outcomes in a reintroduced elk (Cervus canadensis) population"

description: Raw and processed datasets used for analysis in "Correlates of mid-winter pregnancy and early reproductive outcomes in a reintroduced elk (Cervus canadensis) population" by Hooven et al., published in Mammalian Biology. Datasets are as follows:

Pregnancy.csv - Raw dataset detailing year and date of capture, individual identifier, and measured intrinsic variables, along with confirmed or predicted pregnancy/calf viability status.

Pregnancy_final_mass.csv - Raw dataset after body mass estimation for individuals that were not weighed. 

all_confirmed_preg.csv - Subset of raw data for all individuals with confirmed pregnancy status (via lab PSPB assay).

preg_ageclass.csv - Subset of all_confirmed_preg dataset including all individuals with general age classification (e.g., adult or subadult).

preg_numeric.csv - Subset of all_confirmed_preg dataset including all individuals with numeric age value (from incisiform canine cementum annuli).

all_fns.csv - Subset of dataset including all individuals with confirmed or predicted fetal/early neonatal survival ("offspring viability") status.

fns_ageclass.csv - Subset of all_fns.csv including all individuals with general age classification.

fns_numeric.csv - Subset of all_fns.csv including all individuals with numeric age values.

parameter_est.csv - Parameter estimates from top-performing generalized linear mixed models for both pregnancy and offpsinrg viability, for plotting.
DOI: 10.5281/zenodo.10839705
title: Data from: "Correlates of mid-winter pregnancy and early reproductive outcomes in a reintroduced elk (Cervus canadensis) population"

description: Raw and processed datasets used for analysis in "Correlates of mid-winter pregnancy and early reproductive outcomes in a reintroduced elk (Cervus canadensis) population" by Hooven et al., published in Mammalian Biology. Datasets are as follows:

Pregnancy.csv - Raw dataset detailing year and date of capture, individual identifier, and measured intrinsic variables, along with confirmed or predicted pregnancy/calf viability status.

Pregnancy_final_mass.csv - Raw dataset after body mass estimation for individuals that were not weighed. 

all_confirmed_preg.csv - Subset of raw data for all individuals with confirmed pregnancy status (via lab PSPB assay).

preg_ageclass.csv - Subset of all_confirmed_preg dataset including all individuals with general age classification (e.g., adult or subadult).

preg_numeric.csv - Subset of all_confirmed_preg dataset including all individuals with numeric age value (from incisiform canine cementum annuli).

all_fns.csv - Subset of dataset including all individuals with confirmed or predicted fetal/early neonatal survival ("offspring viability") status.

fns_ageclass.csv - Subset of all_fns.csv including all individuals with general age classification.

fns_numeric.csv - Subset of all_fns.csv including all individuals with numeric age values.

parameter_est.csv - Parameter estimates from top-performing generalized linear mixed models for both pregnancy and offpsinrg viability, for plotting.
DOI: 10.5066/p9tc92b5
title: Water-level data and selected field notes for aquifer-interval-isolation tests at and near the former Naval Air Warfare Center Warminster, Bucks County, Pennsylvania, 2018-19 (ver. 2.0, January 2024)

description: The U.S. Geological Survey (USGS) conducted aquifer interval isolation (packer) tests of discrete water-bearing zones using straddle packers in 13 wells in Northampton, Warminster, and Warwick Townships and Ivyland Borough, Bucks County, Pennsylvania during 2018-19 to support detailed groundwater investigations at and near the former Naval Air Warfare Center (NAWC) Warminster, where groundwater contamination with per- and polyfluoroalkyl substances (PFAS) had become a concern since 2014. The area is underlain by the Triassic-age Stockton Formation, which forms a fractured-sedimentary-rock aquifer used for private, industrial, and public drinking-water supply. The packer tests were conducted in 7 former production wells ranging in depth from 160 to 604 feet (ft) near NAWC Warminster and 6 new monitoring wells drilled in 2018 to depths of about 600 ft. on NAWC Warminster. The tested intervals were selected using geophysical and video logs previously collected by USGS to characterize the boreholes and identify potential water-bearing fractures. During the packer tests, water levels in intervals above the upper packer, within the straddled (mid) interval, and below the lower packer were measured during packer inflation, pumping, recovery, and packer deflation. Pumping rates and sampling times were noted. Version 2.0 of data release also includes Appendix 1) summary tables for pumping rates, drawdown, calculated specific capacity, and estimated volume of water pumped before sampling and Appendix 2) results of field and laboratory chemical analysis for water samples from isolated intervals. While previous version is available from the author, all of the records in the previous version can be found in version 2.0.

First posted - November 19, 2020
Revised - January 16, 2024 (version 2.0)
DOI: 10.5281/zenodo.10809406
title: Data for grain boundaries are not the source of Urbach tails in the CIGSe
DOI: 10.5281/zenodo.10809407
title: Data for grain boundaries are not the source of Urbach tails in the CIGSe
DOI: 10.5281/zenodo.10839743
title: Data for grain boundaries are not the source of Urbach tails in the CIGSe
DOI: 10.5281/zenodo.10839767
title: Schubert Winterreise Dataset

description: The Schubert Winterreise Dataset (SWD) is a multimodal dataset comprising various representations and annotations of Franz Schubert's 24-song cycle Winterreise. The primary material (raw data) consists of textual representations of the songs' lyrics, music scores in image, symbolic, and MIDI format, as well as nine audio recordings of performances (only two included due to copyright issues). The secondary material (annotations) comprises information of musical measure positions in sheet music images and audio recordings as well as analyses of chords, local keys, global keys, and structural parts.

UPDATE: From version 2.0 onwards, the SWD contains additional note annotations comprising pitch, pitch class (chroma), and instrument labels for each note event (generated semi-automatically).

The SWD is organized as follows:

01_RawData



lyrics_txt

score-IMSLP_png

score-IMSLP_pdf-complete.pdf

score_sibelius

score_pdf

score_musicxml

score_midi

audio_wav


02_Annotations



ann_score-IMSLP_measure

ann_score_chord

ann_score_localkey-ann1

ann_score_localkey-ann2

ann_score_localkey-ann3

ann_score_globalkey.csv

ann_score_structure

ann_audio_measure

ann_audio_chord

ann_audio_localkey-ann1

ann_audio_localkey-ann2

ann_audio_localkey-ann3

ann_audio_globalkey.csv

ann_audio_structure

ann_audio_note


03_ExtraMaterial



original data

scripts for cutting

licenses of the published performances


Further information can be found in the README file and the accompanying journal paper.

 

License:

The dataset is published under a Creative Commons Attribution 3.0 Unported license (https://creativecommons.org/licenses/by/3.0/legalcode). We acknowledge the publication of the performance by baritone Randall Scarlata with pianist Jeremy Denk (denoted as SC06), published under the same license by the Isabella Stewart Gardner Museum (Boston). Please note that the audio files of this performance must not be re-distributed in modified form. All other sources for the dataset are in the Public Domain.

 

 
description: For a detailed description, please see the accompanying journal paper:
Christof Weiß, Frank Zalkow, Vlora Arifi-Müller, Meinard Müller, Hendrik Vincent Koops, Anja Volk, and Harald G. Grohganz. Schubert Winterreise Dataset: A Multimodal Scenario for Music Analysis. In: ACM Journal on Computing and Cultural Heritage, 2021.
DOI: 10.5281/zenodo.3968389
title: Schubert Winterreise Dataset

description: The <strong>Schubert Winterreise Dataset (SWD)</strong> is a multimodal dataset comprising various representations and annotations of Franz Schubert's 24-song cycle <em>Winterreise</em>. The primary material (<strong>raw data</strong>) consists of textual representations of the songs' lyrics, music scores in image, symbolic, and MIDI format, as well as nine audio recordings of performances (only two included due to copyright issues). The secondary material (<strong>annotations</strong>) comprises information of musical measure positions in sheet music images and audio recordings as well as analyses of chords, local keys, global keys, and structural parts. The SWD is organized as follows: <strong>01_RawData</strong> lyrics_txt score-IMSLP_png <em>score-IMSLP_pdf-complete.pdf</em> score_sibelius score_pdf score_musicxml score_midi audio_wav <strong>02_Annotations</strong> ann_score-IMSLP_measure ann_score_chord ann_score_localkey-ann1 ann_score_localkey-ann2 ann_score_localkey-ann3 <em>ann_score_globalkey.csv</em> ann_score_structure ann_audio_measure ann_audio_chord ann_audio_localkey-ann1 ann_audio_localkey-ann2 ann_audio_localkey-ann3 <em>ann_audio_globalkey.csv</em> ann_audio_structure <strong>03_ExtraMaterial</strong> original data, scripts for cutting, licenses, ...
description: For a detailed description, please see the accompanying journal paper: Christof Weiß, Frank Zalkow, Vlora Arifi-Müller, Meinard Müller, Hendrik Vincent Koops, Anja Volk, and Harald G. Grohganz. Schubert Winterreise Dataset: A Multimodal Scenario for Music Analysis. In: ACM Journal on Computing and Cultural Heritage, XX:YY, 2020, under revision
description: {"references": ["Frans Absil. Musical Analysis \u2013 Visiting the Great Composers (6th ed.), 2017", "Harald Grohganz. Algorithmen zur strukturellen Analyse von Musikaufnahmen. Ph.D. Dissertation. University of Bonn, Germany, 2015", "Hendrik Vincent Koops. Computational Modelling of Variance in Musical Harmony. Ph.D. Dissertation. Utrecht University, Utrecht, The Netherlands, 2019", "Frank Zalkow, Angel Villar Corrales, TJ Tsai, Vlora Arifi-M\u00fcller, and Meinard M\u00fcller. Tools for Semi-Automatic Bounding Box Annotation of Musical Measures in Sheet Music. In Demos and Late Breaking News of the International Society for Music Information Retrieval Conference (ISMIR). Delft, The Netherlands, 2019"]}
DOI: 10.5281/zenodo.4122060
title: Schubert Winterreise Dataset

description: The <strong>Schubert Winterreise Dataset (SWD)</strong> is a multimodal dataset comprising various representations and annotations of Franz Schubert's 24-song cycle <em>Winterreise</em>. The primary material (<strong>raw data</strong>) consists of textual representations of the songs' lyrics, music scores in image, symbolic, and MIDI format, as well as nine audio recordings of performances (only two included due to copyright issues). The secondary material (<strong>annotations</strong>) comprises information of musical measure positions in sheet music images and audio recordings as well as analyses of chords, local keys, global keys, and structural parts. The SWD is organized as follows: <strong>01_RawData</strong> lyrics_txt score-IMSLP_png <em>score-IMSLP_pdf-complete.pdf</em> score_sibelius score_pdf score_musicxml score_midi audio_wav <strong>02_Annotations</strong> ann_score-IMSLP_measure ann_score_chord ann_score_localkey-ann1 ann_score_localkey-ann2 ann_score_localkey-ann3 <em>ann_score_globalkey.csv</em> ann_score_structure ann_audio_measure ann_audio_chord ann_audio_localkey-ann1 ann_audio_localkey-ann2 ann_audio_localkey-ann3 <em>ann_audio_globalkey.csv</em> ann_audio_structure <strong>03_ExtraMaterial</strong> original data scripts for cutting licenses of the published performances Further information can be found in the README file and the accompanying journal paper. <strong>License:</strong> The dataset is published under a Creative Commons Attribution 3.0 Unported license (https://creativecommons.org/licenses/by/3.0/legalcode). We acknowledge the publication of the performance by baritone Randall Scarlata with pianist Jeremy Denk (denoted as SC06), published under the same license by the Isabella Stewart Gardner Museum (Boston). Please note that the audio files of this performance must not be re-distributed in modified form. All other sources for the dataset are in the Public Domain.
description: For a detailed description, please see the accompanying journal paper: Christof Weiß, Frank Zalkow, Vlora Arifi-Müller, Meinard Müller, Hendrik Vincent Koops, Anja Volk, and Harald G. Grohganz. Schubert Winterreise Dataset: A Multimodal Scenario for Music Analysis. In: ACM Journal on Computing and Cultural Heritage, 2020.
description: {"references": ["Frans Absil. Musical Analysis \u2013 Visiting the Great Composers (6th ed.), 2017", "Harald Grohganz. Algorithmen zur strukturellen Analyse von Musikaufnahmen. Ph.D. Dissertation. University of Bonn, Germany, 2015", "Hendrik Vincent Koops. Computational Modelling of Variance in Musical Harmony. Ph.D. Dissertation. Utrecht University, Utrecht, The Netherlands, 2019", "Frank Zalkow, Angel Villar Corrales, TJ Tsai, Vlora Arifi-M\u00fcller, and Meinard M\u00fcller. Tools for Semi-Automatic Bounding Box Annotation of Musical Measures in Sheet Music. In Demos and Late Breaking News of the International Society for Music Information Retrieval Conference (ISMIR). Delft, The Netherlands, 2019"]}
DOI: 10.5281/zenodo.4431535
title: Schubert Winterreise Dataset

description: The <strong>Schubert Winterreise Dataset (SWD)</strong> is a multimodal dataset comprising various representations and annotations of Franz Schubert's 24-song cycle <em>Winterreise</em>. The primary material (<strong>raw data</strong>) consists of textual representations of the songs' lyrics, music scores in image, symbolic, and MIDI format, as well as nine audio recordings of performances (only two included due to copyright issues). The secondary material (<strong>annotations</strong>) comprises information of musical measure positions in sheet music images and audio recordings as well as analyses of chords, local keys, global keys, and structural parts. The SWD is organized as follows: <strong>01_RawData</strong> lyrics_txt score-IMSLP_png <em>score-IMSLP_pdf-complete.pdf</em> score_sibelius score_pdf score_musicxml score_midi audio_wav <strong>02_Annotations</strong> ann_score-IMSLP_measure ann_score_chord ann_score_localkey-ann1 ann_score_localkey-ann2 ann_score_localkey-ann3 <em>ann_score_globalkey.csv</em> ann_score_structure ann_audio_measure ann_audio_chord ann_audio_localkey-ann1 ann_audio_localkey-ann2 ann_audio_localkey-ann3 <em>ann_audio_globalkey.csv</em> ann_audio_structure <strong>03_ExtraMaterial</strong> original data scripts for cutting licenses of the published performances Further information can be found in the README file and the accompanying journal paper. <strong>License:</strong> The dataset is published under a Creative Commons Attribution 3.0 Unported license (https://creativecommons.org/licenses/by/3.0/legalcode). We acknowledge the publication of the performance by baritone Randall Scarlata with pianist Jeremy Denk (denoted as SC06), published under the same license by the Isabella Stewart Gardner Museum (Boston). Please note that the audio files of this performance must not be re-distributed in modified form. All other sources for the dataset are in the Public Domain.
description: For a detailed description, please see the accompanying journal paper: Christof Weiß, Frank Zalkow, Vlora Arifi-Müller, Meinard Müller, Hendrik Vincent Koops, Anja Volk, and Harald G. Grohganz. Schubert Winterreise Dataset: A Multimodal Scenario for Music Analysis. In: ACM Journal on Computing and Cultural Heritage, 2021.
description: {"references": ["Frans Absil. Musical Analysis \u2013 Visiting the Great Composers (6th ed.), 2017", "Harald Grohganz. Algorithmen zur strukturellen Analyse von Musikaufnahmen. Ph.D. Dissertation. University of Bonn, Germany, 2015", "Hendrik Vincent Koops. Computational Modelling of Variance in Musical Harmony. Ph.D. Dissertation. Utrecht University, Utrecht, The Netherlands, 2019", "Frank Zalkow, Angel Villar Corrales, TJ Tsai, Vlora Arifi-M\u00fcller, and Meinard M\u00fcller. Tools for Semi-Automatic Bounding Box Annotation of Musical Measures in Sheet Music. In Demos and Late Breaking News of the International Society for Music Information Retrieval Conference (ISMIR). Delft, The Netherlands, 2019"]}
DOI: 10.5281/zenodo.3968388
title: Schubert Winterreise Dataset

description: The Schubert Winterreise Dataset (SWD) is a multimodal dataset comprising various representations and annotations of Franz Schubert's 24-song cycle Winterreise. The primary material (raw data) consists of textual representations of the songs' lyrics, music scores in image, symbolic, and MIDI format, as well as nine audio recordings of performances (only two included due to copyright issues). The secondary material (annotations) comprises information of musical measure positions in sheet music images and audio recordings as well as analyses of chords, local keys, global keys, and structural parts.

UPDATE: From version 2.0 onwards, the SWD contains additional note annotations comprising pitch, pitch class (chroma), and instrument labels for each note event (generated semi-automatically).

The SWD is organized as follows:

01_RawData



lyrics_txt

score-IMSLP_png

score-IMSLP_pdf-complete.pdf

score_sibelius

score_pdf

score_musicxml

score_midi

audio_wav


02_Annotations



ann_score-IMSLP_measure

ann_score_chord

ann_score_localkey-ann1

ann_score_localkey-ann2

ann_score_localkey-ann3

ann_score_globalkey.csv

ann_score_structure

ann_audio_measure

ann_audio_chord

ann_audio_localkey-ann1

ann_audio_localkey-ann2

ann_audio_localkey-ann3

ann_audio_globalkey.csv

ann_audio_structure

ann_audio_note


03_ExtraMaterial



original data

scripts for cutting

licenses of the published performances


Further information can be found in the README file and the accompanying journal paper.

 

License:

The dataset is published under a Creative Commons Attribution 3.0 Unported license (https://creativecommons.org/licenses/by/3.0/legalcode). We acknowledge the publication of the performance by baritone Randall Scarlata with pianist Jeremy Denk (denoted as SC06), published under the same license by the Isabella Stewart Gardner Museum (Boston). Please note that the audio files of this performance must not be re-distributed in modified form. All other sources for the dataset are in the Public Domain.

 

 
description: For a detailed description, please see the accompanying journal paper:
Christof Weiß, Frank Zalkow, Vlora Arifi-Müller, Meinard Müller, Hendrik Vincent Koops, Anja Volk, and Harald G. Grohganz. Schubert Winterreise Dataset: A Multimodal Scenario for Music Analysis. In: ACM Journal on Computing and Cultural Heritage, 2021.
DOI: 10.5281/zenodo.10203912
title: Human health impact based on adult European consumers' dietary exposure to chemical contaminants and consumption of unprocessed red meat, processed meat, and legumes

description: This dataset was generated within the PRISMA project (Marie Skłodowska-Curie Grant Agreement No. 101110615) for assessing the health impact for adult consumers from 25 European countries due to dietary exposure to chemical contaminants and consumption of food based on different dietary patterns.
The risk coefficients used to generate data are presented in Table S1.
File S2 presents the health impact based on the chronic dietary exposure to chemical contaminants for each country.
File S3 presents figures regarding the health impact for each country for adult consumers due to dietary exposure to chemical contaminants and consumption of food based on different dietary patterns.
File S4 presents the health impact based on the consumption of unprocessed red meat, processed meat, and legumes for each country.