cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p9zwfd6o
title: High-Water Mark Elevations in Upstate New York from Flash Flooding during July 9-10, 2023

description: This data release contains results of a high-water mark survey across Upstate New York following flash flooding during July 9-10, 2023. The survey was conducted between July 12 and September 20, 2023 by U.S. Geological Survey (USGS) personnel, and is based on surveyed elevations of mud, debris, and seed lines (Koenig and others, 2016) left by the flooding. Real-time and static Global Navigation Satellite System (GNSS) surveying (Rydlund and Densmore, 2012), combined with differential leveling (Kenney, 2010), were used to determine high-water mark elevations at 186 locations. Additional data associated with the July 2023 flooding, such as photos of the survey locations, can be found in the USGS Flood Event Viewer, https://stn.wim.usgs.gov/fev/#2023JulyMANYVTFlood.
DOI: 10.15139/s3/kcnbz3
title: Roman Aqaba Project Stratigraphic Information

description: This contains referential data tied to the Roman Aqaba Project Volumes 2 and 3 on the archaeological loci and their stratigraphic relationships by excavation trench.
DOI: 10.5281/zenodo.10048209
title: Melting and Defect Transitions in FeO up to Pressures of Earth's Core-Mantle Boundary

description: The tables here represent the Source Data for Figure 6 in the manuscript titled "Melting and defect transitions in FeO up to pressures of Earth's core-mantle boundary.
DOI: 10.5281/zenodo.10048208
title: Melting and Defect Transitions in FeO up to Pressures of Earth's Core-Mantle Boundary

description: The tables here represent the Source Data for Figure 6 in the manuscript titled "Melting and defect transitions in FeO up to pressures of Earth's core-mantle boundary.
DOI: 10.5281/zenodo.10048276
title: SoftwareKG-PMC

description: SoftwareKG-PMC is a Knowledge Graph of Software mentions extracted from articles of the PMC Open Access Dataset.
Code for Construction and Analysis is provided at https://github.com/f-krueger/SoftwareKG-PMC-Analysis
This data set contains the CSV based representation of the SoftwareKG knowledge graph.
Note that the CSV files do not contain information about articles that where only available as pdf, so the overall number of articles considered here is reduced to 3036913.
description: This work was financially supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) as part of the projects SFB 1270/2 (grant: 299150580) and ScienceLinker (grant: 404417453).
Parts of the computation were done by using a compute cluster funded by DFG (grant: 440623123).
DOI: 10.5281/zenodo.5553738
title: SoftwareKG-PMC

description: SoftwareKG-PMC is a Knowledge Graph of Software mentions extracted from articles of the PMC Open Access Dataset. Code for Construction and Analysis is provided at https://github.com/f-krueger/SoftwareKG-PMC-Analysis
description: This work was financially supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) as part of the projects SFB 1270/2 (grant: 299150580) and ScienceLinker (grant: 404417453). Parts of the computation were done by using a compute cluster funded by DFG (grant: 440623123).
DOI: 10.5281/zenodo.7400022
title: SoftwareKG-PMC

description: SoftwareKG-PMC is a Knowledge Graph of Software mentions extracted from articles of the PMC Open Access Dataset. Code for Construction and Analysis is provided at https://github.com/f-krueger/SoftwareKG-PMC-Analysis This data set contains the ntriples based representation of the SoftwareKG knowledge graph.
description: This work was financially supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) as part of the projects SFB 1270/2 (grant: 299150580) and ScienceLinker (grant: 404417453). Parts of the computation were done by using a compute cluster funded by DFG (grant: 440623123).
DOI: 10.5281/zenodo.5553737
title: SoftwareKG-PMC

description: SoftwareKG-PMC is a Knowledge Graph of Software mentions extracted from articles of the PMC Open Access Dataset.
Code for Construction and Analysis is provided at https://github.com/f-krueger/SoftwareKG-PMC-Analysis
This data set contains the CSV based representation of the SoftwareKG knowledge graph.
Note that the CSV files do not contain information about articles that where only available as pdf, so the overall number of articles considered here is reduced to 3036913.
description: This work was financially supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) as part of the projects SFB 1270/2 (grant: 299150580) and ScienceLinker (grant: 404417453).
Parts of the computation were done by using a compute cluster funded by DFG (grant: 440623123).
DOI: 10.5281/zenodo.5713973
title: SoftwareKG-PMC

description: SoftwareKG-PMC is a Knowledge Graph of Software mentions extracted from articles of the PMC Open Access Dataset. Code for Construction and Analysis is provided at https://github.com/f-krueger/SoftwareKG-PMC-Analysis
description: This work was financially supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) as part of the projects SFB 1270/2 (grant: 299150580) and ScienceLinker (grant: 404417453). Parts of the computation were done by using a compute cluster funded by DFG (grant: 440623123).
DOI: 10.5281/zenodo.5780121
title: SoftwareKG-PMC

description: SoftwareKG-PMC is a Knowledge Graph of Software mentions extracted from articles of the PMC Open Access Dataset. Code for Construction and Analysis is provided at https://github.com/f-krueger/SoftwareKG-PMC-Analysis
description: This work was financially supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) as part of the projects SFB 1270/2 (grant: 299150580) and ScienceLinker (grant: 404417453). Parts of the computation were done by using a compute cluster funded by DFG (grant: 440623123).
DOI: 10.5519/qd.mq8pro0n
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (35 records)
DOI: 10.5067/suborbital/tote-vote/data001
title: TOTE-VOTE Campaign Data
DOI: 10.5067/asdc/suborbital/tote-vote_ground_data_1
title: TOTE-VOTE Ground Site Lidar Data
DOI: 10.5067/asdc/suborbital/tote-vote_sondes_data_1
title: TOTE-VOTE Sonde Data
DOI: 10.5067/asdc/suborbital/tote-vote_satellite_data_1
title: TOTE-VOTE Supplementary Satellite Data
DOI: 10.5067/asdc/suborbital/tote-vote_analysis_dc8_data_1
title: TOTE-VOTE DC-8 Analysis Data
DOI: 10.5067/asdc/suborbital/tote-vote_miscellaneous_dc8_data_1
title: TOTE-VOTE DC-8 Ancillary Data
DOI: 10.5067/asdc/suborbital/tote-vote_metnav_aircraftinsitu_dc8_data_1
title: TOTE-VOTE In Situ DC-8 Meteorology and Navigation Data
DOI: 10.5067/asdc/suborbital/tote-vote_aircraftremotesensing_dc8_dial_data_1
title: TOTE-VOTE DC-8 Remotely Sensed Differential Absorption Lidar (DIAL) Data
DOI: 10.5067/asdc/suborbital/tote-vote_aircraftremotesensing_dc8_lidar_data_1
title: TOTE-VOTE DC-8 Remotely Sensed Lidar Data
DOI: 10.5067/asdc/suborbital/tote-vote_aerosol_aircraftinsitu_dc8_data_1
title: TOTE-VOTE DC-8 In Situ Aerosol Data
DOI: 10.5067/asdc/suborbital/tote-vote_tracegas_aircraftinsitu_dc8_data_1
title: TOTE-VOTE DC-8 In Situ Trace Gas Data
DOI: 10.18112/openneuro.ds004830.v1.0.0
title: Spatial Attention fNIRS Dataset
DOI: 10.3886/e194726
title: Are Law Schools Cream-Skimming to Bolster Their Bar Exam Pass Rates? A Multilevel Regression Approach to Estimate How Attrition and Transfer Rates Affect Bar Passage

description: Law schools are held accountable on many fronts to achieve and maintain high bar passage rates. While the course of legal education itself, along with various interventions, is a key driver of bar exam performance, Bahadur et al. (2021) suggests that obscure institutional practices might be inflating institutional bar passage performance. Such practices could include recruitment and admission of transfer students and academic attrition. We examine this hypothesis to assess the influence of both attrition and transfer on law schools’ bar passage differential using fixed-effects and between-within models. We also utilize Poisson regression to explore the effect of geographical proximity to other law schools on transfer rates. We find that, on average, neither attrition nor transfer activity substantively affect bar passage performance, and that although geographic proximity to other schools is related to transfer rates, this relationship does not result in notable differences in bar passage. This repository contains the data and R files associated with this project.
DOI: 10.3886/e194726v1
title: Are Law Schools Cream-Skimming to Bolster Their Bar Exam Pass Rates? A Multilevel Regression Approach to Estimate How Attrition and Transfer Rates Affect Bar Passage

description: Law schools are held accountable on many fronts to achieve and maintain high bar passage rates. While the course of legal education itself, along with various interventions, is a key driver of bar exam performance, Bahadur et al. (2021) suggests that obscure institutional practices might be inflating institutional bar passage performance. Such practices could include recruitment and admission of transfer students and academic attrition. We examine this hypothesis to assess the influence of both attrition and transfer on law schools’ bar passage differential using fixed-effects and between-within models. We also utilize Poisson regression to explore the effect of geographical proximity to other law schools on transfer rates. We find that, on average, neither attrition nor transfer activity substantively affect bar passage performance, and that although geographic proximity to other schools is related to transfer rates, this relationship does not result in notable differences in bar passage. This repository contains the data and R files associated with this project.
DOI: 10.57745/eukh74
title: Metro Experiment.zip

description: This file Metro Experiment.zip contains two folders, “MetroUE5_windows” and “RawData”, and a “README.txt” file describing the folder structure. The first folder contains the executable of the original experiment for reproducibility purposes. It contains the file “MetroUE5.exe” which features the experiment and a file “README.txt” with instructions on how to run it. The second folder “RawData”, contains the dataset from 38 individuals who were tested for the purposes of the main objective of the project ForEVR, to study the perception of virtual human motion and their effect on users’ physical avoidance behaviour in virtual reality. The data is anonymised and contains information about the participants’ demographics and subjective responses to the questionnaires. The data is presented in the form of csv files with the x and y coordinates of the participant’s HMD in the virtual environment for each frame of the VR experience. The full experiment and results are published in the publication: Patotskaya, Y. et al. (2023). Avoiding virtual humans in a constrained environment: exploration of novel behavioural measures. Computers and Graphics.
DOI: 10.5519/qd.wur077km
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (118 records)
DOI: 10.5281/zenodo.10048227
title: RRID Gold Set of annotations for software tools in the biomedical literature

description: This data is a subset of a larger human curated, machine assisted gold standard data set of RRID citations within the text of the scientific literature. The full set is accessible via Hypothes.is at https://hypothes.is/users/scibot?q=group%3A__world__  and via individual RRID records such as RRID:SCR_016250 https://scicrunch.org/resolver/SCR_016250/mentions?q=&i=rrid:scr_016250 
The data is based on authors who added RRIDs into their manuscripts. The data was then extracted by SciBot (RRID:SCR_016250), into Hypothes.is (RRID:SCR_000430) and then manually checked by a curator to determine if the author and the database agreed. The list of annotators is available in Hypothes.is user group: SciBotCurationGroup.
There are 78,140 rows and each row contains an annotation (annotation id, URI), linked to a paper (paper identifiers: PMID, DOI, PMC) and linked to the RRID (scr_id, exact, text_quote_selector). 
A second spreadsheet contains a list of 8,322 software tools from the SciCrunch Registry (available here https://scicrunch.org/resources/data/source/nlx_144509-1/search ), enhanced by additions by thousands of individual authors, and curated over 10 years (Ozyurt et al., 2016). 
The third spreadsheet contains a data dictionary and links to related ontologies, and tagging sets.
DOI: 10.5281/zenodo.10048228
title: RRID Gold Set of annotations for software tools in the biomedical literature

description: This data is a subset of a larger human curated, machine assisted gold standard data set of RRID citations within the text of the scientific literature. The full set is accessible via Hypothes.is at https://hypothes.is/users/scibot?q=group%3A__world__  and via individual RRID records such as RRID:SCR_016250 https://scicrunch.org/resolver/SCR_016250/mentions?q=&i=rrid:scr_016250 
The data is based on authors who added RRIDs into their manuscripts. The data was then extracted by SciBot (RRID:SCR_016250), into Hypothes.is (RRID:SCR_000430) and then manually checked by a curator to determine if the author and the database agreed. The list of annotators is available in Hypothes.is user group: SciBotCurationGroup.
There are 78,140 rows and each row contains an annotation (annotation id, URI), linked to a paper (paper identifiers: PMID, DOI, PMC) and linked to the RRID (scr_id, exact, text_quote_selector). 
A second spreadsheet contains a list of 8,322 software tools from the SciCrunch Registry (available here https://scicrunch.org/resources/data/source/nlx_144509-1/search ), enhanced by additions by thousands of individual authors, and curated over 10 years (Ozyurt et al., 2016). 
The third spreadsheet contains a data dictionary and links to related ontologies, and tagging sets.
DOI: 10.5281/zenodo.10048319
title: Data for Manuscript: Location and design of flow control structures differentially influence salinity patterns in small artificial drainages

description: Longitudinal and time series data which correspond to analysis and figures shown in the manuscript titled: Location and design of flow control structures differentially influence salinity patterns in small artificial drainages.
The following files contain longitudinal data of salinity and depth for drainages sampled:
ppp_072820_casts_floats_combined.csv ppp_083120_casts_floats_combined.csv
ar_081720_casts_floats_combined.csv ar_082820_casts_floats_combined.csv
gc_cnldn_072720.csv gc_cnl_up_full_072720.csv gc_canal_YSI_082620_latlong.csv
The following files contain time series data surrounding the land fall of Hurricane Florence in 2018 with water depth and salinity data for the time period.
gc2_flor.csv gc3_flor.csv ar0_florence.csv ar1_florence.csv 
 
 
description: The AR_fcs.csv file contains the latitude and longitude of identified flow control structures along with information regarding their design type.
DOI: 10.5281/zenodo.7319869
title: Data for Manuscript: Location and design of flow control structures differentially influence salinity patterns in small artificial drainages

description: Longitudinal and time series data which correspond to analysis and figures shown in the manuscript titled: Location and design of flow control structures differentially influence salinity patterns in small artificial drainages.
The following files contain longitudinal data of salinity and depth for drainages sampled:
ppp_072820_casts_floats_combined.csv ppp_083120_casts_floats_combined.csv
ar_081720_casts_floats_combined.csv ar_082820_casts_floats_combined.csv
gc_cnldn_072720.csv gc_cnl_up_full_072720.csv gc_canal_YSI_082620_latlong.csv
The following files contain time series data surrounding the land fall of Hurricane Florence in 2018 with water depth and salinity data for the time period.
gc2_flor.csv gc3_flor.csv ar0_florence.csv ar1_florence.csv 
 
 
description: The AR_fcs.csv file contains the latitude and longitude of identified flow control structures along with information regarding their design type.
DOI: 10.5281/zenodo.7319870
title: Data for Manuscript: Location and design of flow control structures differentially influence salinity patterns in small artificial drainages

description: Longitudinal and time series data which correspond to analysis and figures shown in the manuscript titled: Location and design of flow control structures differentially influence salinity patterns in small artificial drainages. The following files contain longitudinal data of salinity and depth for drainages sampled: ppp_072820_casts_floats_combined.csv <br> ppp_083120_casts_floats_combined.csv ar_081720_casts_floats_combined.csv <br> ar_082820_casts_floats_combined.csv gc_cnldn_072720.csv <br> gc_cnl_up_full_072720.csv <br> gc_canal_YSI_082620_latlong.csv The following files contain time series data surrounding the land fall of Hurricane Florence in 2018 with water depth and salinity data for the time period. gc2_flor.csv <br> gc3_flor.csv <br> ar0_florence.csv <br> ar1_florence.csv <br> <br>
DOI: 10.5281/zenodo.10044773
title: Dataset and Code Accompanying the Study by Medina-Vega et al. in Nature Ecology & Evolution: Tropical Tree Ectomycorrhiza Are Distributed Independently of Soil Nutrients

description: This Zenodo repository contains the code and the processed dataset used in the research paper titled "Tropical tree ectomycorrhiza are distributed independently of soil nutrients" published in Nature Ecology & Evolution. In this study, we investigate the distribution and abundance of ectomycorrhizal (EcM) trees in lowland tropical forests and their relationship with soil quality.
Key Finding: EcM-associated trees' distribution and abundance in lowland tropical forests are independent of soil quality.
Contents:

Code (CODE_COARSE_SCALE.R and CODE_FINE_SCALE.R): Contains the R scripts used for data analysis.
Processed Dataset (PCs_prop_EcM.csv): Includes the processed data for the fine-scale analysis.
README: Provides detailed information on how to use the code, interpret the dataset, and access additional required information.
Data Access Information:

To perform the full analyses, please request additional data from the Principal Investigators (PIs) of the plots.
ForestGEO plot data can be obtained upon request through the ForestGEO portal at http://ctfs.si.edu/datarequest/.
Refer to Extended Data Table 1 in the manuscript for a comprehensive list of data sources.
DOI: 10.6084/m9.figshare.24188512
title: Computational analysis of target genes in monkeypox virus infection and potential therapeutic precursors

description: Monkeypox is an orthopoxvirus that is responsible for zoonotic infections in humans. The virus has recently spread rapidly and the WHO has listed it as an international public health emergency of concern. Here, we used network analysis and gene enrichment protocols and analyzed datasets of MPXV infection that induced host cell gene expression list and subsequently mapped them against two herbal target gene lists which highlighted considerable coherence in pharmacological attributes with COVID-19. Molecular docking and simulation were performed for the screened compounds. Our results identified β-carotene and kaempferol possessing tremendous ability against the MPXV PLD protein. Both compounds were subjected to each of 100 ns molecular dynamics simulation and were found native to the PLD pocket. MM-PB (GB) SA analyses indicated −25.4, −40.1 kcal/mol and −17.2, −26.4kcal/mol of ΔG<sub>bind</sub> to the active pocket of PLD. Our data suggest the adaptive nature of the MPXV PLD active pocket toward hydrophobic inhibitors. These results will be of high importance for the viral researchers to be tested in wet lab settings in designing potential inhibitors.
DOI: 10.6084/m9.figshare.24188512.v1
title: Computational analysis of target genes in monkeypox virus infection and potential therapeutic precursors

description: Monkeypox is an orthopoxvirus that is responsible for zoonotic infections in humans. The virus has recently spread rapidly and the WHO has listed it as an international public health emergency of concern. Here, we used network analysis and gene enrichment protocols and analyzed datasets of MPXV infection that induced host cell gene expression list and subsequently mapped them against two herbal target gene lists which highlighted considerable coherence in pharmacological attributes with COVID-19. Molecular docking and simulation were performed for the screened compounds. Our results identified β-carotene and kaempferol possessing tremendous ability against the MPXV PLD protein. Both compounds were subjected to each of 100 ns molecular dynamics simulation and were found native to the PLD pocket. MM-PB (GB) SA analyses indicated −25.4, −40.1 kcal/mol and −17.2, −26.4kcal/mol of ΔG<sub>bind</sub> to the active pocket of PLD. Our data suggest the adaptive nature of the MPXV PLD active pocket toward hydrophobic inhibitors. These results will be of high importance for the viral researchers to be tested in wet lab settings in designing potential inhibitors.
DOI: 10.6084/m9.figshare.24451531
title: Supplementray file .xlsx

description: literacy data of Uttar Pradesh, gender disparity in literacy calculated through the sopher index, Total elementary schools, correlation between elementary schools and female enrolment in uttar pradesh.
DOI: 10.6084/m9.figshare.24451531.v1
title: Supplementray file .xlsx

description: literacy data of Uttar Pradesh, gender disparity in literacy calculated through the sopher index, Total elementary schools, correlation between elementary schools and female enrolment in uttar pradesh.
DOI: 10.6084/m9.figshare.19369463
title: Description and quality of the snakebite database in Brazil from 2007 to 2020

description: “<b>NAIMAC</b>” is a compressed .zip file with a set of 378 DATASUS open datasets."<b>R_script_for_Silva-Neto_et.al.05.07.2022.zip</b>” is a compressed file with all R scripts used for dataset joining, variable preprocessing, completeness assessment, and Table 1 design."<b>Figure 1"</b> presents the bank's total processing steps. The set of 378 datasets were cured. These were extracted and joined, resulting in 2,422,825 records, which were filtered for snakebites."<b>Figure 2"</b> shows the number of records in the dataset by type of snakebite reported in Brazil from 2007 to 2020"<b>Figure 3"</b> shows the age structure of reported cases in this dataset, divided into three categories: youth (up to 18 years of age), adults (age between 20 and 59 years) and elderly (60 years and over)."<b>Figure 4"</b> shows heat maps of the number of accumulated reported snakebite cases, by type of snakebite and municipalities in Brazil."<b>Figure 5"</b> represents the distribution of severity by type of snakebite."<b>Figure 6"</b> represents the number of deaths from accidents over the years."<b>Table 1"</b> Socio-demographic data (SINAN_2007_2020)"<b>Table 2"</b> Clinical/Laboratory data – Symptoms. (SINAN_2007_2020)"<b>DATA_BASE</b>" SINAN database to create table 3."<b>Table 3"</b> Descriptive table<br>“<b>LIM_MUNI_2017</b>” is a compressed .zip file with shapefile files used for accident distribution maps by city.<br>
DOI: 10.5281/zenodo.10035533
title: Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma - Location Data

description: This dataset is meant to be used with "Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma - Results and Data". It provides spatial output data for 4 different setups (spheroid, traditional, 3d gravity, and traditional floating) of an agent-based model of in vitro tuberculosis infection models.