cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/ca34be7554ddc67c9fa0f8dea01f375b
title: Dissolved inorganic nutrients from the Martha's Vineyard Coastal Observatory (MVCO), including 4 macro-nutrients from water column bottle samples, ongoing since 2003 (NES-LTER since 2017)

description: Dissolved inorganic nutrients including nitrate + nitrite, ammonium, silicate, and phosphate are measured from water column bottle and bucket samples taken on NES-LTER day cruises in the vicinity of the Martha's Vineyard Coastal Observatory (MVCO). Sampling frequency near MVCO is approximately monthly, ongoing since 2003. Samples were filtered, frozen, then processed at the Woods Hole Oceanographic Institution's Nutrient Analytical Facility. These macro-nutrients are analyzed in seawater using a colorimetric assay in which light absorbance is measured versus known standards, and final concentrations are calculated (in micromole per liter). Each sample may have up to 3 replicates.
DOI: 10.5281/zenodo.6625286
title: Brienomyrus longianalis decontaminated gx

description: .
DOI: 10.5281/zenodo.6625285
title: Brienomyrus longianalis decontaminated gx

description: .
DOI: 10.25318/3210022801-eng
title: Land tenure, Census of Agriculture historical data

description: Census of Agriculture, 1921 to date. Total farm area, land owned and land rented or leased from others.
DOI: 10.34681/0evy-8q69
title: Gallup Poll: Child Abuse Study, 1995

description: A nationwide random telephone survey of 1,000 households was conducted between August 15 and September 14,1995. The survey assessed parental attitudes regarding methods of discipline; agreement on discipline; fights between partners; child rearing; and childhood experience of punishment, abuse between parents, and sexual abuse. This survey represents the first national study assessing the validity and reliability of the Parent-Child version of the Conflict Tactics Scale as developed by Straus et al. The maximum margin of error for the survey was +/- 3 percentage points.
DOI: 10.25318/3210022801-fra
title: Mode d'occupation des terres, données chronologiques du Recensement de l'agriculture

description: Recensement de l’agriculture, 1921 jusqu’à présent. Superficie agricole totale, terres possédées et terres louées des autres.
DOI: 10.25828/sgbs-q698
title: ALPHA HIV Incidence and Mortality Data, Kisesa 1994-2016
DOI: 10.25318/3210022901-eng
title: Tractors, Census of Agriculture historical data

description: Census of Agriculture, 1921 to date. Tractors.
DOI: 10.25318/3210022901-fra
title: Tracteurs, données chronologiques du Recensement de l'agriculture

description: Recensement de l’agriculture, 1921 jusqu’à présent. Tracteurs.
DOI: 10.5281/zenodo.6625291
title: Chamaetylas fuelleborni decontaminated gx

description: .
DOI: 10.5281/zenodo.6625290
title: Chamaetylas fuelleborni decontaminated gx

description: .
DOI: 10.25318/3210023001-eng
title: Characteristics of farm operators, Census of Agriculture historical data

description: Census of Agriculture, 1991 to date. Characteristics of farm operators: sex, age and paid non-farm work.
DOI: 10.25921/vkt7-qz21
title: EM2040C Water Column Sonar Data Collected During H13311
DOI: 10.5281/zenodo.6625341
title: Chrysaora achlyos decontaminated gx

description: .
DOI: 10.5281/zenodo.6625340
title: Chrysaora achlyos decontaminated gx

description: .
DOI: 10.25318/3210023001-fra
title: Caractéristiques des exploitants agricoles, données chronologiques du Recensement de l'agriculture

description: Recensement de l'agriculture, 1991 jusqu’à présent. Caractéristiques des exploitants agricoles : sexe, âge et travail non agricole rémunéré.
DOI: 10.48493/w01v-fe90
title: Isotopic dataset for late medieval Capitanata (southern Italy)
DOI: 10.6084/m9.figshare.20031017
title: DU-ASL-DATA-GLOVE-DB

description: Hardware The primary hardware is a data glove consisting of three units, namely sensing, processing, and onboard power regulation unit. The sensing unit is comprised of five 2.2" flex sensors (SEN-10264) and an IMU (MPU-6050) which has a triaxial accelerometer and a triaxial gyroscope. Dataset <strong>Overview. </strong>We explored 40 signs from the standard ASL dictionary that including 26 letters and 14 words. Among these signs, 24 require only a certain finger flexion and no hand motion; hence, are addressed as static signs or gestures. Conversely, the remaining 16 signs need hand motion alongside the finger flexion to portray meaningful expression according to the ASL dictionary. Moreover, we collected the signs from 25 subjects (19 Male and 6 Female) in separate data recording sessions with a consistent protocol. Overall, three channels for acceleration in both body and earth axis, three for angular velocity, four for quaternion, and five for flex sensors were recorded in the dataset. The data was recorded by the data glove processing unit which was connected to a laptop for data storage via USB. The sampling frequency is set to 100 Hz and each gesture was repeated 10 times to record the performance variabilities of each subject. However, during a few sessions denoted in the dataset supplementary information, the laptop charger was connected which resulted in AC-induced noise all over those specific recorded data. <br> <strong>Data recording protocol.</strong> Before starting the recording process, each subject signed an approval form for the usage of their data in this research and was briefed about the data recording steps. As the subjects were not familiar with the signs before the study, they were taught each sign before the data recording via online video materials. The data was recorded by the data glove and stored on the laptop at the same time. Hence, a Python script was used on the laptop to make the handshake between the two devices and to store the data in separate folders as per the signs and the subjects. At the beginning of each data recording session, the subjects were prompted to declare their subject id and the gesture name. Afterward, a five-second countdown is prompted on the laptop screen for preparation. Each instance of the gesture data is recorded for a 1.5 seconds window and the subjects can easily perform their gesture once within that window. In a single gesture recording session, this process is repeated 10 times. <br>
DOI: 10.5519/qd.ei8ef5jy
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.25318/3210023101-eng
title: Farms classified by farm type, Census of Agriculture, 2021

description: Census of Agriculture, 2021. Farms classified by the North American Industry Classification System (NAICS).
DOI: 10.25921/yhsj-cf22
title: EM122 Water Column Sonar Data Collected During FSP180003
DOI: 10.34740/kaggle/dsv/3767034
title: Sales_Repo
DOI: 10.25318/3210023101-fra
title: Exploitations agricoles classées selon le type d'exploitation agricole, Recensement de l’agriculture, 2021

description: Recensement de l’agriculture, 2021. Exploitations agricoles classées selon le Système de classification des industries de l'Amérique du Nord (SCIAN).
DOI: 10.34681/cm7c-tc77
title: National Child Abuse and Neglect Data System (NCANDS) Combined Aggregate File (CAF) FFY 2000-2002

description: The National Child Abuse and Neglect Data System (NCANDS) Combined Aggregate File (CAF) dataset consists of State-specific data of all investigated reports of maltreatment to State child protective service agencies. The NCANDS is a federally-sponsored national data collection effort created for the purpose of tracking the volume and nature of child maltreatment reporting each year within the United States. The CAF is the State-level component of the NCANDS that replaced the Summary Data Component (SDC) beginning in the year 2000. The CAF is created by merging three different NCANDS data sources, the Child File, the Agency File, and the SDC, into a single dataset. NCANDS Case-level data are collected through the Child File data submission. States that submit a Child File also submit an Agency File, which collects State-level data for areas not covered in the Child File, such items as preventive services and screened-out referrals. Other States continued to submit NCANDS data using the SDC survey. Child File data are aggregated to the State-level by key variables and then combined with the data from the Agency file and the SDC to create the CAF. The number of children and families receiving preventive services, the number of reports and investigations of child abuse and neglect, the number of children who were the subjects of reports of abuse or neglect, the number of child victims of maltreatment, the number of child fatalities, the size of the State's CPS workforce, and other statistics are provided in the CAF. Data for from 2000 to 2002 are provided in a single data file. A variable crosswalk to the 1990-1999 SDC dataset is also provided.
DOI: 10.5517/ccdc.csd.cc23tnqb
title: CCDC 1961082: Experimental Crystal Structure Determination

description: Related Article: Hong Zeng|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27243l
title: CCDC 2057628: Experimental Crystal Structure Determination

description: Related Article: Runnan Guan, Muqing Chen, Jinpeng Xin, Xiao-Ming Xie, Fei Jin, Qianyan Zhang, Su-Yuan Xie, Shangfeng Yang|2021|J.Am.Chem.Soc.|143|8078|doi:10.1021/jacs.1c02428
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27hvj4
title: CCDC 2070816: Experimental Crystal Structure Determination

description: Related Article: Daniel Bindl, Elisabeth Heinemann, Pradeep K. Mandal, Ivan Huc|2021|Chem.Commun.|57|5662|doi:10.1039/D1CC01452H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.6625347
title: Online Supplement for An Arabic Version of The Visual Aesthetics of Websites Inventory (AR-VisAWI): Translation and Psychometric Properties

description: This is the online supplement for a translation of the Visual Aesthetics of Websites Inventory into Arabic (AR-VisAWI). In the field of human-computer interaction, the concept of visual aesthetics gained popularity after researchers started to recognize its merits and effects on user experience. Yet, no proper instrument exists to assess the visual aesthetics of websites that are intended for users who speak Arabic as their native language. As such, the aim of this study was to develop and evaluate an Arabic version of the Visual Aesthetics of Websites Inventory (VisAWI, Moshagen & Thielsch, 2010) and its short version (VisAWI-S, Moshagen & Thielsch, 2013). For this purpose, participants were asked to evaluate a randomly assigned website with the AR-VisAWI and with different validating instruments. A final sample of 223 participants was included in the analyses. This online supplement includes a codebook describing all instructions and items raw data (anonymised) and analysis script (Note: The raw data contains only the information of persons who have agreed to be included in the analysis. Some demographic information was deleted to ensure anonymity.) Questionnaire template and scoring instructions
DOI: 10.5281/zenodo.6393208
title: Online Supplement for An Arabic Version of The Visual Aesthetics of Websites Inventory (AR-VisAWI): Translation and Psychometric Properties

description: This is the online supplement for a translation of the Visual Aesthetics of Websites Inventory into Arabic (AR-VisAWI). In the field of human-computer interaction, the concept of visual aesthetics gained popularity after researchers started to recognize its merits and effects on user experience. Yet, no proper instrument exists to assess the visual aesthetics of websites that are intended for users who speak Arabic as their native language. As such, the aim of this study was to develop and evaluate an Arabic version of the Visual Aesthetics of Websites Inventory (VisAWI, Moshagen & Thielsch, 2010) and its short version (VisAWI-S, Moshagen & Thielsch, 2013). For this purpose, participants were asked to evaluate a randomly assigned website with the AR-VisAWI and with different validating instruments. A final sample of 223 participants was included in the analyses. This online supplement includes a codebook describing all instructions and items raw data (anonymised) and analysis script (Note: The raw data contains only the information of persons who have agreed to be included in the analysis. Some demographic information was deleted to ensure anonymity.) Questionnaire template and scoring instructions
DOI: 10.5517/ccdc.csd.cc290r7b
title: CCDC 2115881: Experimental Crystal Structure Determination

description: Related Article: David M. King, Benjamin E. Atkinson, Lucile Chatelain, Matthew Gregson, John A. Seed, Ashley J. Wooles, Nikolas Kaltsoyannis, Stephen T. Liddle|2022|Dalton Trans.|51|8855|doi:10.1039/D2DT00998F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc290r8c
title: CCDC 2115882: Experimental Crystal Structure Determination

description: Related Article: David M. King, Benjamin E. Atkinson, Lucile Chatelain, Matthew Gregson, John A. Seed, Ashley J. Wooles, Nikolas Kaltsoyannis, Stephen T. Liddle|2022|Dalton Trans.|51|8855|doi:10.1039/D2DT00998F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc299lz6
title: CCDC 2124398: Experimental Crystal Structure Determination

description: Related Article: Shi-Fang Yuan, Luyao Wang, Yi Yan, Tian Liu, Zygmunt Flisak, Yanping Ma, Wen-Hua Sun|2022|RSC Advances|12|15741|doi:10.1039/D2RA01547A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25318/3210023201-eng
title: Farms classified by total farm area, Census of Agriculture, 2021

description: Census of Agriculture, 2021. Farms classified by total farm area.
DOI: 10.5281/zenodo.6625364
title: Surface feature height, spacing and form drag coefficients over Arctic sea ice from Operation IceBridge, 2009-2015

description: Data used to estimate the neutral form drag coefficient over Arctic sea ice using high-resolution IceBridge laser (ATM) data, from Petty et al., (2017). The data here include the raw 1D linear profiling (along the edge of the ATM swath) data of surface feature data: e.g. 1km_xyres2m_20cm/1D/[year]/ and also 10 km mean along-track surface feature and form drag estimates: 1km_xyres2m_20cm/1D/ATMO/. The code to generate these data can be found here: https://github.com/akpetty/ibdrag2017. The Python pickle files have been converted to CSV here to aid data ingestion. 2D surface feature data using the same input data can be found here: https://zenodo.org/record/6617715 The following raw IceBridge datasets are used to create these data: L1B ATM data: https://nsidc.org/data/docs/daac/icebridge/ilatm1b/. L1B DMS imagery: http://nsidc.org/data/iodms1b}. IceBridge IDCSI4 and quick-look sea ice thickness data: http://nsidcorg/data/docs/daac/icebridge/evaluation_products/sea-ice-freeboard-snowdepth-thickness-quicklook-index.html and http://nsidc.org/data/idcsi4.html. <strong>References</strong> Petty, A. A., M. C. Tsamados, N. T. Kurtz, S. L. Farrell, T. Newman, J. P. Harbeck, D. L. Feltham, and J. A. Richter-Menge (2016), Characterizing Arctic sea ice topography using high-resolution IceBridge data, The Cryosphere, 10(3), 1161–1179, doi:10.5194/tc-10-1161-2016. Petty, A. A., M. C. Tsamados, N. T. Kurtz (2017), Atmospheric form drag over Arctic sea ice using remotely sensed ice topography observations, J. Geophys. Res. Earth Surf., 122, doi:10.1002/2017JF004209.
DOI: 10.5281/zenodo.6625363
title: Surface feature height, spacing and form drag coefficients over Arctic sea ice from Operation IceBridge, 2009-2015

description: Data used to estimate the neutral form drag coefficient over Arctic sea ice using high-resolution IceBridge laser (ATM) data, from Petty et al., (2017). The data here include the raw 1D linear profiling (along the edge of the ATM swath) data of surface feature data: e.g. 1km_xyres2m_20cm/1D/[year]/ and also 10 km mean along-track surface feature and form drag estimates: 1km_xyres2m_20cm/1D/ATMO/. The code to generate these data can be found here: https://github.com/akpetty/ibdrag2017. The Python pickle files have been converted to CSV here to aid data ingestion. 2D surface feature data using the same input data can be found here: https://zenodo.org/record/6617715 The following raw IceBridge datasets are used to create these data: L1B ATM data: https://nsidc.org/data/docs/daac/icebridge/ilatm1b/. L1B DMS imagery: http://nsidc.org/data/iodms1b}. IceBridge IDCSI4 and quick-look sea ice thickness data: http://nsidcorg/data/docs/daac/icebridge/evaluation_products/sea-ice-freeboard-snowdepth-thickness-quicklook-index.html and http://nsidc.org/data/idcsi4.html. <strong>References</strong> Petty, A. A., M. C. Tsamados, N. T. Kurtz, S. L. Farrell, T. Newman, J. P. Harbeck, D. L. Feltham, and J. A. Richter-Menge (2016), Characterizing Arctic sea ice topography using high-resolution IceBridge data, The Cryosphere, 10(3), 1161–1179, doi:10.5194/tc-10-1161-2016. Petty, A. A., M. C. Tsamados, N. T. Kurtz (2017), Atmospheric form drag over Arctic sea ice using remotely sensed ice topography observations, J. Geophys. Res. Earth Surf., 122, doi:10.1002/2017JF004209.
DOI: 10.25318/3210023201-fra
title: Exploitations agricoles classées selon la superficie agricole totale, Recensement de l’agriculture, 2021

description: Recensement de l’agriculture, 2021. Exploitations agricoles classées selon la superficie agricole totale.
DOI: 10.25318/3210023301-eng
title: Farms classified by area in crops and summerfallow, Census of Agriculture, 2021

description: Census of Agriculture, 2021. Farms classified by area in crops and summerfallow (excluding Christmas tree area).
DOI: 10.25318/3210023301-fra
title: Exploitations agricoles classées selon la superficie des terres en culture et en jachère, Recensement de l’agriculture, 2021

description: Recensement de l’agriculture, 2021. Exploitations agricoles classées selon la superficie des terres en culture et en jachère (excluant la superficie en arbres de Noël).
DOI: 10.6084/m9.figshare.20022590
title: PaperBLAST and SitesBLAST database from April 2022

description: Source code and data files for PaperBLAST, SitesBLAST, and Curated BLAST for Genomes. The database is as of April 2022. The code is as of June 2022.<br> Exploding the code tarball will create a PaperBLAST/ directory. The code is in the cgi/ bin/ and lib/ subdirectories. <br> To install the data, create a data subdirectory, and explode the PaperBLAST_Apr2022 tarball into that directory. This includes the SQLite database (litsearch.db), and two BLAST databases (uniq.faa for PaperBLAST and hassites.faa for SitesBLAST). <br> For up to date code and databases, see https://github.com/morgannprice/PaperBLAST
DOI: 10.5281/zenodo.6624972
title: Supporting information for "Measuring understory vegetation structure using a novel mixed-reality device"

description: MEE Appendix 1: Code necessary to extract vegetation detection data from VegSense scans MEE Appendix 2: Supplementary methods MEE Appendix 3: Instructions for downloading the test version of VegSense onto the HoloLens DBH.Analysis.FINAL.R: Code for all data analysis used in the study HoloLens MEM samples test.csv: vegetation detection data HoloLens MEM samples 6_8.csv: tree/sapling detection and DBH measurements VegSense.zip- Underlying code for VegSense application AppPackages.zip- Test VegSense application packages available to download on the HoloLens
DOI: 10.5281/zenodo.6363643
title: Supporting information for "Measuring understory vegetation structure using a novel mixed-reality device"

description: MEE Appendix 1: Code necessary to extract vegetation detection data from VegSense scans MEE Appendix 2: Supplementary methods MEE Appendix 3: Instructions for downloading the test version of VegSense onto the HoloLens DBH.Analysis.FINAL.R: Code for all data analysis used in the study HoloLens MEM samples test.csv: vegetation detection data HoloLens MEM samples 6_8.csv: tree/sapling detection and DBH measurements VegSense.zip- Underlying code for VegSense application AppPackages.zip- Test VegSense application packages available to download on the HoloLens
DOI: 10.25318/3210023401-eng
title: Land tenure, Census of Agriculture, 2021

description: Census of Agriculture, 2021. Land owned, leased, rented, crop-shared, used through other arrangements or used by others.
DOI: 10.25318/3210023401-fra
title: Mode d'occupation des terres, Recensement de l’agriculture, 2021

description: Recensement de l’agriculture, 2021. Terres possédées, louées, en métayage, utilisées sous d'autres arrangements ou exploitées par d'autres.
DOI: 10.25625/avaw2y/gkb6sm
title: Global mantle clinopyroxene data (major and trace elements).tab

description: We downloaded compositional data for clinopyroxenes from mantle xenoliths from 972 locations worldwide from the GEOROC database (http://georoc.mpch-mainz.gwdg.de/georoc/; accessed 14 July 2020). Each location includes multiple samples and analyses (Figure S1). To exclude unreliable samples, we used only clinopyroxenes with 40–60 wt.% SiO2, &lt;40 wt.% MgO, &lt;30 wt.% FeOT (the superscript ‘T’ indicates total iron), &lt;26 wt.% CaO, and oxide totals of 98.5–101.5 wt.%. Elements missing from &gt;60% of the entire dataset were not considered. After this initial filtering, our dataset contained 21,605 observations (rows) corresponding to clinopyroxene major element analyses (SiO2, TiO2, Al2O3, Cr2O3, FeOT, CaO, MgO, MnO, and Na2O), and 2,967 rows of trace element analyses (including Sc, Ti, V, Cr, Ni, Rb, Sr, Y, Zr, Nb, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Hf, Ta, Pb, Th, and U) (Figure S2). In general, the proportion of missing values varies among elements, with major element data being rather complete, e.g., 5% missing analyses for Cr2O3 (1,024 of 21,605), and a higher proportion of missing data for trace elements, e.g., 32% missing analyses for Ti (961 of 2,967).
DOI: 10.25625/avaw2y/na4dpo
title: 2022-06_AVAW2Y_Qin_data.tab

description: :unav