cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5588289
title: Data from a three-phase Delphi study used to investigate Knowledge Infrastructure for Research Data in Norway, KIRDN_Data; PhD project

description: A modified three-phase Delphi study was used to explore the knowledge infrastructure for research data in Norway. The study includes different stakeholders involved in research data sharing. A Delphi study is characterised by the use of an expert panel to elicit opinions on a shared reality from different perspectives. Data collection is performed in several rounds with the intention of reaching consensus or solving an issue. A group of 24 experts took part in the study. The group consisted of policy-makers, representatives of national service providers, and researchers and research support staff from four Norwegian universities. The participants were invited based on their involvement in the development of policies, infrastructure or data-related research support. The research support staff were recruited to include representatives from different research support services at the universities, including libraries, research offices and IT departments. While the researchers were selected from based on their receival of EU funding with requirements of data management plans. Data were collected in three phases. The first phase, the ‘exploration phase’, was conducted using open interviews lasting approximately one hour in January/February 2018. The purpose of this phase was to obtain an initial overview of the panel members opinions’ on issues regarding research data management. In the second phase, the ‘evaluation phase’, conducted in August/September 2018, participants answered a survey containing nine questions on topics such as data stewardship, DMPs, ethical aspects of data sharing and core functions in a research data infrastructure. The survey was designed to further explore issues and tensions uncovered in the first interviews. Several of the questions were formulated as statements that the participants were asked to agree or disagree upon. The third, ‘concluding phase’ was conducted using interviews in March/April 2019. These interviews lasted approximately 30 minutes and were based on results from the questionnaire as well as the first interview. Participants were asked whether they had thoughts on the preliminary findings of the study. Based on requests from some of the participants, the questions were sent to all participants prior to the data collection, in all three phases. The participants were also sent the transcripts from the interviews and were asked for permission to share the complete material or parts of the data material to which they contributed.
DOI: 10.21421/d2/lhm7nx/ervde1
title: 4.Data file of Plot details.tab

description: :unav
DOI: 10.21421/d2/lhm7nx/hcmqsb
title: 2.Description file of Experiment.docx

description: :unav
DOI: 10.21421/d2/lhm7nx/aynazm
title: 5.Data file of Field plan.tab

description: :unav
DOI: 10.21421/d2/lhm7nx/a8ax9w
title: 4.Description file of Plot details.docx

description: :unav
DOI: 10.21421/d2/lhm7nx/kh93d6
title: 3.Description file of Soil bulk density.docx

description: :unav
DOI: 10.21421/d2/lhm7nx/rez7km
title: 6.Description file of Weather.docx

description: :unav
DOI: 10.21421/d2/lhm7nx/tbxmts
title: 6.Data file of Weather.tab

description: :unav
DOI: 10.21421/d2/lhm7nx/sttymc
title: 1.Description file of Growth and development.docx

description: :unav
DOI: 10.21421/d2/lhm7nx/5bewes
title: 2.Data file of Experiment.tab

description: :unav
DOI: 10.21421/d2/lhm7nx/s1fltx
title: 1.Data file of Growth and development.tab

description: :unav
DOI: 10.21421/d2/lhm7nx/aejtmy
title: 3.Data file of Soil bulk density.tab

description: :unav
DOI: 10.6084/m9.figshare.15123327
title: Supplementary Material for: Experience of Excess Skin and Attitude to Body Contouring Surgery of a Chinese Post-Bariatric Population

description: <b><i>Introduction:</i></b> Western studies have explored post-bariatric patients concerning their views on excess skin and body contouring surgery (BCS), but Asian data were lacking. This study aims to investigate the experience of excess skin and attitude to BCS of a Chinese post-bariatric population. <b><i>Methods:</i></b> A total of 210 Chinese patients who underwent bariatric surgery from March 2015 to September 2018 were cross-sectional studied using the Sahlgrenska Excess Skin Questionnaire and a study-specific questionnaire. <b><i>Results:</i></b> The survey response rate was 61.4%. Most responders (78.2%) reported they had excess skin, and the most common sites were the abdomen (70.2%) and the upper arms (61.3%). Most responders (66.1%) reported being bothered by impaired health-related quality of life (HRQoL), and the most common problem was “the feeling of having unattractive body appearance” (42.7%). Many patients (37.9%) desired for BCS, and “the impact of excess skin is not serious enough” was the reason why not undergoing BCS being chosen most (28.1%), then “the cost is too high” (20.2%) and “worrying about the risk or complications of BCS” (18.4%). Younger age, female gender, higher weight loss, having full-time job, and earning higher income were independent factors increasing their desires for BCS. <b><i>Conclusions:</i></b> Most Chinese post-bariatric patients have excess skin and are bothered by impaired HRQoL. The abdomen and upper arms are the sites where patients are most seriously affected and most eager for BCS. The conservative attitude toward BCS and the cost without reimbursement are the main barriers.
DOI: 10.6084/m9.figshare.15123327.v1
title: Supplementary Material for: Experience of Excess Skin and Attitude to Body Contouring Surgery of a Chinese Post-Bariatric Population

description: <b><i>Introduction:</i></b> Western studies have explored post-bariatric patients concerning their views on excess skin and body contouring surgery (BCS), but Asian data were lacking. This study aims to investigate the experience of excess skin and attitude to BCS of a Chinese post-bariatric population. <b><i>Methods:</i></b> A total of 210 Chinese patients who underwent bariatric surgery from March 2015 to September 2018 were cross-sectional studied using the Sahlgrenska Excess Skin Questionnaire and a study-specific questionnaire. <b><i>Results:</i></b> The survey response rate was 61.4%. Most responders (78.2%) reported they had excess skin, and the most common sites were the abdomen (70.2%) and the upper arms (61.3%). Most responders (66.1%) reported being bothered by impaired health-related quality of life (HRQoL), and the most common problem was “the feeling of having unattractive body appearance” (42.7%). Many patients (37.9%) desired for BCS, and “the impact of excess skin is not serious enough” was the reason why not undergoing BCS being chosen most (28.1%), then “the cost is too high” (20.2%) and “worrying about the risk or complications of BCS” (18.4%). Younger age, female gender, higher weight loss, having full-time job, and earning higher income were independent factors increasing their desires for BCS. <b><i>Conclusions:</i></b> Most Chinese post-bariatric patients have excess skin and are bothered by impaired HRQoL. The abdomen and upper arms are the sites where patients are most seriously affected and most eager for BCS. The conservative attitude toward BCS and the cost without reimbursement are the main barriers.
DOI: 10.21421/d2/lhm7nx
title: Data on multi factorial treatments in Rabi Sorghum for 2018-19 at Patancheru, ICRISAT

description: Sequential observations of agronomical important traits during cropping season for Rabi Sorghum Crop during 2018 and 2019 season in ICRISAT Patancheru campus research fields. This dataset has the agronomic details of 18 sorghum genotypes. These 18 genotypes were subjected to 3 different treatment combinations which are well-watered high nitrogen high density (WW HN HD), well-watered high nitrogen low density (WW HN LD), water stress high nitrogen high density (WS HN HD). In well-watered treatment all the genotypes were replicated thrice and in water stress treatment plants were replicated 6 times. Plants were sampled at 3 different crop growth stages (6 weeks, booting and at maturity) in all the treatment combinations. At each stage leaf biomass, stem biomass and grain biomass (for the samples at maturity) were measured. All the agronomic practices like irrigation and fertilization, etc are provided. Soil sampling was done before sowing and after harvesting to know the soil moisture. Weather data and field layout are also provided. Four plants were selected in each plot and were observed for 50% flowering. At maturity these 4 plants per plot were harvested and panicles were threshed and total seed weight, 50 seed weight were recorded. Experiment location on Google Map
DOI: 10.21421/d2/7m3mzt/ds4ik8
title: 6.Description file of Weather.docx

description: :unav
DOI: 10.21421/d2/7m3mzt/iiaihs
title: 1.Description file of Growth and development.docx

description: :unav
DOI: 10.21421/d2/7m3mzt/5uqxqa
title: 3.Data file of Soil bulk density.tab

description: :unav
DOI: 10.21421/d2/7m3mzt/ikwjyi
title: 6.Data file of Weather.tab

description: :unav
DOI: 10.21421/d2/7m3mzt/bkaz41
title: 1.Data file of Growth and development.tab

description: :unav
DOI: 10.21421/d2/7m3mzt/hh1txu
title: 3.Description file of Soil bulk density.docx

description: :unav
DOI: 10.21421/d2/7m3mzt/cfshay
title: 2.Data file of Experiment.tab

description: :unav
DOI: 10.21421/d2/7m3mzt/psvh7m
title: 4.Description file of Plot details.docx

description: :unav
DOI: 10.21421/d2/7m3mzt/cwepog
title: 5.Data file of Filed plan.tab

description: :unav
DOI: 10.21421/d2/7m3mzt/hdjid5
title: 4.Data file of Plot details.tab

description: :unav
DOI: 10.21421/d2/7m3mzt/7dqvhp
title: 2.Description file of Experiment.docx

description: :unav
DOI: 10.21421/d2/7m3mzt
title: Data on multi factorial treatments in Rabi Sorghum for 2017-18 in Plant Quarantine E2, Patancheru, ICRISAT

description: Sequential observations of agronomical important traits during cropping season for Rabi Sorghum Crop during 2017 and 2018 season in ICRISAT Patancheru campus research fields at Plant Quarantine E2 field. This dataset includes the research on the evaluation of 31 genotypes of Sorghum. Out of these 31 entries, 5 genotypes were studied in detail for the plant growth dynamics for which sequential sampling was done at different stages of plant growth like at 6 weeks (vegetative) stage, flowering and at maturity. At each stage leaf biomass, stem biomass and grain biomass (for the samples at maturity) were measured. Leaf area was measured for the samples that were taken at 6 weeks and flowering stages with the help this specific leaf area was calculated. For the rest of the 26 genotypes date of fifty percent flowering was recorded and were harvested at maturity. For all the samples that were harvested at maturity, panicles were threshed, total grain weight, 50 grain weight were recorded. Experiment location on Google Map
DOI: 10.6084/m9.figshare.14526954
title: Comparison of Longitudinal and Cross-Sectional Approaches in Studies on Knowledge, Attitude and Practices Related to Non-Medical Tranquilizer Use

description: Datasets analyzed in the study "Comparison of Longitudinal and Cross-Sectional Approaches in Studies on Knowledge, Attitude and Practices Related to Non-Medical Tranquilizer Use"<br>
DOI: 10.6084/m9.figshare.14526954.v1
title: Comparison of Longitudinal and Cross-Sectional Approaches in Studies on Knowledge, Attitude and Practices Related to Non-Medical Tranquilizer Use

description: Datasets analyzed in the study "Comparison of Longitudinal and Cross-Sectional Approaches in Studies on Knowledge, Attitude and Practices Related to Non-Medical Tranquilizer Use"<br>
DOI: 10.5281/zenodo.5588393
title: Supplementary material S1. Character list and character state matrix.

description: <strong>Supplementary material S1. </strong>Character list and character state matrix. Jiří Kolibáč, Vitalii I. Alekseev, Kristaps Kairišs and Andris Bukejs: Systematic placement and new data on the checkered beetles <em>Aberrokorynetes</em> Winkler and <em>Visokorynetes</em> Winkler (Coleoptera: Cleridae) from Eocene Baltic amber obtained from X-ray tomography. Historical Biology, DOI: 10.1080/08912963.2021.1994561
DOI: 10.5281/zenodo.5588392
title: Supplementary material S1. Character list and character state matrix.

description: <strong>Supplementary material S1. </strong>Character list and character state matrix. Jiří Kolibáč, Vitalii I. Alekseev, Kristaps Kairišs and Andris Bukejs: Systematic placement and new data on the checkered beetles <em>Aberrokorynetes</em> Winkler and <em>Visokorynetes</em> Winkler (Coleoptera: Cleridae) from Eocene Baltic amber obtained from X-ray tomography. Historical Biology, DOI: 10.1080/08912963.2021.1994561
DOI: 10.25721/5w23-ah78
title: Marche pour danser
DOI: 10.25345/c5p85c
title: MassIVE MSV000088249 - DOM Interlab-LCMS 2021- Lab 023
title: Interlab study of marine dissolved organic matter and algae extracts.
DOI: 10.6084/m9.figshare.16843417
title: Reactive phase data U1339D

description: Reactive Fe, Mn and Al content in marine sediment and tephra samples from IODP Hole U1339D
DOI: 10.6084/m9.figshare.16843417.v1
title: Reactive phase data U1339D

description: Reactive Fe, Mn and Al content in marine sediment and tephra samples from IODP Hole U1339D
DOI: 10.6084/m9.figshare.13794008
title: Emiliania huxleyi pan-transcriptome: mRNA, protein, and annotation

description: This project contains the files of the Emiliania huxleyi pan-transcriptome. It was constructed from Illumina reads of the following strains: CCMP2090, CCMP373, CCMP374.<br>Included are the following files:<br>unified_loci_Ehux_v4_May2020.fasta - one representative transcript per locus<br>unified_transcripts_Ehux_v4_May2020.fasta - all transcripts<br>unified_pep_Ehux_v4_Nov2020.fasta - Blast based translation of loci<br>ehux_kegg_reformat_May2020.txt - KEGG pathway annotation<br>blast2go_ehux_annot.ids - GO term annotation (Ontologizer compatible)<br><br>ehux_blast2go_KEGG_merged.xlsx - joint annotation file (KEGG, GO) for loci<br>snps_hard_filtered.recode.vcf - SNPs called and filtered on the representative transcripts, in four strains (CCMP2090, CCMP373, CCMP374, CCMP379)<br>indel_hard_filtered.recode.vcf - Indels called and filtered on the representative transcripts, in four strains (CCMP2090, CCMP373, CCMP374, CCMP379)<br><br><br><br><br>
DOI: 10.5281/zenodo.3824150
title: East Caucasian villages dataset

description: This dataset contains a list of villages in the eastern Caucasus, their coordinates and the language spoken there, as well as dialect affiliation based on available literature (and partially personal communication with experts).
DOI: 10.6084/m9.figshare.16843465
title: Carbon content, carbon isotope composition U1339D

description: All carbon-related parameters
DOI: 10.6084/m9.figshare.16843465.v1
title: Carbon content, carbon isotope composition U1339D

description: All carbon-related parameters
DOI: 10.6084/m9.figshare.16695616
title: CCFD_dataset

description: The dataset has been released by [1], which had been collected and analysed during a research collaboration of Worldline and the Machine Learning Group (http://mlg.ulb.ac.be) of Université Libre de Bruxelles (ULB) on big data mining and fraud detection. <br>[1] Pozzolo, A. D., Caelan, O., Johnson, R. A., and Bontempi, G. (2015). Calibrating Probability with Undersampling for Unbalanced Classification. 2015 IEEE Symposium Series on Computational, pp. 159-166, doi: 10.1109/SSCI.2015.33 <br>open source kaggle : https://www.kaggle.com/mlg-ulb/creditcardfraud
DOI: 10.6084/m9.figshare.16843213
title: Data_Potential ODmatrix (for calculate time)

description: (1) The dataset is the potential OD travel matrix from all communities to tertiary hospitals in Chengdu city, it is used to caculate the time cost of each pair of OD matrix by calling the API of path planning function of Amap, which is a set of interfaces for walking, bus, driving query and driving distance and time calculation, it can plan different driving paths according to the origin, destination and modes of transportation, and calculate the travel distance and time of each path in consideration of traffic conditions.(2) The dataset is a csv file.<br>
DOI: 10.6084/m9.figshare.16843213.v1
title: Data_Potential ODmatrix (for calculate time)

description: (1) The dataset is the potential OD travel matrix from all communities to tertiary hospitals in Chengdu city, it is used to caculate the time cost of each pair of OD matrix by calling the API of path planning function of Amap, which is a set of interfaces for walking, bus, driving query and driving distance and time calculation, it can plan different driving paths according to the origin, destination and modes of transportation, and calculate the travel distance and time of each path in consideration of traffic conditions.(2) The dataset is a csv file.<br>
DOI: 10.6084/m9.figshare.16843477
title: Results of dithionitte leaching experiment, U1339D

description: Results of dithionite extraction experiment
DOI: 10.6084/m9.figshare.16843477.v1
title: Results of dithionitte leaching experiment, U1339D

description: Results of dithionite extraction experiment
DOI: 10.5281/zenodo.5560843
title: MED-GOLD Indicators for the Wine pilot over Douro Valley based on High Resolution Climate projections

description: Indicators of interest for the Wine sector over the Douro Valley using high resolution climate projections. GDD (Growing Degree Days) - summation of daily differences between daily temperature averages and 10 for the period April-October GST (Growing Season Temperature) - average of daily average temperatures for the period April-October SprR (Spring Rain) - Precipitation accumulated between 21st April-to 21st June, HarvR (Harvest Rain)-Precipitation accumulated between 21 August and 21 October SU35 -number of days with temperature higher than 35°C for the period April-October, WSDI (Warm Spell Duration Index) -days with at least 6 consecutive days when the daily temperature maximum exceeds its 90th percentile for the period April-October. The results are based on an sub-ensemble of five RCMs from the EURO-CORDEX modelling experiment which have been statistically downscaled to 1km x1km horizontal resolution using the PTHRES gridded dataset as the reference dataset. More details can be found in Raül Marcos-Matamoros, (2018). Report on the methodology followed to implement the wine pilot services. Zenodo. https://doi.org/10.5281/zenodo.4543337 Datasets computed by National Observatory of Athens, in collaboration with SOGRAPE VINHOS S.A. in the framework of the European MED-GOLD project, funded from the European Union's Horizon 2020 Research and Innovation programme under Grant agreement No.776467
description: Files in netcdf format
DOI: 10.5281/zenodo.5560842
title: MED-GOLD Indicators for the Wine pilot over Douro Valley based on High Resolution Climate projections

description: Indicators of interest for the Wine sector over the Douro Valley using high resolution climate projections. GDD (Growing Degree Days) - summation of daily differences between daily temperature averages and 10 for the period April-October GST (Growing Season Temperature) - average of daily average temperatures for the period April-October SprR (Spring Rain) - Precipitation accumulated between 21st April-to 21st June, HarvR (Harvest Rain)-Precipitation accumulated between 21 August and 21 October SU35 -number of days with temperature higher than 35°C for the period April-October, WSDI (Warm Spell Duration Index) -days with at least 6 consecutive days when the daily temperature maximum exceeds its 90th percentile for the period April-October. The results are based on an sub-ensemble of five RCMs from the EURO-CORDEX modelling experiment which have been statistically downscaled to 1km x1km horizontal resolution using the PTHRES gridded dataset as the reference dataset. More details can be found in Raül Marcos-Matamoros, (2018). Report on the methodology followed to implement the wine pilot services. Zenodo. https://doi.org/10.5281/zenodo.4543337 Datasets computed by National Observatory of Athens, in collaboration with SOGRAPE VINHOS S.A. in the framework of the European MED-GOLD project, funded from the European Union's Horizon 2020 Research and Innovation programme under Grant agreement No.776467
description: Files in netcdf format
DOI: 10.5281/zenodo.5141727
title: Normalized Multi-band Drought Index for Douro Valley based on MODIS

description: <strong>Normalized Multi-band Drought Index</strong> (NMDI) calculated using MODIS09 imagery provided by USGS/EROS.The original MODIS09 bands were used as data source and then the nmdi was calculated. NMDI uses the 860 nm channel as the reference; instead of using a single liquid water absorption channel, however, it uses the difference between two liquid water absorption channels centered at 1640 nm and 2130 nm as the soil and vegetation moisture sensitive band. Analysis revealed that by combining information from multiple near infrared, and short wave infrared channels, NMDI has enhanced the sensitivity to drought severity, and is well suited to estimate both soil and vegetation moisture.( Lingli Wang, 2007) https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007GL031021 Each compressed file contains the NDVI by years. Internally each file have an ISO TC 211 metadata with a complete geographical description. spatial resolution: 463.313m<br> format: GeoTiff<br> reference system:SR-ORG 6842 To easily manage the data, each file follow name structure: YYYYMMDD_medgold_workpackage_AoI_sensor_index. YYYYMMDD: Imagery acquisition date medgold: Project name sensor: sensor name workpackage: sectorial workpackage name ( WP2 - Olive Oil Sector, WP3 – Wine Grape sector, WP4- Durum wheat pasta sector) Aoi: Andalusia, Douro Valley. Index: NDVI, NMDI, NDWI Example: 20000218_medgold_wp3_douro_MOD09A1_nmdi
description: Datasets computed by GMV Aerospace and Defense, in the framework of the European MED-GOLD project, funded from the European Union's Horizon 2020 Research and Innovation programme under Grant agreement No. 776467 Disclaimer: the producer of this dataset is not responsible of the results due to errors in the source dataset (sensor failures, clouds, reflectance calculations, etc.)