cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5286/isis.e.rb1810786-1
title: HIGH FIELD MUSR STUDY OF SHORT AND LONG RANGE MAGNETIC CORRELATIONS IN CeNi9GeGa3 AND CeNi9Ga4

description: The interesting magnetic phase diagram results from competing Kondo and RKKY interactions with magnetic frustration. One interesting system in this context may be CeNi9Ga4 and solid solutions CeNi9Ge4-xGax which crystallize in a tetragonalstructure. CeNi9Ge4 was found to be near a heavy fermion quantum critical point, showing a paramagnetic ground state with a huge Sommerfeld coefficient, exceeding 5.5 J/molK² . The latter appears being stabilized by its quasi-quartet crystal field (CEF) ground state degeneracy. In CeNi9Ge4-xGax we observed a long range magnetic order with a maximum TN ~2.8 K for CeNi9Ge3Ga, while CeNi9Ga4 shows a weak magnetic transition near 0.5K, which change from FM-type to AFM-type in an applied field &gt;=0.5T. We therefore proposed here to investigate these compounds using musr measurements on HiFi to understand the complex nature of the magnetic ordering.
DOI: 10.26188/5d9b095832f41
title: Year 2016: Space syntax analysis map

description: A package of space syntax files for analysis:1. sx-space-syntax-2016.bak2. sx-td-2016.bak3. sx-td-2016.dxf4. sx-space-syntax-2016.dwg5. sx-td-2016.dwg6. sx-td-pp-2016.bak7. sx-td-pp-2016.dwg8. sy-td-190619-eps.jpg9. sy-td-a_Axial_Map.csv10. sy-td-190619.eps11. sy-td-a.graph12. sy-td-a_Axial_Map.mid13. sy-td-a_Axial_Map.mif14. sy-td-a_Axial_Map.txt15. 190619-w-sy-td.JPG16. 190619-w-sy-td-frame2.JPG<br>17. sy-td-a_Axial_Map.txt<br>18.190619-w-sy-td-frame.JPG<br><br><br><br><br><br>
DOI: 10.6084/m9.figshare.13214489
title: area_risco_modelo2_spatialjointracadobuffer100m.sbx

description: This dataset refers to a photogrammetric point cloud obtained with an uav and digital camera in Blumenau, Santa Catarina, Brazil, aiming to a 3d reconstruction of a power line structures.
DOI: 10.6084/m9.figshare.13214489.v1
title: area_risco_modelo2_spatialjointracadobuffer100m.sbx

description: This dataset refers to a photogrammetric point cloud obtained with an uav and digital camera in Blumenau, Santa Catarina, Brazil, aiming to a 3d reconstruction of a power line structures.
DOI: 10.21227/j4hz-y522
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 90+ different keywords and hashtags that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location.The paper associated with this dataset is available here: Design and analysis of a large-scale COVID-19 tweets dataset-------------------------------------Related: Coronavirus (COVID-19) Tweets Sentiment Trend (Global), Coronavirus (COVID-19) Tweets Dataset and Tweets Originating from India During COVID-19 Lockdowns 1, 2, 3, 4-------------------------------------Below is the quick overview of this dataset.— Dataset name: GeoCOV19Tweets Dataset— Number of tweets : 259,128 tweets— Coverage : Global— Language : English (EN)— Dataset usage terms : By using this dataset, you agree to (i) use the content of this dataset and the data generated from the content of this dataset for non-commercial research only, (ii) remain in compliance with Twitter's Developer Policy and (iii) cite the following paper:Lamsal, R. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence (2020). https://doi.org/10.1007/s10489-020-02029-z— Primary dataset : Coronavirus (COVID-19) Tweets Dataset (COV19Tweets Dataset)— Dataset updates : Everyday— Active keywords and hashtags: keywords.tsvPlease visit this page (primary dataset) for details regarding the collection date and time (and other notes) of each CSV file present in this dataset.
DOI: 10.5281/zenodo.4073034
title: Tara Pacific metabarcoding sequencing (16S, 18S, ITS2) reference & replication tables version 1

description: The tables in this dataset associate metabarcoding sequencing files generated by Genoscope (i.e. fastq.gz files with informative filename structures; with sequencing file pairs associated to unique 'readset' identifiers; housed on their FTP server at www.genoscope.cns.fr/sadc/tarapacific/METABARCODING; with the 'METAB' sequence strategy identifier as part of the sequencing file name) with their associated 'sample-id_source' identifier; as detailed in the 'TARA-PACIFIC_samples-provenance' file part of the 'Tara Pacific samples provenance and environmental context' Zenodo publication (DOI: 10.5281/zenodo.4068292) part of the 'tarapacific' Zenodo community). The main purpose of these tables is to act as a reference to identify samples (i.e., with a single 'sample-id_source') for which sequencing replication exists, per primer set (i.e., more than one set of fastq.gz sequencing files were generated, pre primer set). In the case of replication, these tables classify the replication into three classes color coded as green (same DNA extraction, same PCR, same sequencing run, different sequencing lane), yellow (same DNA extraction, same PCR, different sequencing run) and red (different DNA extraction and/or different PCR). It should be noted that in the vast majority of cases a 'sample-id_source' associates to only one readset per primer set. For a full description of the dataset, please see the included README.
description: Special thanks to the Tara Ocean Foundation, the R/V Tara crew and the Tara Pacific Expedition Participants (https://doi.org/10.5281/zenodo.3777760). We are keen to thank the commitment of the following institutions for their financial and scientific support that made this unique Tara Pacific Expedition possible: CNRS, PSL, CSM, EPHE, Genoscope, CEA, Inserm, Université Côte d'Azur, ANR, agnès b., UNESCO-IOC, the Veolia Foundation, the Prince Albert II de Monaco Foundation, Région Bretagne, Billerudkorsnas, AmerisourceBergen Company, Lorient Agglomération, Oceans by Disney, L'Oréal, Biotherm, France Collectivités, Fonds Français pour l'Environnement Mondial (FFEM), Etienne Bourgois, and the Tara Ocean Foundation teams. Tara Pacific would not exist without the continuous support of the participating institutes. The authors also particularly thank Serge Planes, Denis Allemand, and the Tara Pacific consortium.
description: {"references": ["Pesant et al., 2020. Tara Pacific samples provenance and environmental context - version 1 (Version version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4068293"]}
DOI: 10.6084/m9.figshare.13214462
title: Supplementary Material for: Salivary Hemoglobin Protects against Erosive Tooth Wear in Gastric Reflux Patients

description: <b><i>Objective:</i></b> Saliva is the most important biological factor to protect against erosive tooth wear (ETW). Gastroesophageal reflux disease (GERD) patients have an increased risk of ETW due to the frequent presence of intrinsic acids in the oral cavity. Remarkably, not all GERD patients suffer from ETW, which might be due to differences in the composition of the saliva. <b><i>Methods:</i></b> This study compared the proteomic profile of saliva in patients (1) with GERD and ETW (basic erosive wear examination, BEWE, score ≥9; GE group) and (2) with GERD without ETW (BEWE = 0; GNE group) using shotgun label-free quantitative proteomic analysis nLC-ESI-MS/MS. The ability of hemoglobin (Hb) to protect against initial enamel erosion caused by a daily 10-s immersion of enamel specimens in 0.01 M HCl (pH 2.3) for 3 days was evaluated in vitro for proof of concept. Surface hardness change was used as response variable. <b><i>Results:</i></b> The differential expression of Hb subunits was significantly increased in the GNE group versus the GE group, in particular the Hb α-subunit that showed a &gt;22-fold increase. Expressions of serum albumin (4.5-fold) and isoforms of cytoskeletal keratin type II (&gt;3-fold) were also increased in the GNE group. Proteinase inhibitors, such as α<sub>1</sub>-antitrypsin and α<sub>2</sub>-macroglobulin, were only identified in the GNE group. In vitro, Hb (1.0 and 4.0 mg/mL) significantly reduced initial enamel erosion compared to a negative control after 3 days. <b><i>Conclusions:</i></b> Our results indicate that many proteins, with special emphasis on Hb, may be involved in the resistance of GERD patients to the occurrence of ETW. These proteins may be candidates for inclusion in dental products to protect against ETW.
DOI: 10.6084/m9.figshare.13214462.v1
title: Supplementary Material for: Salivary Hemoglobin Protects against Erosive Tooth Wear in Gastric Reflux Patients

description: <b><i>Objective:</i></b> Saliva is the most important biological factor to protect against erosive tooth wear (ETW). Gastroesophageal reflux disease (GERD) patients have an increased risk of ETW due to the frequent presence of intrinsic acids in the oral cavity. Remarkably, not all GERD patients suffer from ETW, which might be due to differences in the composition of the saliva. <b><i>Methods:</i></b> This study compared the proteomic profile of saliva in patients (1) with GERD and ETW (basic erosive wear examination, BEWE, score ≥9; GE group) and (2) with GERD without ETW (BEWE = 0; GNE group) using shotgun label-free quantitative proteomic analysis nLC-ESI-MS/MS. The ability of hemoglobin (Hb) to protect against initial enamel erosion caused by a daily 10-s immersion of enamel specimens in 0.01 M HCl (pH 2.3) for 3 days was evaluated in vitro for proof of concept. Surface hardness change was used as response variable. <b><i>Results:</i></b> The differential expression of Hb subunits was significantly increased in the GNE group versus the GE group, in particular the Hb α-subunit that showed a &gt;22-fold increase. Expressions of serum albumin (4.5-fold) and isoforms of cytoskeletal keratin type II (&gt;3-fold) were also increased in the GNE group. Proteinase inhibitors, such as α<sub>1</sub>-antitrypsin and α<sub>2</sub>-macroglobulin, were only identified in the GNE group. In vitro, Hb (1.0 and 4.0 mg/mL) significantly reduced initial enamel erosion compared to a negative control after 3 days. <b><i>Conclusions:</i></b> Our results indicate that many proteins, with special emphasis on Hb, may be involved in the resistance of GERD patients to the occurrence of ETW. These proteins may be candidates for inclusion in dental products to protect against ETW.
DOI: 10.5257/iea/ng/2020
title: Natural Gas Information (2020 Edition)

description: Natural Gas Information is a detailed reference work on gas supply and demand covering not only the OECD countries but also the rest of the world; this publication contains essential information on LNG and pipeline trade, gas reserves, storage capacity and prices. The main part of the dataset concentrates on OECD countries, showing a detailed supply and demand balance for each country and for the three OECD regions: Americas, Asia-Oceania and Europe, as well as a breakdown of gas consumption by end user. Import and export data are reported by source and destination.
DOI: 10.6084/m9.figshare.13214564
title: Supplementary Material for: Blood Pressure Variability and Prognosis in Hemodialysis Patients: A Systematic Review and Meta-Analysis

description: <b><i>Background:</i></b> The prognostic value of blood pressure variability (BPV) in patients receiving hemodialysis is inconclusive. In this study, we aimed to assess the association between BPV and clinical outcomes in the hemodialysis population. <b><i>Methods:</i></b> Pubmed/Medline, EMBASE, Ovid, the Cochrane Library, and the Web of Science databases were searched for relevant articles published until April 1, 2020. Studies on the association between BPV and prognosis in patients receiving hemodialysis were included. <b><i>Results:</i></b> A total of 14 studies (37,976 patients) were included in the analysis. In patients receiving hemodialysis, systolic BPV was associated with higher all-cause (hazard ratio [HR]: 1.13; 95% confidence interval [CI]: 1.07–1.19; <i>p</i> &lt; 0.001) and cardiovascular (HR: 1.16; 95% CI: 1.10–1.22; <i>p</i> &lt; 0.001) mortality. In the stratified analysis of systolic BPV, interdialytic systolic BPV, rather than 44-h ambulatory systolic BPV or intradialytic systolic BPV, was identified to be related to both all-cause (HR: 1.11; 95% CI: 1.05–1.17; <i>p</i> = 0.001) and cardiovascular (HR: 1.14; 95% CI: 1.06–1.22; <i>p</i> &lt; 0.001) mortality. Among the different BPV metrics, the coefficient of variation of systolic blood pressure was a predictor of both all-cause (<i>p</i> = 0.01) and cardiovascular (<i>p</i> = 0.002) mortality. Although diastolic BPV was associated with all-cause mortality (HR: 1.09; 95% CI: 1.01–1.17; <i>p</i> = 0.02) in patients receiving hemodialysis, it failed to predict cardiovascular mortality (HR: 0.86; 95% CI: 0.52–1.42; <i>p</i> = 0.56). <b><i>Conclusions:</i></b> This meta-analysis revealed that, in patients receiving hemodialysis, interdialytic systolic BPV was associated with both increased all-cause and cardiovascular mortality. Furthermore, the coefficient of variation of systolic blood pressure was identified as a potentially promising metric of BPV in predicting all-cause and cardiovascular mortality. The use of 44-h ambulatory systolic BPV, intradialytic systolic BPV, and metrics of diastolic BPV in the prognosis of the hemodialysis population require further investigation (PROSPERO registry number: CRD42019139215).
DOI: 10.6084/m9.figshare.13214564.v1
title: Supplementary Material for: Blood Pressure Variability and Prognosis in Hemodialysis Patients: A Systematic Review and Meta-Analysis

description: <b><i>Background:</i></b> The prognostic value of blood pressure variability (BPV) in patients receiving hemodialysis is inconclusive. In this study, we aimed to assess the association between BPV and clinical outcomes in the hemodialysis population. <b><i>Methods:</i></b> Pubmed/Medline, EMBASE, Ovid, the Cochrane Library, and the Web of Science databases were searched for relevant articles published until April 1, 2020. Studies on the association between BPV and prognosis in patients receiving hemodialysis were included. <b><i>Results:</i></b> A total of 14 studies (37,976 patients) were included in the analysis. In patients receiving hemodialysis, systolic BPV was associated with higher all-cause (hazard ratio [HR]: 1.13; 95% confidence interval [CI]: 1.07–1.19; <i>p</i> &lt; 0.001) and cardiovascular (HR: 1.16; 95% CI: 1.10–1.22; <i>p</i> &lt; 0.001) mortality. In the stratified analysis of systolic BPV, interdialytic systolic BPV, rather than 44-h ambulatory systolic BPV or intradialytic systolic BPV, was identified to be related to both all-cause (HR: 1.11; 95% CI: 1.05–1.17; <i>p</i> = 0.001) and cardiovascular (HR: 1.14; 95% CI: 1.06–1.22; <i>p</i> &lt; 0.001) mortality. Among the different BPV metrics, the coefficient of variation of systolic blood pressure was a predictor of both all-cause (<i>p</i> = 0.01) and cardiovascular (<i>p</i> = 0.002) mortality. Although diastolic BPV was associated with all-cause mortality (HR: 1.09; 95% CI: 1.01–1.17; <i>p</i> = 0.02) in patients receiving hemodialysis, it failed to predict cardiovascular mortality (HR: 0.86; 95% CI: 0.52–1.42; <i>p</i> = 0.56). <b><i>Conclusions:</i></b> This meta-analysis revealed that, in patients receiving hemodialysis, interdialytic systolic BPV was associated with both increased all-cause and cardiovascular mortality. Furthermore, the coefficient of variation of systolic blood pressure was identified as a potentially promising metric of BPV in predicting all-cause and cardiovascular mortality. The use of 44-h ambulatory systolic BPV, intradialytic systolic BPV, and metrics of diastolic BPV in the prognosis of the hemodialysis population require further investigation (PROSPERO registry number: CRD42019139215).
DOI: 10.18112/openneuro.ds003363.v1.0.0
title: GSP1000_Connectome
DOI: 10.18112/openneuro.ds003367.v1.0.0
title: Ascending arousal network connectivity during recovery from traumatic coma
DOI: 10.5517/ccdc.csd.cc21w256
title: CCDC 1902847: Experimental Crystal Structure Determination

description: Related Article: Sayaka Oka, Yuma Shigehiro, Yasutaka Kataoka, Yasuyuki Ura|2020|Chem.Commun.|56|12977|doi:10.1039/D0CC05572G
DOI: 10.5517/ccdc.csd.cc25r166
title: CCDC 2018137: Experimental Crystal Structure Determination

description: Related Article: Yu Chen, Yangjian Quan, Zuowei Xie|2020|Chem.Commun.|56|12997|doi:10.1039/D0CC05207H
DOI: 10.5517/ccdc.csd.cc25r177
title: CCDC 2018138: Experimental Crystal Structure Determination

description: Related Article: Yu Chen, Yangjian Quan, Zuowei Xie|2020|Chem.Commun.|56|12997|doi:10.1039/D0CC05207H
DOI: 10.5517/ccdc.csd.cc25r188
title: CCDC 2018139: Experimental Crystal Structure Determination

description: Related Article: Yu Chen, Yangjian Quan, Zuowei Xie|2020|Chem.Commun.|56|12997|doi:10.1039/D0CC05207H
DOI: 10.5517/ccdc.csd.cc25r199
title: CCDC 2018140: Experimental Crystal Structure Determination

description: Related Article: Yu Chen, Yangjian Quan, Zuowei Xie|2020|Chem.Commun.|56|12997|doi:10.1039/D0CC05207H
DOI: 10.5517/ccdc.csd.cc25r1bb
title: CCDC 2018141: Experimental Crystal Structure Determination

description: Related Article: Yu Chen, Yangjian Quan, Zuowei Xie|2020|Chem.Commun.|56|12997|doi:10.1039/D0CC05207H
DOI: 10.5517/ccdc.csd.cc25slvf
title: CCDC 2019645: Experimental Crystal Structure Determination

description: Related Article: Léo Bettoni, Sylvain Gaillard, Jean-Luc Renaud|2020|Chem.Commun.|56|12909|doi:10.1039/D0CC05840H
DOI: 10.5517/ccdc.csd.cc25ttkd
title: CCDC 2020814: Experimental Crystal Structure Determination

description: Related Article: Sheng-Yi Yang, Ya-Kun Wang, Chen-Chen Peng, Zheng-Guang Wu, Shuai Yuan, You-Jun Yu, Hao Li, Tong-Tong Wang, Hong-Cheng Li, You-Xuan Zheng, Zuo-Quan Jiang, Liang-Sheng Liao|2020|J.Am.Chem.Soc.|142|17756|doi:10.1021/jacs.0c08980
DOI: 10.5517/ccdc.csd.cc1mhyln
title: CCDC 1504882: Experimental Crystal Structure Determination

description: Related Article: Hea Jung Park, Eun Ah Chae, Hye Won Seo, Jae-Ho Jang, Won Jae Chung, Jun Yeob Lee, Do-Hoon Hwang, Ung Chan Yoon|2020|J.Mater.Chem.C|8|13843|doi:10.1039/D0TC03773G
DOI: 10.5517/ccdc.csd.cc25yw45
title: CCDC 2024707: Experimental Crystal Structure Determination

description: Related Article: Carolyn E. Ramirez, Su Chen, Natalia E. Powers-Riggs, Itai Schlesinger, Ryan M. Young, Michael R. Wasielewski|2020|J.Am.Chem.Soc.|142|18243|doi:10.1021/jacs.0c09185
DOI: 10.5517/ccdc.csd.cc25yw89
title: CCDC 2024711: Experimental Crystal Structure Determination

description: Related Article: Carolyn E. Ramirez, Su Chen, Natalia E. Powers-Riggs, Itai Schlesinger, Ryan M. Young, Michael R. Wasielewski|2020|J.Am.Chem.Soc.|142|18243|doi:10.1021/jacs.0c09185
DOI: 10.5517/ccdc.csd.cc266rhp
title: CCDC 2032282: Experimental Crystal Structure Determination

description: Related Article: Mari Kimura, Masaki Yoshida, Sho Fujii, Atsushi Miura, Kosei Ueno, Yasuhiro Shigeta, Atsushi Kobayashi, Masako Kato|2020|Chem.Commun.|56|12989|doi:10.1039/D0CC04164E
DOI: 10.5517/ccdc.csd.cc266vfq
title: CCDC 2032373: Experimental Crystal Structure Determination

description: Related Article: Hea Jung Park, Eun Ah Chae, Hye Won Seo, Jae-Ho Jang, Won Jae Chung, Jun Yeob Lee, Do-Hoon Hwang, Ung Chan Yoon|2020|J.Mater.Chem.C|8|13843|doi:10.1039/D0TC03773G
DOI: 10.5517/ccdc.csd.cc26bvxb
title: CCDC 2036232: Experimental Crystal Structure Determination

description: Related Article: Yolanda L. Li, Chih-Te Zee, Janice B. Lin, Victoria M. Basile, Mit Muni, Maria D. Flores, Julen Munárriz, Richard B. Kaner, Anastassia N. Alexandrova, K. N. Houk, Sarah H. Tolbert, Yves Rubin|2020|J.Am.Chem.Soc.|142|18093|doi:10.1021/jacs.0c07657
DOI: 10.5517/ccdc.csd.cc26bwhy
title: CCDC 2036250: Experimental Crystal Structure Determination

description: Related Article: Michael Schneider, Matthieu J. R. Richter, Erick M. Carreira|2020|J.Am.Chem.Soc.|142|17802|doi:10.1021/jacs.0c09520
DOI: 10.21227/v3fv-ar72
title: wind -Part 1

description: This dataset is in support of Research Paper " Grid-Connected Wind " submitted to "IEEE Transactions on Energy Conversion".Abstract of the above submitted paper
DOI: 10.34725/dvn/or5wbq/dcuxy2
title: Birds_IKI-TonF_HN_ams_05oct2020.xlsx

description: Clean data
DOI: 10.34725/dvn/or5wbq
title: Farm inventory surveys in Honduras: Birds data

description: Birds surveys done in Honduras
DOI: 10.34725/dvn/25ydhz/swhwjb
title: 3.Honduras_tree_form_stemsampling.xlsx

description: Stem sampling table
DOI: 10.34725/dvn/25ydhz/dalltg
title: 1.Honduras_tree_form_idvariables.xlsx

description: Main variables
DOI: 10.34725/dvn/25ydhz/yknwxn
title: 2.Honduras_tree_form_treeinfo.xlsx

description: Tree information table
DOI: 10.34725/dvn/25ydhz/kilm2r
title: 5.Honduras_tree_form_figinfo.xlsx

description: Fig information table
DOI: 10.34725/dvn/25ydhz/os1fzd
title: 4.Honduras_tree_form_climberinfo.xlsx

description: Climber information table
DOI: 10.34725/dvn/25ydhz/tryepn
title: 0.IKI_tree_form.xls

description: Questionnaire: ODK form
DOI: 10.34725/dvn/25ydhz/paowjz
title: 2.Honduras_tree_form_treeinfo_SPECIES_v3.xlsx

description: Cleaned tree species data
DOI: 10.34725/dvn/25ydhz
title: Farm inventory surveys in Honduras: Tree data

description: Tree surveys done in Honduras
DOI: 10.5281/zenodo.4247161
title: Data of "Consistent Framework for Coupling Basal Friction with Subglacial Hydrology on Hard-bed Glaciers"

description: The data set contains all data presented in ''Consistent Framework for Coupling Basal Friction with Subglacial Hydrology on Hard-bed Glaciers" that is currently under review. Files Description: ==================================<br> SlidingVelocities2000_2019.dat :<br> ================================== Contains daily values of recorded sliding velocities at the wheel. Column 1 = Day number in Gregorian calendar<br> Column 2 = Daily Values (cm/day) ================================<br> BasalShearStress2000_2019.dat :<br> ================================ Contains daily values of inferred basal shear stress at the wheel. Column 1 = Day number in Gregorian calendar<br> Column 2 = Daily Values (MPa) ================================<br> WaterDischarge2000_2019.dat :<br> ================================ Contains daily values of recorded water discharge at the glacier outlet Column 1 = Day number in Gregorian calendar<br> Column 2 = Daily Values (m3/s)
DOI: 10.34725/dvn/5lzvxr/kyob0b
title: 2.Honduras_plot_form_subplots.xlsx

description: Sub plots data
DOI: 10.34725/dvn/5lzvxr/43rz3g
title: 3.Honduras_plot_form_cwd.xlsx

description: Coarse woody debris information table
DOI: 10.34725/dvn/5lzvxr/avxkwd
title: 1.Honduras_plot_form_main.xlsx

description: Main variables data
DOI: 10.34725/dvn/5lzvxr/yawdux
title: 0.IKI_plot_form.xls

description: Questionnaire: ODK form
DOI: 10.34725/dvn/5lzvxr/lhmjis
title: 4.Plots_land uses_strata_24082020.tab

description: Clean land uses data
DOI: 10.34725/dvn/5lzvxr
title: Farm inventory surveys in Honduras: Plots data

description: Plots data from Honduras