cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc20j3c1
title: CCDC 1862522: Experimental Crystal Structure Determination

description: Related Article: Balendra, Azeem Banday, Shailabh Tewari, Bharti Singh, Sevi Murugavel, Arunachalam Ramanan|2019|Inorg.Chim.Acta|495|118940|doi:10.1016/j.ica.2019.05.039
DOI: 10.5517/ccdc.csd.cc210gwf
title: CCDC 1877294: Experimental Crystal Structure Determination

description: Related Article: ulien Jaxel, Hassan Amer, Markus Bacher, Alexander Roller, Matthias Guggenberger, Nele Sophie Zwirchmayr, Christian Hansmann, Falk Liebner|2020|Dyes Pigm.|173|107991|doi:10.1016/j.dyepig.2019.107991
DOI: 10.5517/ccdc.csd.cc20j31q
title: CCDC 1862512: Experimental Crystal Structure Determination

description: Related Article: Balendra, Azeem Banday, Shailabh Tewari, Bharti Singh, Sevi Murugavel, Arunachalam Ramanan|2019|Inorg.Chim.Acta|495|118940|doi:10.1016/j.ica.2019.05.039
DOI: 10.5517/ccdc.csd.cc24w73d
title: CCDC 1992373: Experimental Crystal Structure Determination

description: Related Article: Dukanya, Muthu K. Shanmugam, Shobith Rangappa, Prashant K. Metri, Surender Mohan, Basappa, Kanchugarakoppal S. Rangappa|2020|Bioorg.Med.Chem.Lett.|30|127330|doi:10.1016/j.bmcl.2020.127330
DOI: 10.5517/ccdc.csd.cc24w74f
title: CCDC 1992374: Experimental Crystal Structure Determination

description: Related Article: Dukanya, Muthu K. Shanmugam, Shobith Rangappa, Prashant K. Metri, Surender Mohan, Basappa, Kanchugarakoppal S. Rangappa|2020|Bioorg.Med.Chem.Lett.|30|127330|doi:10.1016/j.bmcl.2020.127330
DOI: 10.5517/ccdc.csd.cc24w75g
title: CCDC 1992375: Experimental Crystal Structure Determination

description: Related Article: Dukanya, Muthu K. Shanmugam, Shobith Rangappa, Prashant K. Metri, Surender Mohan, Basappa, Kanchugarakoppal S. Rangappa|2020|Bioorg.Med.Chem.Lett.|30|127330|doi:10.1016/j.bmcl.2020.127330
DOI: 10.5281/zenodo.6388135
title: Data from: Traces of Genetic but Not Epigenetic Adaptation in the Invasive Goldenrod Solidago canadensis Despite the Absence of Population Structure

description: <strong>General information</strong> This deposition contains the datasets that were used in the statistical analysis of the manuscript entitled <strong>Traces of genetic but not epigenetic adaptation in the invasive goldenrod <em>Solidago canadensis</em> despite the absence of population structure </strong>published in Frontiers in Ecology and Evolution (doi: 10.3389/fevo.2022.856453). <strong>Uploaded files</strong> <strong>README</strong> file to explain the datasets <strong>AFLP/MSAP metadata</strong> called EckertHerdenStiftDurkavanKleunenJoshi_2022_FrontEcolEvol_AFLPMSAP_meta_data.txt <strong>AFLP scoring dataset</strong> called EckertHerdenStiftDurkavanKleunenJoshi_2022_FrontEcolEvol_AFLP_scoring_data.txt <strong>MSAP scoring dataset</strong> called EckertHerdenStiftDurkavanKleunenJoshi_2022_FrontEcolEvol_MSAP_scoring_data.txt <strong>MSAP mix1-scoring dataset</strong> called EckertHerdenStiftDurkavanKleunenJoshi_2022_FrontEcolEvol_MSAP_scoring_data_mix1.txt All files were combined in a <strong>.zip file</strong>
description: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) in the project number 491466077 and with the following grants: KL 1866/10-1 and JO 777/8-1.
DOI: 10.5281/zenodo.6388134
title: Data from: Traces of Genetic but Not Epigenetic Adaptation in the Invasive Goldenrod Solidago canadensis Despite the Absence of Population Structure

description: <strong>General information</strong> This deposition contains the datasets that were used in the statistical analysis of the manuscript entitled <strong>Traces of genetic but not epigenetic adaptation in the invasive goldenrod <em>Solidago canadensis</em> despite the absence of population structure </strong>published in Frontiers in Ecology and Evolution (doi: 10.3389/fevo.2022.856453). <strong>Uploaded files</strong> <strong>README</strong> file to explain the datasets <strong>AFLP/MSAP metadata</strong> called EckertHerdenStiftDurkavanKleunenJoshi_2022_FrontEcolEvol_AFLPMSAP_meta_data.txt <strong>AFLP scoring dataset</strong> called EckertHerdenStiftDurkavanKleunenJoshi_2022_FrontEcolEvol_AFLP_scoring_data.txt <strong>MSAP scoring dataset</strong> called EckertHerdenStiftDurkavanKleunenJoshi_2022_FrontEcolEvol_MSAP_scoring_data.txt <strong>MSAP mix1-scoring dataset</strong> called EckertHerdenStiftDurkavanKleunenJoshi_2022_FrontEcolEvol_MSAP_scoring_data_mix1.txt All files were combined in a <strong>.zip file</strong>
description: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) in the project number 491466077 and with the following grants: KL 1866/10-1 and JO 777/8-1.
DOI: 10.5063/f1cr5rsr
title: AgEvidence US: Agro-environmental responses of conservation agricultural practices published from 1980 to 2020

description: AgEvidence US is a database of the multiple benefits and trade-offs associated with conservation agricultural practices in the United States Midwest. The purpose of these data are to provide organizations, policy makers, scientists, and other interested parties with all the available evidence related to the diversity and magnitude of agro-environmental impacts that occur following the implementation of conservation practices. The conservation practices we focused on include winter cover crops, conservation tillage, strategic nutrient management, and early season pest management in corn and soybean systems. Data were extracted from peer-reviewed literature published between 1980 and 2020 with experimental field sites located in at least one of the following states: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, North Dakota, Nebraska, Ohio, South Dakota, and Wisconsin. Our dataset includes all response variables reported in each paper where there are isolated comparisons of a conservation practice (e.g. soil nitrate content following winter fallow and following winter cover crop). With this approach, we were able to capture the state-of-knowledge for a wide diversity of response variables and identify where we lack knowledge.
DOI: 10.5281/zenodo.6405971
title: Input files required by the bioconvert benchmark

description: These files required to launch the bioconvert benchmarking snakemake framework. For details see https://bioconvert.readthedocs.io .
DOI: 10.5281/zenodo.6405970
title: Input files required by the bioconvert benchmark

description: These files required to launch the bioconvert benchmarking snakemake framework. For details see https://bioconvert.readthedocs.io .
DOI: 10.5281/zenodo.6405536
title: Distance decay 2.0 – a global synthesis of taxonomic and functional decay in ecological communities

description: Datasets used in the analysis of the manuscript by Graco-Roza, C., Aarnio, S., Abrego, N., Acosta, A. T., Alahuhta, J., Altman, J., ... & Soininen, J. (2022). Distance decay 2.0–a global synthesis of taxonomic and functional turnover in ecological communities.<em> Global Ecology and Biogeography.</em> <strong>raw_data.zip - </strong>Includes the raw datasets used in the analysis. <strong>processed_data.xlsx - </strong>Includes the results from the distance decay analysis, specifically: - Dataset : dataset code (same as in raw_data) - Beta_type: The component of beta diversity (i.e., total similarity, replacement, richness differences) - Level : Taxonomic (TAX) or functional (FUN) - Based: Occurrence (occ) or Abundance (abund) - Organism: Code used to describe organisms (see Appendix S1 of the paper) - Realm: Aquatic, Terrestrial, or Freshwaters - Body_size - Dispersal_mode: Seeds, Passive or Active - Latitude: Mean latitude of the dataset (average of all data points) - Latitude_range Distance in kilometres between the two vertically most distant points. - Longitude_range: Distance in kilometres between the two horizontally most distant points. - spa_min: minimum distance between sites (in kilometres) - spa_mean: average distance between sites (in kilometres) - spa_max: maximum distance between sites (in kilometres) - ext: area in kilometres covered by all sites in the dataset - n_sites: Number of sites in each dataset - n_var: Number of environmental variables in each dataset - gamma_spe: Number of species observed in each dataset - gamma_trait: Volume of the hypervolume constructed using the traits in each dataset - n_traits: Number of traits in each dataset - Intercept_spa: Intercept of GLM including community similarity and spatial distances - Slope_Spa: Slope of GLM including community similarity and spatial distances - R2_spa: R² of GLM including community similarity and spatial distances - Intercept_env: Intercept of GLM including community similarity and environmental distances - Slope_env: Slope of GLM including community similarity and environmental distances - R2_env: R² of GLM including community similarity and environmental distances - Mantel_spa: Mantel statistics of community similarity and spatial distances - spa_signif: Significance of Mantel statistics considering community similarity and spatial distances - Mantel_env: Mantel statistics considering community similarity and environmental distances - env_signif: Significance of Mantel statistics considering community similarity and environmental distances <strong>Null_models.zip - </strong>Includes the results from the null models for each dataset.
DOI: 10.5281/zenodo.5102762
title: Original Data for Manuscript "Energy and Momentum Distribution of Surface Plasmon-induced Hot Carriers Isolated via Spatiotemporal Separation"

description: Raw data of the time-dependent energy density calculation and time-resolved photoemission electron microscopy (TR-PEEM) measurements used in the manuscript. A preprint of the manuscript is available on arXiv: 2107.14277 The manuscript was published in <em>ACS Nano</em> 2021, 15, 12, 19559-19569 10.1021/acsnano.1c06586 The data is provided in hdf5 files, which were produced using the snomtools python package (availale on github) and can be read with any hdf5 compatible software. The calculated data was produced as described in Ref.1 with the parameters given in the manuscript. For the experimental data, each zip file contains the raw data (hdf5 Files) as well as the PEEM settings used (sav Files as output from the experiment control software) for the respective measurement. Parts of the manuscript that are generated from the calculated data [calculation_energy_density.zip]: Figure 2 A Figure S2 Parts of the manuscript that are evaluated from the PEEM real space dataset [PEEM_realspace.zip]: Figure 2 B Figure 3 Figure S1 Figure S3 Figure S4 Movie S2 [timeseries_binned_fermi.avi] in the supplementary material Parts of the manuscript that are evaluated from the PEEM momentum space (momentum microscopy) SPP dataset [PEEM_k-space_timesteps_SPP.zip]: Figure 4 (in combination with the pump pulse reference dataset) Figure S5 B Figure S6 B Figure S7 B Parts of the manuscript that are evaluated from the PEEM momentum space (momentum microscopy) pump pulse reference dataset [PEEM_k-space_timesteps_pump.zip]: Figure 4 (in combination with the SPP dataset) Figure S5 A Figure S6 A Figure S7 A Parts of the manuscript that are evaluated from the PEEM momentum space (momentum microscopy) data of the full timetrace, combining SPP dataset [PEEM_k-space_full-timetrace_SPP.zip] and pump pulse reference dataset [PEEM_k-space_full-timetrace_pump.zip]: Figure S8
description: {"references": ["Terekhin, P. N.; Benhayoun, O.; We- ber, S. T.; Ivanov, D. S.; Garcia, M. E.; Rethfeld, B. Influence of surface plasmon polaritons on laser energy absorption and structuring of surfaces. Applied Surface Sci- ence 2020, 512, 144420."]}
DOI: 10.5281/zenodo.5102761
title: Original Data for Manuscript "Energy and Momentum Distribution of Surface Plasmon-induced Hot Carriers Isolated via Spatiotemporal Separation"

description: Raw data of the time-dependent energy density calculation and time-resolved photoemission electron microscopy (TR-PEEM) measurements used in the manuscript. A preprint of the manuscript is available on arXiv: 2107.14277 The manuscript was published in <em>ACS Nano</em> 2021, 15, 12, 19559-19569 10.1021/acsnano.1c06586 The data is provided in hdf5 files, which were produced using the snomtools python package (availale on github) and can be read with any hdf5 compatible software. The calculated data was produced as described in Ref.1 with the parameters given in the manuscript. For the experimental data, each zip file contains the raw data (hdf5 Files) as well as the PEEM settings used (sav Files as output from the experiment control software) for the respective measurement. Parts of the manuscript that are generated from the calculated data [calculation_energy_density.zip]: Figure 2 A Figure S2 Parts of the manuscript that are evaluated from the PEEM real space dataset [PEEM_realspace.zip]: Figure 2 B Figure 3 Figure S1 Figure S3 Figure S4 Movie S2 [timeseries_binned_fermi.avi] in the supplementary material Parts of the manuscript that are evaluated from the PEEM momentum space (momentum microscopy) SPP dataset [PEEM_k-space_timesteps_SPP.zip]: Figure 4 (in combination with the pump pulse reference dataset) Figure S5 B Figure S6 B Figure S7 B Parts of the manuscript that are evaluated from the PEEM momentum space (momentum microscopy) pump pulse reference dataset [PEEM_k-space_timesteps_pump.zip]: Figure 4 (in combination with the SPP dataset) Figure S5 A Figure S6 A Figure S7 A Parts of the manuscript that are evaluated from the PEEM momentum space (momentum microscopy) data of the full timetrace, combining SPP dataset [PEEM_k-space_full-timetrace_SPP.zip] and pump pulse reference dataset [PEEM_k-space_full-timetrace_pump.zip]: Figure S8
description: {"references": ["Terekhin, P. N.; Benhayoun, O.; We- ber, S. T.; Ivanov, D. S.; Garcia, M. E.; Rethfeld, B. Influence of surface plasmon polaritons on laser energy absorption and structuring of surfaces. Applied Surface Sci- ence 2020, 512, 144420."]}
DOI: 10.5063/f1805124
title: AgEvidence Kenya: Agro-environmental responses of conservation agricultural practices published from 2015 to 2020

description: AgEvidence Kenya is a database of the multiple benefits and trade-offs associated with conservation agricultural practices. The purpose of these data are to provide organizations, policy makers, scientists, and other interested parties with all the available evidence related to the diversity and magnitude of agro-environmental impacts that occur following the implementation of conservation practices. The conservation practices we focused on in Kenya include continuous cover, conservation tillage, and nutrient management in bean, cereal, tree, and vegetable systems. Data were extracted from peer-reviewed literature published between 2015 and 2020 with experimental field sites located in Kenya. Our dataset includes all response variables reported in each paper where there are isolated comparisons of a conservation practice (e.g. weed density following intercropping and monocropping). With this approach, we were able to capture the state-of-knowledge for a wide diversity of response variables and identify where we lack knowledge.
DOI: 10.5063/f1hh6hg1
title: AgEvidence Kenya: Agro-environmental responses of conservation agricultural practices published from 2015-2020

description: AgEvidence Kenya is a database of the multiple benefits and trade-offs associated with conservation agricultural practices. The purpose of these data are to provide organizations, policy makers, scientists, and other interested parties with all the available evidence related to the diversity and magnitude of agro-environmental impacts that occur following the implementation of conservation practices. The conservation practices we focused on in Kenya include continuous cover, conservation tillage, and nutrient management in bean, cereal, tree, and vegetable systems. Data were extracted from peer-reviewed literature published between 2015 and 2020 with experimental field sites located in Kenya. Our dataset includes all response variables reported in each paper where there are isolated comparisons of a conservation practice (e.g. weed density following intercropping and monocropping). With this approach, we were able to capture the state-of-knowledge for a wide diversity of response variables and identify where we lack knowledge.
DOI: 10.5517/ccdc.csd.cc297p9k
title: CCDC 2122548: Experimental Crystal Structure Determination

description: Related Article: Dariusz Osypiuk, Beata Cristóvão, Liliana Mazur|2022|J.Mol.Struct.|1261|132924|doi:10.1016/j.molstruc.2022.132924
DOI: 10.5517/ccdc.csd.cc297pbl
title: CCDC 2122549: Experimental Crystal Structure Determination

description: Related Article: Dariusz Osypiuk, Beata Cristóvão, Liliana Mazur|2022|J.Mol.Struct.|1261|132924|doi:10.1016/j.molstruc.2022.132924
DOI: 10.6073/pasta/81f0a8d9afac86aed88fc442dff15e64
title: Tree-ring width measurements and isotope data, Santa Clara River, 2019

description: This data set comprises tree-ring data collected from 114 cottonwood trees (Populus trichocarpa and Populus fremontii) within the floodplain of the Santa Clara River, CA. Tree-ring data includes annual ring width measurements for all rings of each individual as well as semi-annual (earlywood and latewood) measurements of stable carbon and oxygen isotopes for pure alpha cellulose extracted from annual growth rings corresponding to calendar years 2010-2019 for a subset of 48 individuals. This data set is completed. Carbon and oxygen isotope ratios are reported using “delta” notation (i.e. δ13C and δ18O) calculated by the equation: δ13C (or δ18O) = (Rsample/Rstandard - 1) x1000 where R is the molar ratio of 13C/12C (or 18O/16O), with Rsample being that of tree ring cellulose and Rstandard that of Vienna Pee Dee Belemite (VPDB) for δ13C and Vienna Standard Mean Ocean Water (VSMOW) for δ18O.
DOI: 10.5281/zenodo.6406911
title: Distance decay 2.0 – a global synthesis of taxonomic and functional decay in ecological communities

description: Datasets used in the analysis of the manuscript by Graco-Roza, C., Aarnio, S., Abrego, N., Acosta, A. T., Alahuhta, J., Altman, J., ... & Soininen, J. (2022). Distance decay 2.0–a global synthesis of taxonomic and functional turnover in ecological communities.<em> Global Ecology and Biogeography.</em> <strong>raw_data.zip - </strong>Includes the raw datasets used in the analysis. <strong>processed_data.xlsx - </strong>Includes the results from the distance decay analysis, specifically: - Dataset : dataset code (same as in raw_data) - Beta_type: The component of beta diversity (i.e., total similarity, replacement, richness differences) - Level : Taxonomic (TAX) or functional (FUN) - Based: Occurrence (occ) or Abundance (abund) - Organism: Code used to describe organisms (see Appendix S1 of the paper) - Realm: Aquatic, Terrestrial, or Freshwaters - Body_size - Dispersal_mode: Seeds, Passive or Active - Latitude: Mean latitude of the dataset (average of all data points) - Latitude_range Distance in kilometres between the two vertically most distant points. - Longitude_range: Distance in kilometres between the two horizontally most distant points. - spa_min: minimum distance between sites (in kilometres) - spa_mean: average distance between sites (in kilometres) - spa_max: maximum distance between sites (in kilometres) - ext: area in kilometres covered by all sites in the dataset - n_sites: Number of sites in each dataset - n_var: Number of environmental variables in each dataset - gamma_spe: Number of species observed in each dataset - gamma_trait: Volume of the hypervolume constructed using the traits in each dataset - n_traits: Number of traits in each dataset - Intercept_spa: Intercept of GLM including community similarity and spatial distances - Slope_Spa: Slope of GLM including community similarity and spatial distances - R2_spa: R² of GLM including community similarity and spatial distances - Intercept_env: Intercept of GLM including community similarity and environmental distances - Slope_env: Slope of GLM including community similarity and environmental distances - R2_env: R² of GLM including community similarity and environmental distances - Mantel_spa: Mantel statistics of community similarity and spatial distances - spa_signif: Significance of Mantel statistics considering community similarity and spatial distances - Mantel_env: Mantel statistics considering community similarity and environmental distances - env_signif: Significance of Mantel statistics considering community similarity and environmental distances <strong>Null_models.zip - </strong>Includes the results from the null models for each dataset.
DOI: 10.5281/zenodo.6405535
title: Distance decay 2.0 – a global synthesis of taxonomic and functional decay in ecological communities

description: Datasets used in the analysis of the manuscript by Graco-Roza, C., Aarnio, S., Abrego, N., Acosta, A. T., Alahuhta, J., Altman, J., ... & Soininen, J. (2022). Distance decay 2.0–a global synthesis of taxonomic and functional turnover in ecological communities.<em> Global Ecology and Biogeography.</em> <strong>raw_data.zip - </strong>Includes the raw datasets used in the analysis. <strong>processed_data.xlsx - </strong>Includes the results from the distance decay analysis, specifically: - Dataset : dataset code (same as in raw_data) - Beta_type: The component of beta diversity (i.e., total similarity, replacement, richness differences) - Level : Taxonomic (TAX) or functional (FUN) - Based: Occurrence (occ) or Abundance (abund) - Organism: Code used to describe organisms (see Appendix S1 of the paper) - Realm: Aquatic, Terrestrial, or Freshwaters - Body_size - Dispersal_mode: Seeds, Passive or Active - Latitude: Mean latitude of the dataset (average of all data points) - Latitude_range Distance in kilometres between the two vertically most distant points. - Longitude_range: Distance in kilometres between the two horizontally most distant points. - spa_min: minimum distance between sites (in kilometres) - spa_mean: average distance between sites (in kilometres) - spa_max: maximum distance between sites (in kilometres) - ext: area in kilometres covered by all sites in the dataset - n_sites: Number of sites in each dataset - n_var: Number of environmental variables in each dataset - gamma_spe: Number of species observed in each dataset - gamma_trait: Volume of the hypervolume constructed using the traits in each dataset - n_traits: Number of traits in each dataset - Intercept_spa: Intercept of GLM including community similarity and spatial distances - Slope_Spa: Slope of GLM including community similarity and spatial distances - R2_spa: R² of GLM including community similarity and spatial distances - Intercept_env: Intercept of GLM including community similarity and environmental distances - Slope_env: Slope of GLM including community similarity and environmental distances - R2_env: R² of GLM including community similarity and environmental distances - Mantel_spa: Mantel statistics of community similarity and spatial distances - spa_signif: Significance of Mantel statistics considering community similarity and spatial distances - Mantel_env: Mantel statistics considering community similarity and environmental distances - env_signif: Significance of Mantel statistics considering community similarity and environmental distances <strong>Null_models.zip - </strong>Includes the results from the null models for each dataset.
DOI: 10.34943/1568e44b-47b0-482d-8b5b-856759a20145
title: Port Alberni Meteorological Station Deployed 2015-03-19

description: The Davis Vantage Pro2 Plus 6162W AM140708075 was deployed on 2015-03-19 at Port Alberni. Port Alberni is a city located on Vancouver Island. This device is a Meteorological Station. Meteorological stations are instruments that make routine meteorological measurements on the atmosphere and are comprised of a suite of sensors. Typical examples of measurements include temperature, barometric pressure, humidity, rainfall, solar radiation, wind speed and direction. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.