cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2dz2zg
title: CCDC 2233456: Experimental Crystal Structure Determination

description: Related Article: A. Pyrih, A. Łapiński, S. Zięba, A. Mizera, R. Lesyk, M. Jaskolski, A.K. Gzella|2023|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|79|220|doi:10.1107/S2052520623003852
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.cc2dz30j
title: CCDC 2233457: Experimental Crystal Structure Determination

description: Related Article: A. Pyrih, A. Łapiński, S. Zięba, A. Mizera, R. Lesyk, M. Jaskolski, A.K. Gzella|2023|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|79|220|doi:10.1107/S2052520623003852
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.cc2dz31k
title: CCDC 2233458: Experimental Crystal Structure Determination

description: Related Article: A. Pyrih, A. Łapiński, S. Zięba, A. Mizera, R. Lesyk, M. Jaskolski, A.K. Gzella|2023|Acta Crystallogr.,Sect.B:Struct.Sci.,Cryst.Eng. and Mat.|79|220|doi:10.1107/S2052520623003852
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.cc2fxc4w
title: CCDC 2261578: Experimental Crystal Structure Determination

description: Related Article: T. Honda, M. Ito, K. Yamaguchi, N.C. Kasuga, H. Sato|2023|Acta Crystallogr.,Sect.E:Cryst.Commun.|79|549|doi:10.1107/S2056989023004103
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: 10.6084/m9.figshare.23301218.v1
title: Widespread adaptive introgression of the Major Histocompatibility Complex genes in vertebrates - 3rd chapter of PhD dissertation.

description: The dataset includes three parts which constitute supplementary materials for the 3rd chapter of my dissertation, entitled "Widespread adaptive introgression of the Major Histocompatibility Complex genes in vertebrates". It includes: sequences of all detected MHC alleles supplementary figures in the original resolution supplementary tables
DOI: 10.6084/m9.figshare.23301218
title: Widespread adaptive introgression of the Major Histocompatibility Complex genes in vertebrates - 3rd chapter of PhD dissertation.

description: The dataset includes three parts which constitute supplementary materials for the 3rd chapter of my dissertation, entitled "Widespread adaptive introgression of the Major Histocompatibility Complex genes in vertebrates". It includes: sequences of all detected MHC alleles supplementary figures in the original resolution supplementary tables
DOI: 10.5281/zenodo.4670462
title: Repeat active layer depths at sites near Fairbanks, Alaska

description: This set of files provides: 1) Seasonal thaw and active layer measurements from four transects near Fairbanks, Alaska, and 2) information the area of Central Alaska mapped as yedoma permafrost terrain and a calculation of the carbon content of these yedoma areas. File names and descriptions: "Active layer measurements 2014 to 2020.xls" This Excel file provides repeat active layer depth measurements for four transects from 2014 to 2020 "Yedoma areas ecotype information.xls" A set of calculations using the areas mapped as yedoma across Central Alaska and their total carbon content in permafrost soils. "Creamers Field Transect thaw depth measurements 2014.xls" This Excel file provides repeat seasonal thaw depth measurements for the Creamer's Field transect in 2014 "Farmers Loop Transect 1 thaw depth measurements 2014.xls" This Excel file provides repeat seasonal thaw depth measurements for the Farmer's Loop transect #1 in 2014 "Farmers Loop Transect 2 thaw depth measurements 2014.xls" This Excel file provides repeat seasonal thaw depth measurements for the Farmer's Loop transect #2 in 2014 "Permafrost Tunnel Transect thaw depth measurements 2014.xls" This Excel file provides repeat seasonal thaw depth measurements for the Permafrost Tunnel transect in 2014
DOI: 10.5281/zenodo.4670463
title: Repeat active layer depths at sites near Fairbanks, Alaska

description: This set of files provides: 1) Seasonal thaw and active layer measurements from four transects near Fairbanks, Alaska, and 2) information the area of Central Alaska mapped as yedoma permafrost terrain and a calculation of the carbon content of these yedoma areas. File names and descriptions: "Active layer measurements 2014 to 2020.xls" This Excel file provides repeat active layer depth measurements for four transects from 2014 to 2020 "Yedoma areas ecotype information.xls" A set of calculations using the areas mapped as yedoma across Central Alaska and their total carbon content in permafrost soils. "Creamers Field Transect thaw depth measurements 2014.xls" This Excel file provides repeat seasonal thaw depth measurements for the Creamer's Field transect in 2014 "Farmers Loop Transect 1 thaw depth measurements 2014.xls" This Excel file provides repeat seasonal thaw depth measurements for the Farmer's Loop transect #1 in 2014 "Farmers Loop Transect 2 thaw depth measurements 2014.xls" This Excel file provides repeat seasonal thaw depth measurements for the Farmer's Loop transect #2 in 2014 "Permafrost Tunnel Transect thaw depth measurements 2014.xls" This Excel file provides repeat seasonal thaw depth measurements for the Permafrost Tunnel transect in 2014
DOI: 10.5281/zenodo.4119128
title: Data from: "Inventory of Earth's Ice Loss and Associated Energy Uptake from 1979 to 2017"

description: Earth’s cryosphere is a buffer to the warming of the planet and its loss must be accounted for in planetary energy budgets. Yet, even as melting ice is an evident manifestation of climate change, inventories of its energy uptake are largely lacking, based on inconsistent methods, or limited to the fraction that contributes to sea level rise. By combining recent syntheses, we undertake a systematic estimate of ice loss to show that Earth lost 40700 ± 5800 Gt of ice with a corresponding energy uptake of 13.8 ± 2.0 ZJ, from 1979 to 2017, larger than previous estimates and equivalent to the energy uptake by the deep ocean, the land and the atmosphere. The total loss is due to approximately equal contributions from Arctic sea-ice, the Antarctic and Greenland ice sheets, and glaciers. Only half of it contributed to sea level rise. From the 1980s to the 2010s, the rate of ice loss has almost tripled. In this HDF5 dataset, we provide cumulative annual estimates of energy uptake for three components of the cryosphere in Zetajoules (10<sup>21</sup> Joules): 1) Antarctica<br> 2) Greenland<br> 2) Glaciers<br> 3) Sea Ice For 1–3, we separate energy uptake contributions for the grounded and floating components. We also provide a Matlab file with code to read the fields in the dataset. Python code to read the data is available at: https://github.com/sioglaciology/energy_imbalance_cryosphere
DOI: 10.5281/zenodo.4119129
title: Data from: "Inventory of Earth's Ice Loss and Associated Energy Uptake from 1979 to 2017"

description: Earth’s cryosphere is a buffer to the warming of the planet and its loss must be accounted for in planetary energy budgets. Yet, even as melting ice is an evident manifestation of climate change, inventories of its energy uptake are largely lacking, based on inconsistent methods, or limited to the fraction that contributes to sea level rise. By combining recent syntheses, we undertake a systematic estimate of ice loss to show that Earth lost 40700 ± 5800 Gt of ice with a corresponding energy uptake of 13.8 ± 2.0 ZJ, from 1979 to 2017, larger than previous estimates and equivalent to the energy uptake by the deep ocean, the land and the atmosphere. The total loss is due to approximately equal contributions from Arctic sea-ice, the Antarctic and Greenland ice sheets, and glaciers. Only half of it contributed to sea level rise. From the 1980s to the 2010s, the rate of ice loss has almost tripled. In this HDF5 dataset, we provide cumulative annual estimates of energy uptake for three components of the cryosphere in Zetajoules (10<sup>21</sup> Joules): 1) Antarctica<br> 2) Greenland<br> 2) Glaciers<br> 3) Sea Ice For 1–3, we separate energy uptake contributions for the grounded and floating components. We also provide a Matlab file with code to read the fields in the dataset. Python code to read the data is available at: https://github.com/sioglaciology/energy_imbalance_cryosphere
DOI: 10.5281/zenodo.3727616
title: Potential Sites for Future Lake Formation in Glaciers of Chandra Basin, Western Himalayas, India

description: The disappearance of mountain glaciers and the formation or expansion of glacial lakes are amongst the most distinguishable and dynamic impacts of climate warming in the Himalayas. The given dataset provides the potential sites for future lake formation over 65 study glaciers in the Chandra basin of the western Himalayas.
DOI: 10.5281/zenodo.3727617
title: Potential Sites for Future Lake Formation in Glaciers of Chandra Basin, Western Himalayas, India

description: The disappearance of mountain glaciers and the formation or expansion of glacial lakes are amongst the most distinguishable and dynamic impacts of climate warming in the Himalayas. The given dataset provides the potential sites for future lake formation over 65 study glaciers in the Chandra basin of the western Himalayas.
DOI: 10.5281/zenodo.3468658
title: Data used in meta-analysis of debris-covered glacier melt

description: The data used in the study Accuracy of Empirical Models of Debris-Covered Glaciers, A Winter-Billington, RD Moore and R Dadic, in prep. for submission to the Journal of Glaciology.
DOI: 10.5281/zenodo.3468657
title: Data used in meta-analysis of debris-covered glacier melt

description: The data used in the study Accuracy of Empirical Models of Debris-Covered Glaciers, A Winter-Billington, RD Moore and R Dadic, in prep. for submission to the Journal of Glaciology.
DOI: 10.26188/23301236
title: An example 3D scan of a temperate eucalypt forest plot

description: This is a raw 3D point cloud created from terrestrial LiDAR scans in a temperate forest in southern Victoria. It is an example dataset for exploring how to extract habitat metrics. Code for processing this in R can be found at https://github.com/spenman/TLS-workflow
DOI: 10.34740/kaggle/dsv/5855683
title: Egypt Gold Prices | Daily Updated
DOI: 10.5281/zenodo.166511
title: Data-LIS

description: Data package which allows to run tests related to the snow cover extent detection algorithm for Sentinel-2 and Landsat-8 data developed by CNES and CESBIO. The input files are Sentinel-2 or Landsat-8 level-2A products from the [Theai Land Data Centre](https://theia.cnes.fr/) or [SPOT-4/5 Take 5 level-2A products](https://spot-take5.org) and the SRTM digital elevation model. Source code for the lis detection is available on [CESBIO gitlab](http://tully.ups-tlse.fr/grizonnet/let-it-snow) - Data package structure<br> - Baseline : Baseline data folder. It contains output files of S2Snow that have been reviewed and validated.<br> - Data-Test : Test data folder needed to run tests. It contains Landsat, Take5 and SRTM data.<br> - Output-Test : Temporary output tests folder. Do not modify these folders.
DOI: 10.5281/zenodo.8009974
title: Supplementary data for the study "Unveiling the rheological control of magmatic systems on volcano deformation: the interplay of poroviscoelastic magma-mush and thermo-viscoelastic crust ", submitted in the Journal of Geophysical Research: Solid Earth

description: Supplementary data for the study "Unveiling the rheological control of magmatic systems on volcano deformation: the interplay of poroviscoelastic magma-mush and thermo-viscoelastic crust ", submitted in the Journal of Geophysical Research: Solid Earth
DOI: 10.5281/zenodo.8009973
title: Supplementary data for the study "Unveiling the rheological control of magmatic systems on volcano deformation: the interplay of poroviscoelastic magma-mush and thermo-viscoelastic crust ", submitted in the Journal of Geophysical Research: Solid Earth

description: Supplementary data for the study "Unveiling the rheological control of magmatic systems on volcano deformation: the interplay of poroviscoelastic magma-mush and thermo-viscoelastic crust ", submitted in the Journal of Geophysical Research: Solid Earth
DOI: 10.5281/zenodo.4733251
title: Snow cover from spectral mixture analysis algorithm SCAG: OLI, MODIS, VIIRS

description: This data is snow cover fraction from the Snow Covered Area and Grain Size (SCAG) model for Landsat OLI, Terra MODIS, and Suomi VIIRS. It was used in the a publication for Frontiers Remote Sensing titled Evaluation of VIIRS and MODIS snow covered fraction in High Mountain Asia using Landsat 8 OLI, doi: 10.3389/frsen.2021.647154.
DOI: 10.5281/zenodo.4733252
title: Snow cover from spectral mixture analysis algorithm SCAG: OLI, MODIS, VIIRS

description: This data is snow cover fraction from the Snow Covered Area and Grain Size (SCAG) model for Landsat OLI, Terra MODIS, and Suomi VIIRS. It was used in the a publication for Frontiers Remote Sensing titled Evaluation of VIIRS and MODIS snow covered fraction in High Mountain Asia using Landsat 8 OLI, doi: 10.3389/frsen.2021.647154.
DOI: 10.48425/xjqqhp26
title: S_ungulates_summary_adventdalen_summer

description: Annual census of the Svalbard reindeer population in Adventdalen to estimate the population abundance (sex and age distribution) from 1979 to 2020. The study area for this reindeer census includes the main valley Adventdalen, including adjacent mountain plateaus and side valleys (see map in protocol).
DOI: 10.5281/zenodo.8009995
title: DIO_DMSO vs DIO_seno heart baseline Cardiomyocytes size

description: DIO_DMSO vs DIO_seno heart baseline Cardiomyocytes size
DOI: 10.5281/zenodo.8009994
title: DIO_DMSO vs DIO_seno heart baseline Cardiomyocytes size

description: DIO_DMSO vs DIO_seno heart baseline Cardiomyocytes size
DOI: 10.5281/zenodo.3367347
title: Dataset for ISMIP6 CMIP5 model selection

description: Dataset associated with the manuscript entitled "CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica" for publication in The Cryosphere. This dataset was used to select CMIP5 models as forcing for the ISMIP6 stand-alone Greenland and Antarctica projections.
DOI: 10.5281/zenodo.3367346
title: Dataset for ISMIP6 CMIP5 model selection

description: Dataset associated with the manuscript entitled "CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica" for publication in The Cryosphere. This dataset was used to select CMIP5 models as forcing for the ISMIP6 stand-alone Greenland and Antarctica projections.
DOI: 10.5281/zenodo.803850
title: Permafrost And Ground Ice Map Of Switzerland

description: This KML file contains a countrywide permafrost distribution map of Switzerland, indicating ground temperatures and ice content. Permafrost occurrence is represented by 3 clearly defined classes: Zone1: permafrost, Zone 2: isolated permafrost possible and Zone 3: potential ice-rich permafrost. A corresponding map legend is included in the KML file. A clear improvement in the prediction of ground temperatures could be achieved by distinguishing ice-poor and ice-rich permafrost in the modelling process. There is a very strong correlation (0.99) of ground temperatures with elevation and potential incoming solar radiation in ice-poor ground represented by zone 1. The distribution of ice-rich permafrost was defined by modelling mass wasting processes and the burial of snow and ice into the ground caused by them. A validation of the map yield the following result: All 49 validation points located in zone 1 indicate permafrost. Approximately 2/3 of 33 validation points located in zone 3 indicate permafrost. 34 validation points are located outside the permafrost zonation of which 1 indicates permafrost and 33 permafrost absence.
DOI: 10.5281/zenodo.1470165
title: Permafrost and Ground Ice Map of Switzerland

description: Save the layer file (.lyr) together with the other files (Shapefiles) in a common folder and load the layer file in a GIS or geoviewer application to see the map. If your GIS-Application does not support .lyr files you can define the visualization of the map by yourself using the field “indicator” in the shapefiles attribute table. This field contain the numbers -3; -2; -1; 0; 1; 5 and 9 which have the following meaning: -3 = permafrost &lt; -3°C -2 = permafrost -2 to -3°C -1 = permafrost &lt; -1 to -2°C 0 = permafrost &lt; 0 to -1°C 1 = Ground temperatures 0 to +1°C (possible patchy permafrost) 5 = potential ice-rich permafrost 9= glacier The PGIM and legends can also be accessed online at www.slf.ch\pgim The shapefile contain a countrywide permafrost distribution map of Switzerland, indicating ground temperatures and ice content. A new representation of ground temperatures is achieved by distinguishing ice-poor and ice-rich permafrost in the modelling process. There is a very strong correlation of ground temperatures with elevation and potential incoming solar radiation in ice-poor and ice-free ground. The distribution of ice-rich permafrost was defined by modelling mass wasting processes and the integration of snow and ice into the ground caused by them. This approach yields a relatively accurate and largely unambiguous map. Permafrost occurrence is represented by two clearly defined classes: Zone 1 representing modelled ground temperatures and zone 2 indicating excess ground ice outside of zone 1. 58% of 92 validation sites could be definitively classified as having permafrost or no permafrost. If only ice-poor or –free ground is considered, this value reaches 90%.
DOI: 10.5281/zenodo.803849
title: Permafrost and Ground Ice Map of Switzerland

description: Save the layer file (.lyr) together with the other files (Shapefiles) in a common folder and load the layer file in a GIS or geoviewer application to see the map. If your GIS-Application does not support .lyr files you can define the visualization of the map by yourself using the field “indicator” in the shapefiles attribute table. This field contain the numbers -3; -2; -1; 0; 1; 5 and 9 which have the following meaning: -3 = permafrost &lt; -3°C -2 = permafrost -2 to -3°C -1 = permafrost &lt; -1 to -2°C 0 = permafrost &lt; 0 to -1°C 1 = Ground temperatures 0 to +1°C (possible patchy permafrost) 5 = potential ice-rich permafrost 9= glacier The PGIM and legends can also be accessed online at www.slf.ch\pgim The shapefile contain a countrywide permafrost distribution map of Switzerland, indicating ground temperatures and ice content. A new representation of ground temperatures is achieved by distinguishing ice-poor and ice-rich permafrost in the modelling process. There is a very strong correlation of ground temperatures with elevation and potential incoming solar radiation in ice-poor and ice-free ground. The distribution of ice-rich permafrost was defined by modelling mass wasting processes and the integration of snow and ice into the ground caused by them. This approach yields a relatively accurate and largely unambiguous map. Permafrost occurrence is represented by two clearly defined classes: Zone 1 representing modelled ground temperatures and zone 2 indicating excess ground ice outside of zone 1. 58% of 92 validation sites could be definitively classified as having permafrost or no permafrost. If only ice-poor or –free ground is considered, this value reaches 90%.
DOI: 10.5281/zenodo.4305956
title: A-AFMA Ultrasound Challenge Dataset

description: This is the dataset for A-AFMA Ultrasound Challenge for automatic amniotic fluid measurement and analysis from ultrasound video. <strong>Each team needs to send a registration email including the team name, team members' names, and affiliations to the organizer via email: noble_pm@eng.ox.ac.uk</strong> The challenge is hosted here. Teams are required to register on the Grand Challenge site before they will be given access to the data. Each team needs to send a registration email including the team name, team members' names, and affiliations to the organizer via email: noble_pm@eng.ox.ac.uk No publication rights are given on this data. The data may only be used for the purpose of the challenge. This is due to constraints imposed on use of the data by the ethics approval.
DOI: 10.5281/zenodo.4305955
title: A-AFMA Ultrasound Challenge Dataset

description: This is the dataset for A-AFMA Ultrasound Challenge for automatic amniotic fluid measurement and analysis from ultrasound video. <strong>Each team needs to send a registration email including the team name, team members' names, and affiliations to the organizer via email: noble_pm@eng.ox.ac.uk</strong> The challenge is hosted here. Teams are required to register on the Grand Challenge site before they will be given access to the data. Each team needs to send a registration email including the team name, team members' names, and affiliations to the organizer via email: noble_pm@eng.ox.ac.uk No publication rights are given on this data. The data may only be used for the purpose of the challenge. This is due to constraints imposed on use of the data by the ethics approval.
DOI: 10.5281/zenodo.6106859
title: La Laguna Catchment, Chile - Surface Elevation Change and Velocity Rasters

description: Datasets from Robson et al 2022. The zip contains two sub-folders: 1) Surface elevation changes 1956 to 2020 with time steps 1956 - 1978, 1978 - 2000, 2000 - 2012, 2012 - 2015, 2015 - 2020. Datasets cover Tapado Glacier, La Laguna Catchment, Chile. Additionally surface elevation changes 2012 - 2020 covering rock glaciers in the La Laguna catchment are included. 2) Surface velocity raster (annual displacements between 2012 and 2020) for glaciers and rock glaciers in the La Laguna catchment. For details on the processing, please refer to the publication: Robson, B. A., MacDonell, S., Ayala, Á., Bolch, T., Nielsen, P. R., and Vivero, S (2022). Glacier and Rock Glacier changes since the 1950s in the La Laguna catchment, Chile, The Cryosphere
description: {"references": ["Robson, B. A., MacDonell, S., Ayala, \u00c1., Bolch, T., Nielsen, P. R., and Vivero, S (2022). Glacier and Rock Glacier changes since the 1950s in the La Laguna catchment, Chile, The Cryosphere"]}