cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/f7zs2vc8
title: Bathymetry on the East Fork White River at Columbus, Indiana, March 29-30 and April 13, 2017

description: These data are bathymetry (river bottom elevation) in XYZ format, generated from the March 29-30, 2017 and April 13, 2017, bathymetric survey of the East Fork White River at Columbus, Indiana. The bathymetry was collected from approximately the confluence of Driftwood and Flatrock rivers, downstream to the confluence of Haw Creek. Hydrographic data were collected using an acoustic Doppler current profiler (ADCP) with integrated Differential Global Positioning System (DGPS). Data were collected as the surveying vessel traversed the river, approximately perpendicular to the velocity vectors at 55 cross sections which were spaced 200 feet apart along the river. Additional cross sections were collected upstream and downstream of the low-head dam in Columbus, Indiana, as well. Data collection software integrated and stored the depth and DGPS data from the ADCP. Real-time kinematic GPS was collected at each cross section recording the water-surface elevation. Data processing required computer software to extract bathymetry data from the raw data files and to compile the information. The final csv file contains columns of Longitude and Latitude in degrees WGS84, and Elevation in feet NAVD88.
DOI: 10.5067/gpm/gmi/gpm/gprof/2a/07
title: GPM GMI (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 13 km V07
DOI: 10.6073/pasta/e711d62032f0b78b9a91070a38f2b43f
title: Zooplankton density for lake samples collected near Toolik Lake Arctic LTER in the summer from 1983 to 1992.
DOI: 10.6084/m9.figshare.14845005
title: Increasing impact of warm droughts on northern ecosystem productivity over recent decades - Data

description: This repository contains the materials (data & code) to reproduce, interpret and verify the main figures presented in Gampe et al. 2021 ("Increasing impact of warm droughts on northern ecosystem productivity over recent decades", Nat. Clim. Change); DOI: 10.1038/s41558-021-01112-8
DOI: 10.6084/m9.figshare.16639480.v4
title: Data and Code for RES-11 Scale Validation

description: STATA dataset for tablesMPlus dataset for EFA/CFAMPlus dataset for measurement invariance testingSTATA Code for Tables 1 & 2MPlus Code for measurement invariance testing
DOI: 10.6084/m9.figshare.5123161
title: Supplementary Material for: Körperbeschwerden nach politischer Inhaftierung und deren Zusammenhang mit Ängstlichkeit und Depressivität

description: <i>Hintergrund:</i> Über 200.000 Menschen waren in der DDR aus politischen Gründen inhaftiert. Mehrere Studien existieren zu den psychischen (Langzeit-)Folgen dieser biografischen Erfahrung. Weniger untersucht wurden bisher die körperlichen Folgen. Ziel dieser Studie ist (1) die Ausprägungen körperlicher Beschwerden von ehemals politisch Inhaftierten in der DDR mit Daten aus der Allgemeinbevölkerung zu vergleichen, (2) die körperlichen Beschwerden mit soziodemografischen und Inhaftierungsmerkmalen in Beziehung zu setzen und (3) den Zusammenhang zwischen körperlichen Beschwerden und Ängstlichkeit sowie Depressivität innerhalb der Gruppe der ehemals Inhaftierten zu untersuchen. <i>Methoden:</i> In dieser Querschnittstudie beantworteten 149 Personen, die aus politischen Gründen in der DDR inhaftiert waren, einen Fragebogen über körperliche Beschwerden (Gießener Beschwerdebogen, Kurzform), Ängstlichkeit und Depressivität (Hospital Anxiety and Depression Scale). Für den Vergleich mit der Allgemeinbevölkerung wurde eine hinsichtlich Alter und Geschlecht vergleichbare Stichprobe aus einer deutschen Repräsentativbefragung verwendet (n = 473). <i>Ergebnisse:</i> Ehemalige politisch Inhaftierte berichten im Vergleich zur Allgemeinbevölkerung auch viele Jahre nach der politischen Inhaftierung deutlich mehr körperliche Beschwerden (p &lt; 0,001). Soziodemografische Merkmale und Merkmale der Inhaftierung stehen nur punktuell mit den angegebenen Körperbeschwerden im Zusammenhang. Zur Vorhersage von Ängstlichkeit in der Gruppe der politisch Inhaftierten leisten insbesondere Herzbeschwerden einen substantiellen Beitrag, zur Vorhersage von Depressivität Erschöpfung. Die Haftdauer ist für Ängstlichkeit und Depressivität kein signifikanter Prädiktor. <i>Schlussfolgerungen:</i> Personen, die aus politischen Gründen in der DDR inhaftiert waren, stellen eine Risikogruppe in der medizinischen Versorgung dar. Sie berichten über deutlich mehr Körperbeschwerden als die Allgemeinbevölkerung und weisen stark erhöhte Werte für Depression und Ängstlichkeit auf.
DOI: 10.5517/ccdc.csd.cc2c70qc
title: CCDC 2181492: Experimental Crystal Structure Determination

description: Related Article: John M. Halford-McGuff, David B. Cordes, Allan J. B. Watson|2023|Chem.Commun.|59|7759|doi:10.1039/D3CC00761H
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: 10.22022/tnt/07-2020.16533
title: Innovations for Sustainability. Pathways to an efficient and post-pandemic future. Report prepared by The World in 2050
DOI: 10.5066/p9b7lbqc
title: Channel geometry for upstream and downstream cross sections at selected bridge sites in Montana, 2020

description: The U.S. Geological Survey, in cooperation with the Montana Department of Transportation (MDT), collected cross-section data on the upstream and downstream sides at selected bridges in Montana during the 2020 calendar year. The purpose of the data collection is to determine if scour and channel instability occur in the vicinity of the bridge structures. Data were processed, analyzed, and compiled for scour monitoring, facilitating better understanding, documentation, and prediction of scour processes.
DOI: 10.5281/zenodo.7379584
title: Lightning and volcanic plume data from the climactic eruption of Hunga Volcano, Tonga, in January 2022

description: This dataset contains lightning and volcanic plume data for the eruption of Hunga Volcano in Tonga from 13–15 January 2022. The dataset consists of two files. The first is a spreadsheet containing four tabs: (1) Ground-based flashes, which include lightning flashes from combined ground-based networks from 13–15 January 2022; (2) Ground-based rates, which include flash rates and pulse rates in one-minute bins from 13–15 January 2022 using the combined networks; (3) Optical GLM flashes & rates, which include GLM flashes and per-minute rates from 15 January 2022; and (4) Volcanic plume dimensions, which include maximum plume heights and umbrella radii through time on 15 January 2022. The second file is a Google Earth KMZ file of umbrella cloud areas outlined from stereoscopic cloud height retrievals from 04:17–07:07 UTC on 15 January 2022. Refer to journal article "Lightning rings and gravity waves: Insights into the giant eruption plume from Tonga’s Hunga Volcano on 15 January 2022" published in Geophysical Research Letters for further details about data processing.
DOI: 10.5517/ccdc.csd.cc2fb7pq
title: CCDC 2244173: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.cc2fb7qr
title: CCDC 2244174: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.18070493.v2
title: Complex-amplitude Fourier single-pixel imaging via coherent structured illumination-DataSet

description: Measured Fourier Spectrum Data for Figs. 2, 3, 4, 5
DOI: 10.5517/ccdc.csd.cc2fb7rs
title: CCDC 2244175: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.cc2fb7st
title: CCDC 2244176: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.cc2fb7tv
title: CCDC 2244177: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.cc2fb7vw
title: CCDC 2244178: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.cc2fb7wx
title: CCDC 2244179: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.cc2fb7xy
title: CCDC 2244180: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.cc2fb7yz
title: CCDC 2244181: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.cc2fb7z0
title: CCDC 2244182: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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.cc2fb802
title: CCDC 2244183: Experimental Crystal Structure Determination

description: Related Article: Xinzhe Shi, Sihan Li, Anke Spannenberg, Fabian Reiß, Torsten Beweries|2023|Inorg.Chem.Front.|10|3584|doi:10.1039/D3QI00449J
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: 10.25345/c55x25p62
title: MassIVE MSV000092221 - Luxembourgish surface water samples 2019-2022
title: mzML files from the analysis of SPE-concentrated surface water samples collected in different rivers in Luxembourg between 2019 and 2022 through the collaborative work between the Environmental Cheminformatics Group (LCSB, University of Luxembourg) and the Luxembourg Administration de la gestion de l eau (AGE). The according sampling locations related to each file can be found in the supplementary xlsx file.
DOI: 10.6084/m9.figshare.23260496.v1
title: Calibration

description: Calibration of the flow rate, fluorescence, and light scattering intensity
DOI: 10.5281/zenodo.8063376
title: DAS Urban Mobility Patterns Database

description: This database is based on the MINIDAS format designed by the Incorporated Research Institutions for Seismology (IRIS) with the objective of storing information captured by distributed acoustic systems. These files correspond to the hdf5 type, which facilitates their reading. In this same dataset you can find the official script to work with this kind of data (for more information see official repository, https://github.com/DAS-RCN/RCN_DASformat). New version of https://doi.org/10.5281/zenodo.7981219
DOI: 10.5281/zenodo.8063377
title: DAS Urban Mobility Patterns Database

description: This database is based on the MINIDAS format designed by the Incorporated Research Institutions for Seismology (IRIS) with the objective of storing information captured by distributed acoustic systems. These files correspond to the hdf5 type, which facilitates their reading. In this same dataset you can find the official script to work with this kind of data (for more information see official repository, https://github.com/DAS-RCN/RCN_DASformat). New version of https://doi.org/10.5281/zenodo.7981219
DOI: 10.5281/zenodo.8063384
title: DAS Urban Mobility Patterns Database

description: This database is based on the MINIDAS format designed by the Incorporated Research Institutions for Seismology (IRIS) with the objective of storing information captured by distributed acoustic systems. These files correspond to the hdf5 type, which facilitates their reading. In this same dataset you can find the official script to work with this kind of data (for more information see official repository, https://github.com/DAS-RCN/RCN_DASformat). New version of https://doi.org/10.5281/zenodo.7981219
DOI: 10.5281/zenodo.8063407
title: DAS Urban Mobility Patterns Database

description: This database is based on the MINIDAS format designed by the Incorporated Research Institutions for Seismology (IRIS) with the objective of storing information captured by distributed acoustic systems. These files correspond to the hdf5 type, which facilitates their reading. In this same dataset you can find the official script to work with this kind of data (for more information see official repository, https://github.com/DAS-RCN/RCN_DASformat). New version of https://doi.org/10.5281/zenodo.7981219
DOI: 10.5281/zenodo.8063452
title: DAS Urban Mobility Patterns Database

description: This database is based on the MINIDAS format designed by the Incorporated Research Institutions for Seismology (IRIS) with the objective of storing information captured by distributed acoustic systems. These files correspond to the hdf5 type, which facilitates their reading. In this same dataset you can find the official script to work with this kind of data (for more information see official repository, https://github.com/DAS-RCN/RCN_DASformat). New version of https://doi.org/10.5281/zenodo.7981219
DOI: 10.5281/zenodo.8063423
title: GNSS and IMU data recorded during a vessel sail

description: Example data point of this data set: <pre><code>"0": { "timestamp": 1674573910407, "acceleration_x_ms2": -0.121791042, "acceleration_y_ms2": -0.025389839, "acceleration_z_ms2": -0.049855232, "gps_lat": 51.1537593172, "gps_lon": 2.8057965827, "sog_kmh": 0.39, "rot_deg_min": "1.3", "heading_deg": 230.313, "imu_lat": null, "imu_lon": null, "roll_rate_deg_min": null, "pitch_rate_deg_min": null, "yaw_rate_deg_min": null, "roll_deg": null, "pitch_deg": null, "yaw_deg": null }</code></pre>
DOI: 10.5281/zenodo.8063422
title: GNSS and IMU data recorded during a vessel sail

description: Example data point of this data set: <pre><code>"0": { "timestamp": 1674573910407, "acceleration_x_ms2": -0.121791042, "acceleration_y_ms2": -0.025389839, "acceleration_z_ms2": -0.049855232, "gps_lat": 51.1537593172, "gps_lon": 2.8057965827, "sog_kmh": 0.39, "rot_deg_min": "1.3", "heading_deg": 230.313, "imu_lat": null, "imu_lon": null, "roll_rate_deg_min": null, "pitch_rate_deg_min": null, "yaw_rate_deg_min": null, "roll_deg": null, "pitch_deg": null, "yaw_deg": null }</code></pre>
DOI: 10.17897/0tfz-tr28
title: GlacioBasis Zackenberg - Glacier ice - AWS-Zack-M

description: Ice temperature profile at station Zack-M Glacier ice:Glacier ice GlacioBasis Zackenberg:Since 2008, the GlacioBasis programme has been monitoring the glacier surface mass balance at the A.P. Olsen Ice Cap and its response to climate forcing. Greenland’s glaciers and Ice Caps are losing mass at a rate more than double of the Ice Sheet when adjusted for size, accounting for 14-20 % of the total sea level rise contribution from Greenland. As the glaciological component of a core WMO GCW CryoNet site and a contributor to the GTN-G through WGMS, the GlacioBasis datasets complement the ongoing monitoring based at Zackenberg, enable process-based understanding of physical processes driven by glacier melt water run-off in the downstream terrestrial and marine ecosystems, and can inform regional and global assessments under AMAP and IPCC. GlacioBasis operates the year-round automatic monitoring of A.P. Olsen Ice Cap near-surface weather at three stations, a network of ablation stakes covering the entire altitude range, and geophysical survey campaigns on the ground (radar snow depth) and airborne (surface elevation from lidar, ice thickness from radar). GlacioBasis data collection is adaptively updated to support research in processes emerging as key sources of nonlinearity in the cryosphere, including melt water retention and albedo feedbacks. As a representative Northeast Greenland Ice Cap, A.P. Olsen observations delivered by GlacioBasis are available to the national and international remote sensing and climate modelling communities for calibration, validation and upscaling purposes.
DOI: 10.17897/hs26-2e10
title: GlacioBasis Zackenberg - Glacier ice - AWS-Zack-S

description: Ice temperature profile at station Zack-S Glacier ice:Glacier ice GlacioBasis Zackenberg:Since 2008, the GlacioBasis programme has been monitoring the glacier surface mass balance at the A.P. Olsen Ice Cap and its response to climate forcing. Greenland’s glaciers and Ice Caps are losing mass at a rate more than double of the Ice Sheet when adjusted for size, accounting for 14-20 % of the total sea level rise contribution from Greenland. As the glaciological component of a core WMO GCW CryoNet site and a contributor to the GTN-G through WGMS, the GlacioBasis datasets complement the ongoing monitoring based at Zackenberg, enable process-based understanding of physical processes driven by glacier melt water run-off in the downstream terrestrial and marine ecosystems, and can inform regional and global assessments under AMAP and IPCC. GlacioBasis operates the year-round automatic monitoring of A.P. Olsen Ice Cap near-surface weather at three stations, a network of ablation stakes covering the entire altitude range, and geophysical survey campaigns on the ground (radar snow depth) and airborne (surface elevation from lidar, ice thickness from radar). GlacioBasis data collection is adaptively updated to support research in processes emerging as key sources of nonlinearity in the cryosphere, including melt water retention and albedo feedbacks. As a representative Northeast Greenland Ice Cap, A.P. Olsen observations delivered by GlacioBasis are available to the national and international remote sensing and climate modelling communities for calibration, validation and upscaling purposes.
DOI: 10.17897/46vk-4629
title: GlacioBasis Zackenberg - Glacier ice - AWS-Zack-T

description: Ice temperature profile at station Zack-T Glacier ice:Glacier ice GlacioBasis Zackenberg:Since 2008, the GlacioBasis programme has been monitoring the glacier surface mass balance at the A.P. Olsen Ice Cap and its response to climate forcing. Greenland’s glaciers and Ice Caps are losing mass at a rate more than double of the Ice Sheet when adjusted for size, accounting for 14-20 % of the total sea level rise contribution from Greenland. As the glaciological component of a core WMO GCW CryoNet site and a contributor to the GTN-G through WGMS, the GlacioBasis datasets complement the ongoing monitoring based at Zackenberg, enable process-based understanding of physical processes driven by glacier melt water run-off in the downstream terrestrial and marine ecosystems, and can inform regional and global assessments under AMAP and IPCC. GlacioBasis operates the year-round automatic monitoring of A.P. Olsen Ice Cap near-surface weather at three stations, a network of ablation stakes covering the entire altitude range, and geophysical survey campaigns on the ground (radar snow depth) and airborne (surface elevation from lidar, ice thickness from radar). GlacioBasis data collection is adaptively updated to support research in processes emerging as key sources of nonlinearity in the cryosphere, including melt water retention and albedo feedbacks. As a representative Northeast Greenland Ice Cap, A.P. Olsen observations delivered by GlacioBasis are available to the national and international remote sensing and climate modelling communities for calibration, validation and upscaling purposes.