cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14747714
title: Protests Armenia 2018: Video Database – Velvet Revolution 2018

description: The collection "Protests Armenia 2018: Video Database" is part of a larger and ongoing collection of videos on protest events in the post-Soviet region. It contains a database describing 219 videos (mp4) of protests in Armenia in April 2018 (mainly Yerevan area) also known as the Velvet Revolution of 2018. We compiled the material in February to April 2019. All data is processed in an MS Excel database with metadata.
For this kind of collections on protest events we take into account all videos that 1) are event related AND show actions of this event, 2) are fully accessible, 3) we can find with our search words during a particular period. We strictly aim at a systematic and unbiased selection and organized precessing of protest-related videos. We identify particular event-related search words or phrases after intense research on the event. According to the snowball principle, we then start the search of videos and try to describe as much relevant content as possible. However, we cannot guarantee the completeness of protest videos on the particular event. We search the videos and include them into the collection until a particular degree of saturation has been reached.
The videos have been posted mainly by the participants of the events. Therefore, the material is only an extract and biased by the perspective of the single creator.
Due to data privacy regulations and copyright restrictions, we are only allowed to give access to the database of the collected video files including the hyperlinks with its metadata and not to the videos themselves. YouTube's user guidelines do not allow us to store copies of the video collection described above.
description: Published on Discuss Data, https://discuss-data.net/dataset/1d69b4ef-b2f3-457c-8a03-b9887513872b/
description: Method(s) of data collection: Keyword Search, Snow Ball SearchMethod(s) of data analysis: Raw Data, Raw Data For Analysis
DOI: 10.17877/resolv-2024-m49qd1wz
title: Electronic supplement to Control of Interlocking Mode in Pd4L8 Cage Catenanes

description: The dataset contains NMR spectra (NMR), mass spectra and ion mobility data (MS), ORCA output files (DFT). The data is structured according to analytical methods. The files can be opened with standard programs (e.g. NMR -&gt; TopSpin, MestReNova; MS -&gt; Bruker Compass, MestReNova, OpenMS).
DOI: 10.5281/zenodo.14747730
title: Protests Armenia 2015: Video Database – Hike in Electricity Rates

description: The collection "Protests Armenia 2015: Video Database" is part of a larger and ongoing collection of videos on protest events in the post-Soviet region. It contains a database describing 104 videos (mp4) of protests in Armenia in July 2015 (mainly Yerevan area) triggered by a hike in electricity rates. We compiled the material in March to May 2020. All data is processed in an MS Excel database with metadata.
For this kind of collections on protest events we take into account all videos that 1) are event related AND show actions of this event, 2) are fully accessible, 3) we can find with our search words during a particular period. We strictly aim at a systematic and unbiased selection and organized precessing of protest-related videos. We identify particular event-related search words or phrases after intense research on the event. According to the snowball principle, we then start the search of videos and try to describe as much relevant content as possible. However, we cannot guarantee the completeness of protest videos on the particular event. We search the videos and include them into the collection until a particular degree of saturation has been reached.
The videos have been posted mainly by the participants of the events. Therefore, the material is only an extract and biased by the perspective of the single creator.
Due to data privacy regulations and copyright restrictions, we are only allowed to give access to the database of the collected video files including the hyperlinks with its metadata and not to the videos themselves. YouTube's user guidelines do not allow us to store copies of the video collection described above.
description: Published on Discuss Data, https://discuss-data.net/dataset/80c6f1c8-bf16-46bc-ac3e-c0fde0019266/
description: Method(s) of data collection: Keyword Search, Snow Ball SearchMethod(s) of data analysis: Raw Data, Raw Data For Analysis
DOI: 10.5281/zenodo.14747731
title: Protests Armenia 2015: Video Database – Hike in Electricity Rates

description: The collection "Protests Armenia 2015: Video Database" is part of a larger and ongoing collection of videos on protest events in the post-Soviet region. It contains a database describing 104 videos (mp4) of protests in Armenia in July 2015 (mainly Yerevan area) triggered by a hike in electricity rates. We compiled the material in March to May 2020. All data is processed in an MS Excel database with metadata.
For this kind of collections on protest events we take into account all videos that 1) are event related AND show actions of this event, 2) are fully accessible, 3) we can find with our search words during a particular period. We strictly aim at a systematic and unbiased selection and organized precessing of protest-related videos. We identify particular event-related search words or phrases after intense research on the event. According to the snowball principle, we then start the search of videos and try to describe as much relevant content as possible. However, we cannot guarantee the completeness of protest videos on the particular event. We search the videos and include them into the collection until a particular degree of saturation has been reached.
The videos have been posted mainly by the participants of the events. Therefore, the material is only an extract and biased by the perspective of the single creator.
Due to data privacy regulations and copyright restrictions, we are only allowed to give access to the database of the collected video files including the hyperlinks with its metadata and not to the videos themselves. YouTube's user guidelines do not allow us to store copies of the video collection described above.
description: Published on Discuss Data, https://discuss-data.net/dataset/80c6f1c8-bf16-46bc-ac3e-c0fde0019266/
description: Method(s) of data collection: Keyword Search, Snow Ball SearchMethod(s) of data analysis: Raw Data, Raw Data For Analysis
DOI: 10.5281/zenodo.14745102
title: Replcation Data for Dynamic Transfer of Chiral Edge States in Topological Type-II Hyperbolic Lattices

description: The raw data for Figures 2-4 of the main text.
DOI: 10.15468/dl.j3vqug
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bathyraja bergi Dolganov, 1983"
 ]
}

 The dataset includes 32 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004760-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xzzrra
title: Occurrence Download

description: A dataset containing 574 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Fitzroya cupressoides (Molina) I.M.Johnst.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 574 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004761-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.58132/nia5hy
title: Lipid envelopes of influenza A and SARS-CoV-2 virus – physicochemical description of 2D and 3D models

description: The study shows a detailed physicochemical description of the model viral lipid envelopes of the two selected viruses: the human influenza virus (AH1N1) and the SARS-CoV-2 virus of the compositions reflecting the content of phospholipids found in the two types of envelopes. The models were prepared using the Langmuir technique and by the formation of liposomes. The morphology of the model layers was followed by Brewster angle microscopy, fluorescence microscopy and cryo-TEM.The repository contains files (text and tif files) showing the experimental results included in the publication. Please consult the readme.txt file for additional information and a more detailed description of each txt and tif file.
DOI: 10.5281/zenodo.10724794
title: Combining High-Throughput Analysis and Data-Driven Electrochemistry for Advanced Characterization of Si-Ge-Sn Thin Films as Li-Ion Anodes

description: In this study, a thin film of Si-Ge-Sn alloy with a gradient composition distribution was synthesized using combinatorial magnetron sputtering. This thin-film ternary material library was electrochemically characterized as a lithium-ion anode on a millimeter-scale using a three-electrode half-cell scanning droplet cell. The experimental protocol was driven by automated on-the-fly electrochemical analysis and Bayesian optimization with a Gaussian process to find the chemical composition with the highest specific capacity. Comparative analysis revealed a significant improvement in Li-ion battery performance with the best-performing Si-Ge-Sn anodes outperforming those with conventional graphite anodes, with increases in gravimetric energy densities of over 30%. Advanced high-throughput µ-XRF and Raman spectroscopy provided valuable insights into the composition-structure-property relationships of the Si-Ge-Sn system. Additionally, the results of XPS and EIS studies were used to elucidate the discrepancies between theoretical and experimental reversible capacities of Si- and Ge-rich compounds.
DOI: 10.5281/zenodo.10724872
title: Combining High-Throughput Analysis and Data-Driven Electrochemistry for Advanced Characterization of Si-Ge-Sn Thin Films as Li-Ion Anodes

description: In this study, a thin film of Si-Ge-Sn alloy with a gradient composition distribution was synthesized using combinatorial magnetron sputtering. This thin-film ternary material library was electrochemically characterized as a lithium-ion anode on a millimeter-scale using a three-electrode half-cell scanning droplet cell. The experimental protocol was driven by automated on-the-fly electrochemical analysis and Bayesian optimization with a Gaussian process to find the chemical composition with the highest specific capacity. Comparative analysis revealed a significant improvement in Li-ion battery performance with the best-performing Si-Ge-Sn anodes outperforming those with conventional graphite anodes, with increases in gravimetric energy densities of over 30%. Advanced high-throughput µ-XRF and Raman spectroscopy provided valuable insights into the composition-structure-property relationships of the Si-Ge-Sn system. Additionally, the results of XPS and EIS studies were used to elucidate the discrepancies between theoretical and experimental reversible capacities of Si- and Ge-rich compounds.
DOI: 10.5281/zenodo.14745101
title: Replication Data for Dynamic Transfer of Chiral Edge States in Topological Type-II Hyperbolic Lattices

description: The souce data and code for plotting the graphs presented in Figures 2-4 of the main text.
DOI: 10.5281/zenodo.14747644
title: Replication Data for Dynamic Transfer of Chiral Edge States in Topological Type-II Hyperbolic Lattices

description: The souce data and code for plotting the graphs presented in Figures 2-4 of the main text.
DOI: 10.6084/m9.figshare.25914637.v1
title: Assembly Accession

description: <b>Comparative genomics of microalgae</b>
DOI: 10.15468/dl.dnbayg
title: Occurrence Download

description: A dataset containing 484779 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "OccurrenceStatus is Present",
 "TaxonKey is Bombus Latreille, 1802",
 "Year 2014-2024"
 ]
}

 The dataset includes 484779 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004736-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5284/1125983
title: Data from an Archaeological Recording at Doddershall Deserted Medieval Village (DMV), Buckinghamshire, 2020-2022 (HS2 Phase One)

description: This collection comprises image, report, site record, spreadsheet, database and GIS Data from Archaeological Recording Work at Doddershall Deserted Medieval Village, Buckinghamshire. The work was undertaken by between 2020-2022. The archaeological recording was required to mitigate the impact of construction on the archaeological remains within the site. The general aim of the archaeological recording was to locate, identify, characterise, date and record the nature of the archaeological resource of the site ahead of the construction of HS2 Phase 1 Central.
DOI: 10.15468/dl.v75tsb
title: Occurrence Download

description: A dataset containing 462735 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 462735 records from 1672 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004733-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15493/dffe.ccis.17102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual heatwave duration: the length of the longest heatwave (hwd) for 1.5 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.19102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual heatwave duration: the length of the longest heatwave (hwd) for 3.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.30102024
title: Future Extreme heat index: Ensemble 10th,50th and 90th percentiles of Annual heatwave number: the number of heatwaves (hwn) for baseline period of 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.
DOI: 10.15493/dffe.ccis.13102024
title: Future Fire index: Ensemble 10th,50th and 90th percentiles of Annual number of days with fwi greater than 24 (fwi) for 2.0 degree global temperature scenario relative to the period 1961-1991

description: National Climate Change Information System
description: The climate extremes projections over the Free State Province were conducted using the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets as part of the Assessment Report (AR) 6 of the Intergovernmental Panel on Climate Change (IPCC). The focus was on climate extreme events including heat, drought, heatwaves, and flooding. Calculations of climate extreme indices that speak to the identified extreme events were conducted using 10 CMIP6 climate models from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) community. The ISIMIP models were statistically downscaled using the CMIP6 climate model scenario 4, Shared Socioeconomic Pathways 3-70 (SSP3-7.0), also known as the regional rivalry scenario, in the context of the Paris Agreement temperature goals. Under this scenario, a resurgence of nationalism and regional conflicts overshadow global issues. Governments increasingly prioritize national and regional security, leading to reduced investments in education and technological development. Inequality grows, and some regions experience severe environmental damage. These extreme indices were selected from the 27 core indices developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) widely used for analysing extreme events in a changing climate. The calculations were conducted for the baseline period (1961-1990). The level of model uncertainty was represented by ensemble percentiles (10th, 50th and 90th percentiles) from the 10 models in which agreement between the models on the projected spatial pattern of the monthly maximum value of daily maximum temperature (Txx) for the baseline period is illustrated.
description: All datasets were downloaded from ISIMIP as netcdf and processed using Python to extreme climate indices of interest.