cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7925/drs1.duchas_4811604
title: Chathair Mhór

description: A collection of folklore and local history stories from An Chathair Mhór (school) (Knockroe Middle, Co. Cork), collected as part of the Schools' Folklore Scheme, 1937-1938 under the supervision of teacher Donncha Ó Súilleabháin.
description: Sprid a Bhí i gCnoc Óra / Sullivan, Batt O' -- Belle of Beara / Sullivan, Batt O' -- Scéal an Ghorta / Murphy, James -- Socraid na gCaorach / Sullivan, Batt O' -- Lickbarrahen / Harrington, John -- Cuas na Seisrí / Harrington, Patrick -- Gaibhlean Gabha / Sullivan, John O' -- Oileán Aolbach / Súilleabháin, Donnachadh Ó -- Gaibhlean Gabha agus an Glas Gaibhneach / Súilleabháin, Donnachadh Ó -- Na Sprideanna / Murphy, James -- Souperism / Murphy, James -- Inse Airgid Dhomhnaill / Doherty, Emmet O' -- Lickbarrahen Mermaid / Harrington, Patrick -- Donal Cam / Harrington, Diarmuid -- Brackcluin Sprid / Sullivan, Teddy O' -- Fairy Fiddler / Sullivan, John O' -- Scéal - Aimsir an Ghorta / Murphy, John -- Bean an Leasa / Murphy, Michael -- Rábach / Sullivan, John O' -- Bhó Riabhach / Harrington, Dermot -- Sprid / Séaghdha, Mícheál Ó -- Dónall Cam -- Dónall Cam / Suilleabhan, D. O' -- Cuan na Cruinne -- Bás Dhomhnaill sa Spáinn / S., D. O' -- Ag Déanamh Cleamhnais / S., D. O' -- Cleamhnas Eile / S., D. Ó -- Cathair Draíochta -- Chathair Draíochta / Súílleabháin, Donnchadh Ó -- Muirionn ón Bhaoi -- Muirionn i bhFaoide -- Muirionn agus Puxley -- Scéílín Eile mar Gheall ar Owen Buí / S., D. Ó -- Gadaí Dubh / Harrington, Dermot -- Fairy Twins / Harrington, Nicholas -- Killaugh Fairies / Sullivan, Pat O' -- Holy Water Font (Bullán) / Súilleabháin, D. Ó -- Paidir / Sullivan, Nora O' -- Names of Owners of Farms in Cahermore -- Names of the Owners of the Farms in Kilkinnihin -- The Names of Owners of Farms in Knockroe West and Middle -- Names of Owners of Farmers in Clohane and Knockroe East -- Names of Owners of Farmers in Gurranes and Brackcluin -- Counlough and Lehanebeg -- Lickbarrahan and Coomnamona -- Names of the Owners of Farms in Killaugh East and West -- Gurranes - Cuases -- Cahermore - Cuases -- Sliabh / Sullivan, Bat O' -- Story / Murphy, James -- Story / Harrington, Dermot -- Wreck / Harrington, Patrick -- Bean an Leasa / Murphy, Michael -- White hand / Sullivan, John -- Seanráite -- Paidreacha -- Seanráite / Se, Donnchadh O' -- Véarsa ar Chluain nó Allihies / Súilleabháin, Nóra Ó -- Pósadh Cána / Súilleabháin, Nóra Ó -- At the time Father Devine was in in this parish he has a brother at Castletown... / Súilleabháin, Donnchadh Ó -- Father James Devine - The Liberation of the Widow's Cow / S., D. Ó -- Our Footballers from Bere / Súilleabháin, Donnchadh O'
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.15468/a4ibbs
title: Morphological and molecular characterization of Hemicycliophora subbotini n. sp. (Tylenchida: Hemicycliophoridae) from China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Maria, Munawar, Cai, Ruihang, Qu, Nan, Castillo, Pablo, Zheng, Jingwu (2018): Morphological and molecular characterization of Hemicycliophora subbotini n. sp. (Tylenchida: Hemicycliophoridae) from China. Zootaxa 4433 (1): 161-173, DOI: https://doi.org/10.11646/zootaxa.4433.1.10
DOI: 10.15468/dsfyir
title: A new species of spider (Araneae, Linyphiidae, Islandiana) from a southern Indiana cave

description: This dataset contains the digitized treatments in Plazi based on the original journal article Milne, Marc A., Wells, Elizabeth (2018): A new species of spider (Araneae, Linyphiidae, Islandiana) from a southern Indiana cave. Subterranean Biology 26: 19-26, DOI: http://dx.doi.org/10.3897/subtbiol.26.25605, URL: http://dx.doi.org/10.3897/subtbiol.26.25605
DOI: 10.15468/fvr97a
title: A new species of Pseudopaludicola Miranda-Ribeiro (Anura: Leptodactylidae: Leiuperinae) from eastern Brazil, with novel data on the advertisement call of Pseudopaludicola falcipes (Hensel)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Andrade, Felipe Silva De, Haga, Isabelle Aquemi, Lyra, Mariana Lúcio, Leite, Felipe Sá Fortes, Kwet, Axel, Haddad, Célio Fernando Baptista, Toledo, Luís Felipe, Giaretta, Ariovaldo Antonio (2018): A new species of Pseudopaludicola Miranda-Ribeiro (Anura: Leptodactylidae: Leiuperinae) from eastern Brazil, with novel data on the advertisement call of Pseudopaludicola falcipes (Hensel). Zootaxa 4433 (1): 71-100, DOI: https://doi.org/10.11646/zootaxa.4433.1.4
DOI: 10.7925/drs1.duchas_4811605
title: Rinn Troisc

description: A collection of folklore and local history stories from Rinn Troisc (school) (Reentrusk, Co. Cork), collected as part of the Schools' Folklore Scheme, 1937-1938 under the supervision of teacher Domhnall Ó Súilleabháin.
description: Cistí Óir i bhFolach -- Weather -- Holy Wells -- Potatoes -- Marriages -- Cures -- Roads -- Food -- Feasts of the Year -- Bread -- Clothes / Kelly, Mr Dan -- Buying and Selling -- Houses Long Ago -- Famine -- Penal Laws -- Storms -- Old Prayers -- Mermaids / Sullivan, Brigid -- Old School -- Our Churn / Harrington, Julianna -- Old Sayings about the Weather -- My Townland / Sullivan, Eileen -- Boots / Harrington, Anna -- Bread -- Clothes -- Shops -- Houses Long Ago -- Famine -- Trades -- Tramps -- Prayers -- Landlord / Harrington, Anna -- Cures / Sullivan, Michael -- Lios -- Tailor -- Houses Long Ago -- Boots -- Houses Long Ago -- Trades Long Ago -- Riddles / Sullivan, Agnes -- Lios / Kelly, Julia -- Boots -- St Stephen's Day -- My Townland / Harrington, Anna
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4811606
title: Chluain

description: A collection of folklore and local history stories from An Chluain (school) (Cloan, Co. Cork), collected as part of the Schools' Folklore Scheme, 1937-1938 under the supervision of teacher Tadhg Ó Cearbhaill.
description: Folklore - A Story / Úrdail, Máire Ní -- Scéal / Murchadha, Máire Ní -- Scéal / Murchadha, Máire Ní -- Story / Arrachtáin, Diarmuid Ó h -- Father Downey / Murchadha, Máire Ní -- Scéal / Murchadha, Máire Ní -- Marriages / Arrachtáin, Diarmuid Ó h -- Story / Murchadha, Máire Ní -- Old Customs / Murchadha, Máire Ní -- Scéal / Murchadha, Máire Ní -- Scéal -- Story / Murchadha, Máire Ní -- Story / Murchadha, Máire Ní -- Story / Murchadha, Máire Ní -- Fairy Story / Murchadha, Máire Ní -- Story / Murchadha, Máire Ní -- Story / Murchadha, Máire Ní -- Leighiseanna / Murchadha, Máire Ní -- Story / Murchadha, Máire Ní -- Story / Murchadha, Máire Ní -- Bás agus an Peacach / Murchadha, Máire Ní -- Na Prátaí / Murchadha, Máire Ní -- St Patrick and Oisin / Murchadha, Máire Ní -- What Patience Is / Murchadha, Máire Ní -- Ainmhithe Allta / Murchadha, Máire Ní -- Small Christmas Night / Arrachtáin, Diarmuid Ó h -- Story / Arrachtáin, Máire Ní h -- Seantithe na Seanaimsire / Arrachtáin, Diarmuid Ó h -- Cuigeann / Arrachtáin, Diarmuid Ó h -- Féilí na Bliana / Arrachtáin, Diarmuid Ó h -- Bóithre An Cheantair / Arrachtáin, Diarmuid Ó h -- Cluichí / Úrdail, Máire Ní -- Doineann / Úrdail, Máire Ní -- Names of The Fields In my District / Úrdail, Máire Ní -- Cruatan / Úrdail, Máire Ní -- Place Names / Úrdail, Máire Ní -- Scéal / Arrachtáin, Diarmuid Ó h -- Scéal - The Glas Gaibhneach / Súílleabháin, Sighle Ní -- Scéal / Súilleabháin, Sighle Ní -- Scéal / Arrachtáin, Liam Ó h -- Local Maritime Phrases and Words / Arrachtáin, Liam Ó h -- Scéal / Arrachtáin, Diarmuid Ó h -- Scéal -- Scéal / hArrachtáin, Diarmuid Ó h -- Scéal -- Scéal / Arrachtáin, Liam Ó h -- Scéal / Arrachtáin, Diarmuid Ó h -- Place Names -- Scéal / Urdail, Máire Ní
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.7925/drs1.duchas_4811607
title: Lochán Mór

description: A collection of folklore and local history stories from Lochán Mór (school) (Loughane More, Co. Cork), collected as part of the Schools' Folklore Scheme, 1937-1938 under the supervision of teacher Seán Ó Súilleabháin.
description: Seanchas i dTaobh na hAimsire -- Doineann -- Old Schools -- Marriages -- Daoine Cáiliúla -- Naomh Pátrún an Cheantair -- Peil agus Iomáin -- Murty Óg O'Sullivan -- Gabha agus an Cheárta -- Gaidhleann Gabha -- Cúram na gCos -- Wild Animals -- Cluichí -- Roilig -- Rough Sketch-Map Showing School District and Part of Dursey -- Fathaigh agus Cailleacha -- Sean-Iarsmaí -- Ráthanna agus Liosanna -- Filí an Bhaile -- Mar a Fuair Peaidí Phádraig a Bhean -- Relics of Penal Days -- Hidden Treasures -- Landlords -- Holy Wells -- Measures -- Weeds and Herbs -- Old Trades -- Potatoes -- Others done by children 7 to be found in copy-books are - -- I heard the substance of the foregoing "stories" from my father, Joseph Sullivan
description: Supported by funding from the Department of Arts, Heritage and the Gaeltacht (Ireland), University College Dublin, and the National Folklore Foundation (Fondúireacht Bhéaloideas Éireann), 2014-2016.
DOI: 10.5281/zenodo.8220191
title: Data set Canada Greenland Sea Ice Algae dataset

description: A compiled dataset of ice algae primary production rates from Canada and Greenland including data on snow and ice thickness, nutrients in ice and below ice.
DOI: 10.5281/zenodo.8220190
title: Data set Canada Greenland Sea Ice Algae dataset

description: A compiled dataset of ice algae primary production rates from Canada and Greenland including data on snow and ice thickness, nutrients in ice and below ice.
DOI: 10.6084/m9.figshare.23694504
title: Deep learning neural network derivation and testing to distinguish acute poisonings

description: Acute poisoning is a significant global health burden, and the causative agent is often unclear. The primary aim of this pilot study was to develop a deep learning algorithm that predicts the most probable agent a poisoned patient was exposed to from a pre-specified list of drugs. Data were queried from the National Poison Data System (NPDS) from 2014 through 2018 for eight single-agent poisonings (acetaminophen, diphenhydramine, aspirin, calcium channel blockers, sulfonylureas, benzodiazepines, bupropion, and lithium). Two Deep Neural Networks (PyTorch and Keras) designed for multi-class classification tasks were applied. There were 201,031 single-agent poisonings included in the analysis. For distinguishing among selected poisonings, PyTorch model had specificity of 97%, accuracy of 83%, precision of 83%, recall of 83%, and a F1-score of 82%. Keras had specificity of 98%, accuracy of 83%, precision of 84%, recall of 83%, and a F1-score of 83%. The best performance was achieved in the diagnosis of single-agent poisoning in diagnosing poisoning by lithium, sulfonylureas, diphenhydramine, calcium channel blockers, then acetaminophen, in PyTorch (F1-score = 99%, 94%, 85%, 83%, and 82%, respectively) and Keras (F1-score = 99%, 94%, 86%, 82%, and 82%, respectively). Deep neural networks can potentially help in distinguishing the causative agent of acute poisoning. This study used a small list of drugs, with polysubstance ingestions excluded.Reproducible source code and results can be obtained at https://github.com/ashiskb/npds-workspace.git.
DOI: 10.6084/m9.figshare.23694504.v1
title: Deep learning neural network derivation and testing to distinguish acute poisonings

description: Acute poisoning is a significant global health burden, and the causative agent is often unclear. The primary aim of this pilot study was to develop a deep learning algorithm that predicts the most probable agent a poisoned patient was exposed to from a pre-specified list of drugs. Data were queried from the National Poison Data System (NPDS) from 2014 through 2018 for eight single-agent poisonings (acetaminophen, diphenhydramine, aspirin, calcium channel blockers, sulfonylureas, benzodiazepines, bupropion, and lithium). Two Deep Neural Networks (PyTorch and Keras) designed for multi-class classification tasks were applied. There were 201,031 single-agent poisonings included in the analysis. For distinguishing among selected poisonings, PyTorch model had specificity of 97%, accuracy of 83%, precision of 83%, recall of 83%, and a F1-score of 82%. Keras had specificity of 98%, accuracy of 83%, precision of 84%, recall of 83%, and a F1-score of 83%. The best performance was achieved in the diagnosis of single-agent poisoning in diagnosing poisoning by lithium, sulfonylureas, diphenhydramine, calcium channel blockers, then acetaminophen, in PyTorch (F1-score = 99%, 94%, 85%, 83%, and 82%, respectively) and Keras (F1-score = 99%, 94%, 86%, 82%, and 82%, respectively). Deep neural networks can potentially help in distinguishing the causative agent of acute poisoning. This study used a small list of drugs, with polysubstance ingestions excluded.Reproducible source code and results can be obtained at https://github.com/ashiskb/npds-workspace.git.
DOI: 10.5281/zenodo.8186030
title: TEAMx-PC22 (TEAMx pre-campaing 2022) - KITcube cloud radar horizontal winds (from PPI) in Kolsass

description: The RPG FMCW dual-pol dual-frequency cloud radar was operated in Kolsass. This data set contains wind speed and wind direction in 10 min. temporal resolution for both frequencies, 94 GHz and 35 GHz. The wind is determined from PPI at 70 degree elevation via an unfolding VAD algorithm (see Pierre Tabary, Georges Scialom, and Urs Germann. Real-time retrieval of the wind from aliased velocities measured by doppler radars. J. Atmos. Oceanic Technol., 18 (6):875–882, June 2001.) PPIs were performed from May, 31st, through Aug, 26th, 2022. There were technical problems which caused partly very long measurement gaps especially in the second half of the period. Data are stored as one NetCDF file.<br>
DOI: 10.5281/zenodo.8186031
title: TEAMx-PC22 (TEAMx pre-campaing 2022) - KITcube cloud radar horizontal winds (from PPI) in Kolsass

description: The RPG FMCW dual-pol dual-frequency cloud radar was operated in Kolsass. This data set contains wind speed and wind direction in 10 min. temporal resolution for both frequencies, 94 GHz and 35 GHz. The wind is determined from PPI at 70 degree elevation via an unfolding VAD algorithm (see Pierre Tabary, Georges Scialom, and Urs Germann. Real-time retrieval of the wind from aliased velocities measured by doppler radars. J. Atmos. Oceanic Technol., 18 (6):875–882, June 2001.) PPIs were performed from May, 31st, through Aug, 26th, 2022. There were technical problems which caused partly very long measurement gaps especially in the second half of the period. Data are stored as one NetCDF file.<br>
DOI: 10.5517/ccdc.csd.cc21hywd
title: CCDC 1892174: Experimental Crystal Structure Determination

description: Related Article: Phil Liebing, Ling Wang, John W. Gilje, Liane Hilfert, Frank T. Edelmann|2019|Polyhedron|164|228|doi:10.1016/j.poly.2019.02.056
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.cc21pc59
title: CCDC 1897360: Experimental Crystal Structure Determination

description: Related Article: Ling-Ling Zheng, Jiong-Fei Wang, Jing Wang, Ai-Ju Zhou, Chun-Xian Liao, Sheng Hu|2020|Inorg.Chim.Acta|501|119303|doi:10.1016/j.ica.2019.119303
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.cc235khc
title: CCDC 1941762: Experimental Crystal Structure Determination

description: Related Article: Valery G. Vlasenko, Anatolii S. Burlov, Yurii V. Koshchienko, Alexandra A. Kolodina, Yan V. Zubavichus, Vladimir A. Lazarenko, Victor N. Khrustalev|2020|J.Mol.Struct.|1203|127450|doi:10.1016/j.molstruc.2019.127450
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.cc22gcvs
title: CCDC 1920445: Experimental Crystal Structure Determination

description: Related Article: A. Asano, M. Doi|2019|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|75|1182|doi:10.1107/S2053229619007952
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.23866962.v12
title: Untitled Item

description: Regridding Global CMIP6 GCMs dataset(0.5 degree)Historical dataset: 7 CMIP6 GCMs (1850-2014, ACCESS-CM2 to GFDL-ESM4)Future dataset: 7 CMIP6 GCMs and 4 SSP scenarios (2015-2100)Composition of dataset: Average temperature, Maximum temperature, Minimum temperature, Windspeed, Relative humidity, Solar radiationIf you are using our codes and dataset, please use the following references:Song, Y.H., Chung, E.S., Shahid, S., Kim, Y.J., Kim, D.K. 2023. Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiration. Scientific Data.<br>
DOI: 10.57841/casdc.0001774
title: 交错式扇贝阻尼密封动力特性研究数据集
DOI: 10.18712/nsd-nsd2309-2-v2
title: Travel and Holiday Survey 2015, 1st quarter, Travel File

description: "Travel and Holiday Survey 2015, 1st quarter, Travels" is a continuance of Statistics Norway's Omnibus Survey (1992-2004). Data has been collected on quarterly basis. The purpose is to throw light on Norwegians travel habits in Norway and abroad, as well as to gather other official statistics. This means that the Travel and Holiday Survey also captures other themes than travel. This is the travel file. A person file is also available when ordered. You can see an overview of the various themes that are included in the first quarter below.

- Household
- Working conditions
- Travel with at least one overnight stop
- Smoking and smoking habits
- Use of fuelwood
- Income
DOI: 10.18712/nsd-nsd2310-2-v2
title: Travel and Holiday Survey 2015, 2nd quarter, Travel File

description: Travel and Holiday Survey is a continuance of Statistics Norway's Omnibus Survey (1992-2004). The survey is carried out on quarterly basis. The main goal of the survey is to map out Norwegians travel habits in Norway and abroad, as well as to gather other official statistics. This means that the Travel and Holiday Survey also captures other themes than travel. The themes covered in q2 are: travel with at least one overnight stop, household, use of fuelwood, ICT usage in households and influenza vaccine.
DOI: 10.18712/nsd-nsd2423-2-v2
title: Travel and Holiday Survey 2016, 4th quarter, Travel File

description: The travel and holiday survey is conducted four times a year, once every quarter. The main purpose of the survey is to establish Norwegians travel habits as well as to gather other official statistics. Apart from data about norwegians travel habits data is also collected about purchasing products outside of the country, use of tobacco, alcohol and other substances, use of internet and informational technology, solid fuel heating, flu vaccine, vaccination of children and also attitudes towards immigration. Some subjects are included every quarter, others are only included once. 

This is the travel file. A person file is also available for order. An overview of subjects covered in the fourth quarter follows below.

- Household
- Work and employment
- Travels with atleast one overnight stop
- Nicotine and alcohol habits
- Solid fuel heating
- Income
DOI: 10.26050/wdcc/ar6.c6acmimi
title: IPCC DDC: MIROC MIROC6 model output prepared for CMIP6 AerChemMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.AerChemMIP.MIROC.MIROC6' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MIROC6 climate model, released in 2017, includes the following components: aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T85; 256 x 128 longitude/latitude; 81 levels; top level 0.004 hPa), land: MATSIRO6.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), seaIce: COCO4.9. The model was run by the JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan) (MIROC) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
DOI: 10.5281/zenodo.8175221
title: Marktstammdatenregister Monthly Database Dump

description: Since the dataset provided by Open-MaStR doesn't seem to get updated anymore and only uploads CSV files I will provide a monthly updated database instead. Like the original publication the data set contains all data from the Marktstammdatenregister. The data set is downloaded and processed with the software open-MaStR. If you don't have much experience dealing with databases directly a simple way to interact with the data set is using DB Browser for SQLite. Simply open the file there and you are able to browse all tables included in the dataset. This also allows exporting individual tables as CSV files. License information: Marktstammdatenregister - © Bundesnetzagentur für Elektrizität, Gas, Telekommunikation, Post und Eisenbahnen | DL-DE-BY-2.0