cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4311577
title: Greek Parliament Proceedings, 1989-2020

description: This dataset is produced on behalf of iMEdD by PhD Student in Machine Learning Konstantina Dritsa, with the contribution of data journalist and iMEdD Lab Project Manager Kelly Kiki. iMEdD (incubator for Media Education and Development) is a non-profit journalism organisation that supports and promotes transparency, credibility and independence in journalism. Lab is iMEdD’s content production division which publishes original interactive investigative and data-driven stories by experimenting with new forms and tools in journalism. This dataset is the next version of a previous upload, which originated from the work implemented during the course of the Master thesis entitled "Speech quality and sentiment analysis on the Hellenic Parliament proceedings" at the Athens University of Economics & Business in 2018 under the supervision of the Associate Professor Panagiotis Louridas. This dataset includes 1,280,918 speeches (rows) of Greek parliament members with a total volume of 2.4 GB, that were exported from 5,355 parliamentary sitting record files. They extend chronologically from 1989 up to late July 2020. The dataset consists of a .csv file in UTF-8 encoding and includes the following columns of data: <strong>member_name</strong>: the official name of the parliament member who talked during a sitting. <strong>sitting_date</strong>: the date that the sitting took place. <strong>parliamentary_period</strong>: the name and/or number of the parliamentary period that the speech took place in. A parliamentary period includes multiple parliamentary sessions. <strong>parliamentary_session</strong>: the name and/or number of the parliamentary session that the speech took place in. A parliamentary session includes multiple parliamentary sittings. <strong>parliamentary_sitting</strong>: the name and/or number of the parliamentary sitting that the speech took place in. <strong>political_party</strong>: the political party that the speaker belonged to the moment of their speech. <strong>government</strong>: the government in force when the speech took place. <strong>member_region</strong>: the electoral district the speaker belonged to. <strong>roles</strong>: information about the parliamentary roles and/or government position of the speaker the moment of their speech. <strong>member_gender</strong>: the sex of the speaker <strong>speech</strong>: the speech that the member made during the parliamentary sitting The methodology followed for the production of this dataset is described in the iMEdD Lab's article entitled "The creation of a dataset with the parliament proceedings within 31 years". Scripts and relevant documentation are available on GitHub.
DOI: 10.5281/zenodo.4311576
title: Greek Parliament Proceedings, 1989-2020

description: This dataset is produced on behalf of iMEdD by PhD Student in Machine Learning Konstantina Dritsa, with the contribution of data journalist and iMEdD Lab Project Manager Kelly Kiki. iMEdD (incubator for Media Education and Development) is a non-profit journalism organisation that supports and promotes transparency, credibility and independence in journalism. Lab is iMEdD’s content production division which publishes original interactive investigative and data-driven stories by experimenting with new forms and tools in journalism. This dataset is the next version of a previous upload, which originated from the work implemented during the course of the Master thesis entitled "Speech quality and sentiment analysis on the Hellenic Parliament proceedings" at the Athens University of Economics & Business in 2018 under the supervision of the Associate Professor Panagiotis Louridas. This dataset includes 1,280,918 speeches (rows) of Greek parliament members with a total volume of 2.4 GB, that were exported from 5,355 parliamentary sitting record files. They extend chronologically from 1989 up to late July 2020. The dataset consists of a .csv file in UTF-8 encoding and includes the following columns of data: <strong>member_name</strong>: the official name of the parliament member who talked during a sitting. <strong>sitting_date</strong>: the date that the sitting took place. <strong>parliamentary_period</strong>: the name and/or number of the parliamentary period that the speech took place in. A parliamentary period includes multiple parliamentary sessions. <strong>parliamentary_session</strong>: the name and/or number of the parliamentary session that the speech took place in. A parliamentary session includes multiple parliamentary sittings. <strong>parliamentary_sitting</strong>: the name and/or number of the parliamentary sitting that the speech took place in. <strong>political_party</strong>: the political party that the speaker belonged to the moment of their speech. <strong>government</strong>: the government in force when the speech took place. <strong>member_region</strong>: the electoral district the speaker belonged to. <strong>roles</strong>: information about the parliamentary roles and/or government position of the speaker the moment of their speech. <strong>member_gender</strong>: the sex of the speaker <strong>speech</strong>: the speech that the member made during the parliamentary sitting The methodology followed for the production of this dataset is described in the iMEdD Lab's article entitled "The creation of a dataset with the parliament proceedings within 31 years". Scripts and relevant documentation are available on GitHub.
DOI: 10.34740/kaggle/dsv/1724821
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.7763549
title: Heliconius Data Set

description: This is a large DNA matrix in Phylip format for 13 individuals from four species of Heliconius. It was collected in Martin et al. (2013) and we used it in out paper describing the software HyDe (Blischak et al. 2018).
DOI: 10.6084/m9.figshare.7763549.v2
title: Heliconius Data Set

description: This is a large DNA matrix in Phylip format for 13 individuals from four species of Heliconius. It was collected in Martin et al. (2013) and we used it in out paper describing the software HyDe (Blischak et al. 2018).
DOI: 10.6084/m9.figshare.7763549.v1
title: Heliconius Data Set

description: This is a large DNA matrix in Phylip format for 13 individuals from four species of Heliconius. It was collected in Martin et al. (2013) and we used it in out paper describing the software HyDe (Blischak et al. 2018).
DOI: 10.21258/1441581
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899360
DOI: 10.21258/1454787
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 893426
DOI: 10.21258/1476452
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898927
DOI: 10.21258/1442827
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898226
DOI: 10.21258/1464391
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897008
DOI: 10.5284/1083505
title: The City Fibre Project, Southampton. Archaeological Watching Brief (SOU1711)

description: The Archaeology Unit of Southampton City Council carried out a watching brief in March and April 2016 on groundworks for communications cabling between Palmerston Road and Castle Way in the historic core of Southampton. The work was commissioned by City Fibre Holdings Limited. Groundworks in many trenches did not penetrate modern deposits, and in places the excavated trench could not go to full depth due to pre-existing services. Nevertheless, the natural brickearth, a possible middle Saxon layer, the remains of the medieval Town Wall or its robber trench, and a probable 19th-century feature were exposed during the works.
DOI: 10.21258/1470568
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 891913
DOI: 10.21258/1456072
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 892032
DOI: 10.21258/1439844
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899127
DOI: 10.21258/1465376
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898717
DOI: 10.21258/1439711
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899048
DOI: 10.5284/1083506
title: Townhill Park, Southampton. Archaeological Watching Brief on Soil Investigations (SOU1680)

description: Southampton City Council Archaeology Unit carried out a watching brief on soil investigations carried out as part of a proposed redevelopment of a number of modern multi-storey housing units in the Townhill Park area of Southampton, as part of the Council's ongoing estates regeneration programme. The site lies in an area of known archaeology and a watching brief was held on the works to record any archaeology encountered during the groundworks. The 35 soil investigations included boreholes, window samples and trial pits. At the south end of the site a buried soil contained burnt flints, a flint flake, and a sherd of abraded medieval cooking pot, suggesting probable prehistoric activity over a wide area, followed by period of medieval agricultural use. At the north end of the site investigations in an infilled stream valley found up to 1.6m of probable water-deposited material. These deposits may relate to the fishponds upstream of this area recorded in the Historic Environment Record, and referred in the Townhill Stockwell papers of 1603/4. The 1960s development has caused considerable disturbance in some areas, but had protected the potential archaeology in others.
DOI: 10.21258/1479005
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898014
DOI: 10.21258/1475604
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897990
DOI: 10.21258/1460872
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902177
DOI: 10.21258/1475900
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 892965
DOI: 10.21258/1457174
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899031
DOI: 10.6084/m9.figshare.13348406.v1
title: Psychological Distress and Burden of Care among Family Caregivers of Patients with Mental Illness in a Neuropsychiatric Outpatient Clinic in Nigeria

description: Participants studied were family caregivers of relatives diagnosed mental illness. Females were 57% and males 43.1%. Majority of participants were aged 15-29 years 43.6%.
DOI: 10.6084/m9.figshare.13348241
title: DBPedia

description: DBPedia Ontology Classification Dataset<br>Version 2, Updated 09/09/2015<br><br>LICENSE<br>The DBpedia datasets are licensed under the terms of the Creative Commons Attribution-ShareAlike License and the GNU Free Documentation License. For more information, please refer to http://dbpedia.org. For a recent overview paper about DBpedia, please refer to: Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N. Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick van Kleef, Sören Auer, Christian Bizer: DBpedia – A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia. Semantic Web Journal, Vol. 6 No. 2, pp 167–195, 2015.<br>The DBPedia ontology classification dataset is constructed by Xiang Zhang (xiang.zhang@nyu.edu), licensed under the terms of the Creative Commons Attribution-ShareAlike License and the GNU Free Documentation License. It is used as a text classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. Advances in Neural Information Processing Systems 28 (NIPS 2015).<br><br>DESCRIPTION<br>The DBpedia ontology classification dataset is constructed by picking 14 non-overlapping classes from DBpedia 2014. They are listed in classes.txt. From each of thse 14 ontology classes, we randomly choose 40,000 training samples and 5,000 testing samples. Therefore, the total size of the training dataset is 560,000 and testing dataset 70,000.<br>The files train.csv and test.csv contain all the training samples as comma-sparated values. There are 3 columns in them, corresponding to class index (1 to 14), title and content. The title and content are escaped using double quotes ("), and any internal double quote is escaped by 2 double quotes (""). There are no new lines in title or content.<br><br><b>Classes</b><b><br></b>CompanyEducationalInstitutionArtistAthleteOfficeHolderMeanOfTransportationBuildingNaturalPlaceVillageAnimalPlantAlbumFilmWrittenWork<br>
DOI: 10.21258/1470136
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898006
DOI: 10.5281/zenodo.4311698
title: Multi-fidelity Generative Deep Learning Turbulent Flows

description: Data sets for the two numerical examples in the paper Multi-fidelity Generative Deep Learning Turbulent Flows as well as two pre-trained models. In this work, a novel multi-fidelity deep generative model is introduced for the surrogate modeling of high-fidelity turbulent flow fields given the solution of a computationally inexpensive but inaccurate low-fidelity solver. The resulting surrogate is able to generate physically accurate turbulent realizations at a computational cost magnitudes lower than that of a high-fidelity simulation. The deep generative model developed is a conditional invertible neural network, built with normalizing flows, with recurrent LSTM connections that allow for stable training of transient systems with high predictive accuracy. Data is provided from OpenFOAM LES simulations for turbulent flow over backwards step and flow around an array of cylinders. Data-set Files: backward_step_testing.tar.gz - Backward step testing data. backward_step_training.tar.gz - Backward step training data. cylinder_array_testing.tar.gz - Cylinder array testing data. cylinder_array_training.tar.gz - Cylinder array training data. Pre-trained Models: bstepWorkspace400.zip - Backward step pre-trained model. cylinderWorkspace400.zip - Cylinder array pre-trained model.
description: Please see readme.txt in each data set for additional information.
description: {"references": ["https://arxiv.org/abs/2006.04731"]}
DOI: 10.5281/zenodo.4298895
title: Multi-fidelity Generative Deep Learning Turbulent Flows

description: Data sets for the two numerical examples in the paper Multi-fidelity Generative Deep Learning Turbulent Flows as well as two pre-trained models. In this work, a novel multi-fidelity deep generative model is introduced for the surrogate modeling of high-fidelity turbulent flow fields given the solution of a computationally inexpensive but inaccurate low-fidelity solver. The resulting surrogate is able to generate physically accurate turbulent realizations at a computational cost magnitudes lower than that of a high-fidelity simulation. The deep generative model developed is a conditional invertible neural network, built with normalizing flows, with recurrent LSTM connections that allow for stable training of transient systems with high predictive accuracy. Data is provided from OpenFOAM LES simulations for turbulent flow over backwards step and flow around an array of cylinders. Data-set Files: backward_step_testing.tar.gz - Backward step testing data. backward_step_training.tar.gz - Backward step training data. cylinder_array_testing.tar.gz - Cylinder array testing data. cylinder_array_training.tar.gz - Cylinder array training data. Pre-trained Models: bstepWorkspace400.zip - Backward step pre-trained model. cylinderWorkspace400.zip - Cylinder array pre-trained model.
description: Please see readme.txt in each data set for additional information.
description: {"references": ["https://arxiv.org/abs/2006.04731"]}
DOI: 10.21258/1461907
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 891806
DOI: 10.21258/1464746
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897134
DOI: 10.21258/1446801
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 891704
DOI: 10.21258/1439559
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899448
DOI: 10.21258/1435889
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899656
DOI: 10.21258/1474533
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 891904
DOI: 10.21258/1443258
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 892933
DOI: 10.21258/1473315
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899384
DOI: 10.21258/1477064
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 891805
DOI: 10.21258/1478752
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898531
DOI: 10.21258/1464760
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899289
DOI: 10.21258/1444767
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 902096
DOI: 10.21258/1441330
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 896976
DOI: 10.21258/1446058
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897147
DOI: 10.21258/1448699
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897682
DOI: 10.21258/1450172
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897204
DOI: 10.25505/fiz.icsd.cc21ydgw
title: CSD 1905088: Experimental Crystal Structure Determination

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DOI: 10.21258/1456925
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 898753
DOI: 10.5517/ccdc.csd.cc246tnv
title: CCDC 1972767: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc247v7h
title: CCDC 1973746: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc227tqw
title: CCDC 1914148: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc24ndbk
title: CCDC 1985808: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc24p6fh
title: CCDC 1986586: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc24t2cf
title: CCDC 1990304: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc24t2dg
title: CCDC 1990305: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc24t2fh
title: CCDC 1990306: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc24x55f
title: CCDC 1993274: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc24x56g
title: CCDC 1993275: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc255ksq
title: CCDC 2001353: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc258rlt
title: CCDC 2004416: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc25c4zp
title: CCDC 2006722: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc25c50r
title: CCDC 2006723: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc25c51s
title: CCDC 2006724: Experimental Crystal Structure Determination

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title: CCDC 2006725: Experimental Crystal Structure Determination

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title: CCDC 2006726: Experimental Crystal Structure Determination

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title: CCDC 2006727: Experimental Crystal Structure Determination

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title: CCDC 2011535: Experimental Crystal Structure Determination

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DOI: 10.21258/1462052
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 899097
DOI: 10.5517/ccdc.csd.cc25v99n
title: CCDC 2021271: Experimental Crystal Structure Determination

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title: CCDC 2021518: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc25vkcz
title: CCDC 2021521: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc25vkd0
title: CCDC 2021522: Experimental Crystal Structure Determination

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DOI: 10.21258/1439340
title: Schweizerisches Landesforstinventar - Ergebnistabelle Nr. 897355