cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/jc8nvk4t33.5
title: Data for: Comparative assessment of NCEP and ECMWF global datasets and numerical approaches on rough sea generation for ship navigation based on numerical simulation and shipboard measurements

description: This file consists all the simulated and observed wind for all eight cases, by all linear interpolation method and WRF downscaling simulations. Other researchers may make other possible findings from those data about the wind characteristics on-board a ship.
DOI: 10.17894/ucph.e9dea24d-48e0-42c5-a17f-8b149ffa5309
title: Ad hoc breeding of a genetically depauperate landrace of noble fir using SNP genotyping via high-throughput targeted sequencing
DOI: 10.5281/zenodo.3905045
title: Database for Market uptake of concentrating solar power in Europe: model-based analysis of drivers and policy trade-offs. MUSTEC project.

description: This dataset contains the data underlying the modelling activities of the MUSTEC (<em>Market Uptake of Solar Thermal Electricity through Cooperation</em>) project used in the models Green-X (TU Wien) and Enertile (Fraunhofer ISI). For description of the modelled scenarios, results and findings, see: Resch, G., Schöniger, F., Kleinschmitt, C., Franke, K., Sensfuß, F., Thonig, R., and Lilliestam, J.:<em> </em><em> Market uptake of concentrating solar power in Europe: model-based analysis of drivers and policy trade-offs. </em>Deliverable 8.2 MUSTEC project, TU Wien, Wien. For information on the project see: https://www.mustec.eu/ For data descriptions, licence, and further information, see README.md.
description: {"references": ["Resch, G., Sch\u00f6niger, F., Kleinschmitt, C., Franke, K., Sensfu\u00df, F., Thonig, R., and Lilliestam, J.: Market uptake of concentrating solar power in Europe: model-based analysis of drivers and policy trade-offs. Deliverable 8.2 MUSTEC project, TU Wien, Wien."]}
DOI: 10.5281/zenodo.3905044
title: Database for Market uptake of concentrating solar power in Europe: model-based analysis of drivers and policy trade-offs. MUSTEC project.

description: This dataset contains the data underlying the modelling activities of the MUSTEC (<em>Market Uptake of Solar Thermal Electricity through Cooperation</em>) project used in the models Green-X (TU Wien) and Enertile (Fraunhofer ISI). For description of the modelled scenarios, results and findings, see: Resch, G., Schöniger, F., Kleinschmitt, C., Franke, K., Sensfuß, F., Thonig, R., and Lilliestam, J.:<em> </em><em> Market uptake of concentrating solar power in Europe: model-based analysis of drivers and policy trade-offs. </em>Deliverable 8.2 MUSTEC project, TU Wien, Wien. For information on the project see: https://www.mustec.eu/ For data descriptions, licence, and further information, see README.md.
description: {"references": ["Resch, G., Sch\u00f6niger, F., Kleinschmitt, C., Franke, K., Sensfu\u00df, F., Thonig, R., and Lilliestam, J.: Market uptake of concentrating solar power in Europe: model-based analysis of drivers and policy trade-offs. Deliverable 8.2 MUSTEC project, TU Wien, Wien."]}
DOI: 10.7910/dvn/cupoil/afvuvz
title: FinalMaterials.zip

description: Replication materials and dataset
DOI: 10.5281/zenodo.3365370
title: Bootstrapped Lexicon of German Verbal Polarity Shifters

description: We provide a bootstrapped lexicon of German verbal polarity shifters. Our lexicon covers 2595 verbs of GermaNet. Polarity shifter labels are given for each word lemma. All labels were assigned by an expert annotator who is a native speaker of German. <strong>Data</strong> The data consists of two lists of GermaNet verbs annotated for whether they cause shifting: <code>verbal_shifters.gold_standard.txt</code>: The initial gold standard (§3) of 2000 randomly sampled verbs. <code>verbal_shifters.bootstrapping.txt</code>: The bootstrapped 595 verbs (§5.3) that were labelled as shifters by our best classifier and then manually annotated. <strong>Format</strong> Each line contains a verb and its label, separate by a whitespace. <strong>Attribution</strong> This dataset was created as part of the following publication: Marc Schulder, Michael Wiegand, Josef Ruppenhofer (2018). <strong>"Automatically Creating a Lexicon of Verbal Polarity Shifters: Mono- and Cross-lingual Methods for German"</strong>. <em>Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018)</em>. Santa Fe, New Mexico, USA, August 20 - August 26, 2018. DOI: 10.5281/zenodo.3365694. If you use the data in your research or work, please cite the publication.
description: This work was partially supported by the German Research Foundation (DFG) under grants RU 1873/2-1 and WI4204/2-1.
DOI: 10.5281/zenodo.3365369
title: Bootstrapped Lexicon of German Verbal Polarity Shifters

description: We provide a bootstrapped lexicon of German verbal polarity shifters. Our lexicon covers 2595 verbs of GermaNet. Polarity shifter labels are given for each word lemma. All labels were assigned by an expert annotator who is a native speaker of German. <strong>Data</strong> The data consists of two lists of GermaNet verbs annotated for whether they cause shifting: <code>verbal_shifters.gold_standard.txt</code>: The initial gold standard (§3) of 2000 randomly sampled verbs. <code>verbal_shifters.bootstrapping.txt</code>: The bootstrapped 595 verbs (§5.3) that were labelled as shifters by our best classifier and then manually annotated. <strong>Format</strong> Each line contains a verb and its label, separate by a whitespace. <strong>Attribution</strong> This dataset was created as part of the following publication: Marc Schulder, Michael Wiegand, Josef Ruppenhofer (2018). <strong>"Automatically Creating a Lexicon of Verbal Polarity Shifters: Mono- and Cross-lingual Methods for German"</strong>. <em>Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018)</em>. Santa Fe, New Mexico, USA, August 20 - August 26, 2018. DOI: 10.5281/zenodo.3365694. If you use the data in your research or work, please cite the publication.
description: This work was partially supported by the German Research Foundation (DFG) under grants RU 1873/2-1 and WI4204/2-1.
DOI: 10.5281/zenodo.3921934
title: CysLT2R_6RZ9

description: Serial small-wedge crystallography dataset, associated with the publication: Marin et al, "Small-wedge synchrotron and serial XFEL datasets for Cysteinyl leukotriene GPCRs"
DOI: 10.5281/zenodo.3842753
title: CysLT2R_6RZ6

description: Serial small-wedge crystallography dataset, associated with the publication: Marin et al, "Small-wedge synchrotron and serial XFEL datasets for Cysteinyl leukotriene GPCRs"
DOI: 10.5281/zenodo.3921911
title: CysLT1R_6RZ4

description: Serial small-wedge crystallography dataset, associated with the publication: Marin et al, "Small-wedge synchrotron and serial XFEL datasets for Cysteinyl leukotriene GPCRs"
DOI: 10.5281/zenodo.3921931
title: CysLT2R_6RZ8

description: Serial small-wedge crystallography dataset, associated with the publication: Marin et al, "Small-wedge synchrotron and serial XFEL datasets for Cysteinyl leukotriene GPCRs"
DOI: 10.5281/zenodo.3937237
title: Predictability of European winter 2019/20: Indian Ocean dipole impacts on the NAO

description: Data and code to reproduce the figures in Atmospheric Science Letters publication "Predictability of European winter 2019/20: Indian Ocean dipole impacts on the NAO". Please cite the published ASL article if you use this dataset.
DOI: 10.5281/zenodo.3872080
title: Predictability of European winter 2019/20: Indian Ocean dipole impacts on the NAO

description: Data and code to reproduce the figures in Atmospheric Science Letters publication "Predictability of European winter 2019/20: Indian Ocean dipole impacts on the NAO". Please cite the published ASL article if you use this dataset.
DOI: 10.5281/zenodo.3569743
title: CysLT2R_6RZ7

description: Serial crystallography dataset
DOI: 10.5281/zenodo.3937268
title: The effect of movement coordination with music on polyrhythmic production: Comparison between artistic swimmers and water polo players during a complex motor task of eggbeater kicks

description: TableI. Eggbeater kick frequency over three trials of artistic swimmers and water polo players in task1 TableII. Eggbeater kick and circular arm movement frequency in task2: Normal-slow-fast task TableIII. Eggbeater kick and circular arm movement frequency in task2: Normal-fast-slow task TableIV. Coefficient of variation of circular arm movement range of motion
DOI: 10.5281/zenodo.3937267
title: The effect of movement coordination with music on polyrhythmic production: Comparison between artistic swimmers and water polo players during a complex motor task of eggbeater kicks

description: TableI. Eggbeater kick frequency over three trials of artistic swimmers and water polo players in task1 TableII. Eggbeater kick and circular arm movement frequency in task2: Normal-slow-fast task TableIII. Eggbeater kick and circular arm movement frequency in task2: Normal-fast-slow task TableIV. Coefficient of variation of circular arm movement range of motion
DOI: 10.5281/zenodo.3370051
title: Word Embedding of Amazon Product Review Corpus

description: A word embedding of the Amazon Product Review Corpus (Jindal and Liu, 2008). Created using Word2Vec in CBOW mode, 500 dimensions and window size 5. Words have been lemmatised and particle verbs have been merged into a single token (e.g. <code>calm_down</code>). <strong>Attribution</strong> This dataset was created as part of the following publication: Marc Schulder, Michael Wiegand, Josef Ruppenhofer and Benjamin Roth (2017). <strong>"Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features"</strong>. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP). Taipei, Taiwan, November 27 - December 3, 2017. DOI: 10.5281/zenodo.3365609. If you use the data in your research or work, please cite the publication.
description: {"references": ["Jindal, Nitin and Bing Liu (2008). \"Opinion Spam and Analysis.\" In: Proceedings of the International Conference on Web Search and Data Mining (WSDM). Palo Alto, California, USA: Association for Com- puting Machinery, pp. 219\u2013230. isbn: 978-1-59593-927-2. doi: 10. 1145/1341531.1341560"]}
DOI: 10.5281/zenodo.3370050
title: Word Embedding of Amazon Product Review Corpus

description: A word embedding of the Amazon Product Review Corpus (Jindal and Liu, 2008). Created using Word2Vec in CBOW mode, 500 dimensions and window size 5. Words have been lemmatised and particle verbs have been merged into a single token (e.g. <code>calm_down</code>). <strong>Attribution</strong> This dataset was created as part of the following publication: Marc Schulder, Michael Wiegand, Josef Ruppenhofer and Benjamin Roth (2017). <strong>"Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features"</strong>. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP). Taipei, Taiwan, November 27 - December 3, 2017. DOI: 10.5281/zenodo.3365609. If you use the data in your research or work, please cite the publication.
description: {"references": ["Jindal, Nitin and Bing Liu (2008). \"Opinion Spam and Analysis.\" In: Proceedings of the International Conference on Web Search and Data Mining (WSDM). Palo Alto, California, USA: Association for Com- puting Machinery, pp. 219\u2013230. isbn: 978-1-59593-927-2. doi: 10. 1145/1341531.1341560"]}
DOI: 10.5286/isis.e.rb1990228-1
title: Studying copolymer micelles internal structure by contrast variation SANS
DOI: 10.21227/97zz-xw18
title: Coventry-2018

description: Coventry-2018 is a human activity recognition dataset captured by three Panasonic® Grid-EYE (AMG8833) infrared sensors in March 2018. The Grid-EYE sensors represent a 60 field of view scene by an 8 × 8 array named frame. The data streams are synchronized to 10 frames per second and saved as *.csv recordings using the LabVIEW® software. Two layouts are considered in this dataset with different geometry sizes: 1) small layout; and 2) large layout. The three sensors are located 1.5m from the area of interest in the small geometry size, while the distance grows to 2.5m for the large geometry size as illustrated in the dataset image. The dataset consists of 15 gestures distinguished in two categories: 1) single-subject gestures; and 2) double-subject gestures. There exist eight single-subject activities, and seven double-subject activities. Each single-subject gesture is repeated 10 times by three participants, while for double-subject gestures, the three possible combinations of the three subjects are used and similarly, the gestures are repeated 10 times. It needs to be emphasized that the single-subject activities are conducted in both layouts (small layout and large layout), while the double-subject activities are conducted only in the large layout.
DOI: 10.18434/m32244
title: Supporting Information to accompany: Excess Entropy Scaling in Supercooled Binary Mixtures

description: Initial configurations from equilibration needed to reproduce simulation results
DOI: 10.5281/zenodo.3937295
title: Number of channels involved following a break in the EU DEMO HCPB and WCLL BB FW

description: Excel file reporting the number of involved FW channels following a break in the FW for the EU DEMO HCPB and WCLL Breeding Blanket concepts. The file also reports the resulting flow area. Different break sizes are assumed: 0.01 m², 0.1 m² (small breaks), 1 m², 2 m², 5 m² (large breaks). Two direction of break propagation are considered: poloidal first, then toroidal (approach 1); toroidal first, then poloidal (approach 2)
DOI: 10.5281/zenodo.3937294
title: Number of channels involved following a break in the EU DEMO HCPB and WCLL BB FW

description: Excel file reporting the number of involved FW channels following a break in the FW for the EU DEMO HCPB and WCLL Breeding Blanket concepts. The file also reports the resulting flow area. Different break sizes are assumed: 0.01 m², 0.1 m² (small breaks), 1 m², 2 m², 5 m² (large breaks). Two direction of break propagation are considered: poloidal first, then toroidal (approach 1); toroidal first, then poloidal (approach 2)
DOI: 10.5281/zenodo.3934680
title: Data for "Flat band superconductivity in type-II Weyl-semimetal WTe2 induced by a normal metal contact"

description: Data for the publication "Flat band superconductivity in type-II Weyl-semimetal WTe<sub>2</sub> induced by a normal metal contact"
DOI: 10.5281/zenodo.2547395
title: Bitcoin Network Transaction Inv Data with Java Timestamp and Originator Id

description: The data is a gz compression of a csv file with the following layout: &lt;timestamp in ms&gt;,&lt;originator id as sha-256 hash in hexadecimal string representation&gt;, &lt;hash of BTC Transaction in hexadecimal string representation&gt; Example lines: 1547779473468,6cf1100aaccec75da23995512fc7c7a5b6e25224f5903af011e78691c03d0455,a73578820a41aa6180621bcd90af1997c88794b33d8db2f004ee37c3e09b10ec<br> 1547779473468,6cf1100aaccec75da23995512fc7c7a5b6e25224f5903af011e78691c03d0455,0beb35a4338b026fb4ceb0d215d372f67dfb0c73f1e21157e03dde2fbc6b94ee The data was gathered with a modified version of bitcoinj 0.14.7. The modification consisted of: Blinding Originator IP+Port by hashing with a key generated at application startup Logging every Transaction Inv message to a file The application running the modified library just consisted of creating a Peer Pool of at most 6000 connections and limiting broadcasting to require 100000 connections, set via bitcoinj parameters. The data of crawler-82GB.gz was gathered between 17.01.2019, 15:30 and 18.01.2019, 03:00 at Ulm University in Ulm, Germany. The data of crawler-01-02-2019-09-54-59-ULM.csv.gz was gathered on 01.02.2019 at Ulm Iniversity in Ulm, Germany as well. The data of crawler-24.01.2019-*.gz was gathered between 24.01.2019, 10:00 and 25.01.2019 10:00 on Microsoft Azure instances. The selected region of Azure is indicated in the filename: UK, South; US, East; Southeast Asia. The datasets of crawler-06.02.2019-*-SIMUL.csv.gz were gathered with the same runtime key so ID's can be linked within the datasets. Locations again are Ulm University, Germany, and Azure UK, South (GBS); US, East (USA); Southeast Asia (SEA). ETH-crawler-20+21.02.2019.csv contains a similar collection of the Ethereum network for comparisson.
DOI: 10.5281/zenodo.3364812
title: Bootstrapped Lexicon of English Verbal Polarity Shifters

description: An extended version of this dataset that also covers nominal and adjectival polarity shifters can be found at doi:10.5281/zenodo.3365601. We provide a bootstrapped lexicon of English verbal polarity shifters. Our lexicon covers 3043 verbs of WordNet v3.1 (Miller et al., 1990) that are single word or particle verbs. Polarity shifter labels are given for each word lemma. <strong>Data</strong> The data consists of: Two lists of WordNet verbs (Miller et al., 1990), annotated for whether they cause shifting. The initial gold standard (§2) of 2000 randomly chosen verbs. The bootstrapped 1043 verbs (§5.3) that were labelled as shifters by our best classifier and then manually annotated. Data set of verb phrases from the Amazon Product Review Data corpus (Jindal & Liu, 2008), annotated for polarity of phrase and polar noun. <strong>1. Verbal Shifters</strong> <strong>Files</strong> The initial gold standard: <code>verbal_shifters.gold_standard.txt</code> The bootstrapped verbs: <code>verbal_shifters.bootstrapping.txt</code> <strong>Format</strong> Each line contains a verb and its label, separate by a whitespace. Multiword expressions are separated by an underscore (WORD_WORD). All labels were assigned by an expert annotator. <strong>2. Sentiment Verb Phrases</strong> <strong>Files</strong> All annotated verb phrases: <code>sentiment_phrases.txt</code> <strong>Content</strong> The file starts with 400 phrases containing shifter verbs, followed by 2231 phrases containing non-shifter verbs. <strong>Format</strong> Every item consists of: The sentence from which the VP and the polar noun were extracted. The VP, polar noun and the verb heading the VP. Constituency parse for the VP. Gold labels for VP and polar noun by a human annotator. Predicted labels for VP and polar noun by RNTN tagger (Socher et al., 2013) and <code>LEX_gold</code> approach. Items are separated by a line of asterisks (*) <strong>Related Resources</strong> <strong>Paper:</strong> ACL Anthology or DOI: 10.5281/zenodo.3365609 <strong>Presentation:</strong> ACL Anthology <strong>Word Embedding:</strong> DOI: 10.5281/zenodo.3370051 <strong>Attribution</strong> This dataset was created as part of the following publication: Marc Schulder, Michael Wiegand, Josef Ruppenhofer and Benjamin Roth (2017). <strong>"Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features"</strong>. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP). Taipei, Taiwan, November 27 - December 3, 2017. DOI: 10.5281/zenodo.3365609. If you use the data in your research or work, please cite the publication.
description: This work was partially supported by the German Research Foundation (DFG) under grants RU 1873/2-1 and WI4204/2-1.
DOI: 10.5281/zenodo.3364811
title: Bootstrapped Lexicon of English Verbal Polarity Shifters

description: An extended version of this dataset that also covers nominal and adjectival polarity shifters can be found at doi:10.5281/zenodo.3365601. We provide a bootstrapped lexicon of English verbal polarity shifters. Our lexicon covers 3043 verbs of WordNet v3.1 (Miller et al., 1990) that are single word or particle verbs. Polarity shifter labels are given for each word lemma. <strong>Data</strong> The data consists of: Two lists of WordNet verbs (Miller et al., 1990), annotated for whether they cause shifting. The initial gold standard (§2) of 2000 randomly chosen verbs. The bootstrapped 1043 verbs (§5.3) that were labelled as shifters by our best classifier and then manually annotated. Data set of verb phrases from the Amazon Product Review Data corpus (Jindal & Liu, 2008), annotated for polarity of phrase and polar noun. <strong>1. Verbal Shifters</strong> <strong>Files</strong> The initial gold standard: <code>verbal_shifters.gold_standard.txt</code> The bootstrapped verbs: <code>verbal_shifters.bootstrapping.txt</code> <strong>Format</strong> Each line contains a verb and its label, separate by a whitespace. Multiword expressions are separated by an underscore (WORD_WORD). All labels were assigned by an expert annotator. <strong>2. Sentiment Verb Phrases</strong> <strong>Files</strong> All annotated verb phrases: <code>sentiment_phrases.txt</code> <strong>Content</strong> The file starts with 400 phrases containing shifter verbs, followed by 2231 phrases containing non-shifter verbs. <strong>Format</strong> Every item consists of: The sentence from which the VP and the polar noun were extracted. The VP, polar noun and the verb heading the VP. Constituency parse for the VP. Gold labels for VP and polar noun by a human annotator. Predicted labels for VP and polar noun by RNTN tagger (Socher et al., 2013) and <code>LEX_gold</code> approach. Items are separated by a line of asterisks (*) <strong>Related Resources</strong> <strong>Paper:</strong> ACL Anthology or DOI: 10.5281/zenodo.3365609 <strong>Presentation:</strong> ACL Anthology <strong>Word Embedding:</strong> DOI: 10.5281/zenodo.3370051 <strong>Attribution</strong> This dataset was created as part of the following publication: Marc Schulder, Michael Wiegand, Josef Ruppenhofer and Benjamin Roth (2017). <strong>"Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features"</strong>. Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP). Taipei, Taiwan, November 27 - December 3, 2017. DOI: 10.5281/zenodo.3365609. If you use the data in your research or work, please cite the publication.
description: This work was partially supported by the German Research Foundation (DFG) under grants RU 1873/2-1 and WI4204/2-1.
DOI: 10.21227/p66a-gx16
title: Coventry-2018

description: Coventry-2018 is a human activity recognition dataset captured by three Panasonic® Grid-EYE (AMG8833) infrared sensors in March 2018. The Grid-EYE sensors represent a 60 field of view scene by an 8 × 8 array named frame. The data streams are synchronized to 10 frames per second and saved as *.csv recordings using the LabVIEW® software. Two layouts are considered in this dataset with different geometry sizes: 1) small layout; and 2) large layout. The three sensors are located 1.5m from the area of interest in the small geometry size, while the distance grows to 2.5m for the large geometry size as illustrated in the dataset image. The dataset consists of 15 gestures distinguished in two categories: 1) single-subject gestures; and 2) double-subject gestures. There exist eight single-subject activities, and seven double-subject activities. Each single-subject gesture is repeated 10 times by three participants, while for double-subject gestures, the three possible combinations of the three subjects are used and similarly, the gestures are repeated 10 times. It needs to be emphasized that the single-subject activities are conducted in both layouts (small layout and large layout), while the double-subject activities are conducted only in the large layout.