cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5036977
title: CommonLanguage

description: <pre><strong>CommonLanguage Dataset </strong> This dataset is composed of speech recordings from of languages that were carefully selected from the CommonVoice database. The total duration of audio recordings is 45.1 hours (i.e., 1 hour of material for each language). The dataset is already balanced and split into train, dev (validation) and test sets. The dataset has been extracted from CommonVoice to train easily language-id systems. The baselines for language-id are available in the SpeechBrain toolkit (see recipes/CommonLanguage): https://github.com/speechbrain/speechbrain <strong>Statistics of CommonLanguage:</strong> | Name | Train | Dev | Test | |:---------------------------------:|:------:|:------:|:-----:| | **# of utterances** | 177552 | 47104 | 47704 | | **# unique speakers** | 11189 | 1297 | 1322 | | **Total duration, hr** | 30.04 | 7.53 | 7.53 | | **Min duration, sec** | 0.86 | 0.98 | 0.89 | | **Mean duration, sec** | 4.87 | 4.61 | 4.55 | | **Max duration, sec** | 21.72 | 105.67 | 29.83 | | **Duration per language, min** | ~40 | ~10 | ~10 | ## List of languages: * Arabic * Basque * Breton * Catalan * Chinese_China * Chinese_Hongkong * Chinese_Taiwan * Chuvash * Czech * Dhivehi * Dutch * English * Esperanto * Estonian * French * Frisian * Georgian * German * Greek * Hakha_Chin * Indonesian * Interlingua * Italian * Japanese * Kabyle * Kinyarwanda * Kyrgyz * Latvian * Maltese * Mangolian * Persian * Polish * Portuguese * Romanian * Romansh_Sursilvan * Russian * Sakha * Slovenian * Spanish * Swedish * Tamil * Tatar * Turkish * Ukranian * Welsh ## Other information In addition to the language label, the datapoints have `age`, `gender` and `utterance transcription` associated with each utterance.</pre>
description: {"references": ["Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and Fran\u00e7ois Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio, \"SpeechBrain: A General-Purpose Speech Toolkit\", 2021, arXiv"]}
DOI: 10.5281/zenodo.5036976
title: CommonLanguage

description: <pre><strong>CommonLanguage Dataset </strong> This dataset is composed of speech recordings from of languages that were carefully selected from the CommonVoice database. The total duration of audio recordings is 45.1 hours (i.e., 1 hour of material for each language). The dataset is already balanced and split into train, dev (validation) and test sets. The dataset has been extracted from CommonVoice to train easily language-id systems. The baselines for language-id are available in the SpeechBrain toolkit (see recipes/CommonLanguage): https://github.com/speechbrain/speechbrain <strong>Statistics of CommonLanguage:</strong> | Name | Train | Dev | Test | |:---------------------------------:|:------:|:------:|:-----:| | **# of utterances** | 177552 | 47104 | 47704 | | **# unique speakers** | 11189 | 1297 | 1322 | | **Total duration, hr** | 30.04 | 7.53 | 7.53 | | **Min duration, sec** | 0.86 | 0.98 | 0.89 | | **Mean duration, sec** | 4.87 | 4.61 | 4.55 | | **Max duration, sec** | 21.72 | 105.67 | 29.83 | | **Duration per language, min** | ~40 | ~10 | ~10 | ## List of languages: * Arabic * Basque * Breton * Catalan * Chinese_China * Chinese_Hongkong * Chinese_Taiwan * Chuvash * Czech * Dhivehi * Dutch * English * Esperanto * Estonian * French * Frisian * Georgian * German * Greek * Hakha_Chin * Indonesian * Interlingua * Italian * Japanese * Kabyle * Kinyarwanda * Kyrgyz * Latvian * Maltese * Mangolian * Persian * Polish * Portuguese * Romanian * Romansh_Sursilvan * Russian * Sakha * Slovenian * Spanish * Swedish * Tamil * Tatar * Turkish * Ukranian * Welsh ## Other information In addition to the language label, the datapoints have `age`, `gender` and `utterance transcription` associated with each utterance.</pre>
description: {"references": ["Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and Fran\u00e7ois Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio, \"SpeechBrain: A General-Purpose Speech Toolkit\", 2021, arXiv"]}
DOI: 10.6084/m9.figshare.14758590.v1
title: LEAP_EcoPlateBiolog_rawdata

description: Optical densities of all substrates present in the EcoPlate (individually and grouped by guild) at each sample of the LEAP 2016 experiment.
DOI: 10.6084/m9.figshare.14758590
title: LEAP_EcoPlateBiolog_rawdata

description: Optical densities of all substrates present in the EcoPlate (individually and grouped by guild) at each sample of the LEAP 2016 experiment.
DOI: 10.5281/zenodo.5037552
title: The Open Khipu Repository

description: <strong>Release v1.0.0</strong> This open-source digital repository stores the most up-to-date data and metadata on extant Inka-style khipus from archaeological sites in the Andes, as well as museums around the world. Inka khipus were unique pre-Columbian, Andean recording devices that used three-dimensional signs -- primarily knots, cords, and colors -- as symbols functionally akin to those of early writing systems in other cultures. Spanish chronicles, as well as contemporary khipu studies indicate that the Inka used khipus to record everything from accounting records to historical narratives. The khipu recording system remains undeciphered, however. The purpose of this repository is to enable computational khipu research and Inka khipu decipherment efforts. Currently, data is stored in a serverless SQLite relational database (khipu.db) that contains all known khipu data recorded and published by major Inka khipu scholars: Robert and Marcia Ascher, Hugo Pereyra, Harvard's Khipu Database Project (Carrie Brezine and Gary Urton), and Jon Clindaniel. This repository is currently being developed and maintained as a part of the Open Khipu Research Laboratory under the direction of Jon Clindaniel (jclindaniel@uchicago.edu). It currently includes all Inka khipus recorded through 09/2018 (v1.0.0). The data in the repository will be updated as more khipus become available for study.
DOI: 10.18112/openneuro.ds003709.v1.0.0
title: NIMH-CompyPsych MMI
DOI: 10.6073/pasta/e86fe2ad143a5b7b6ae9fccee5de23fc
title: Modeling Foundation Species in Food Webs

description: Foundation species are basal species that play an important role in determining community composition by physically structuring ecosystems and modulating ecosystem processes. Foundation species largely operate via non-trophic interactions, presenting a challenge to incorporating them into food-web models. Here, we used non-linear, bioenergetic predator-prey models to explore the role of foundation species and their non-trophic effects. We explored four types of models in which the foundation species reduced the metabolic rates of species in a specific trophic position. We examined the outcomes of each of these models for six metabolic rate “treatments” in which the foundation species altered the metabolic rates of associated species by one-tenth to ten times their allometric baseline metabolic rates. For each model simulation, we looked at how foundation species influenced food-web structure during community assembly and the subsequent change in food-web structure when the foundation species was removed. When a foundation species lowered the metabolic rate of only basal species the resultant webs were complex, species-rich, and robust to foundation species removals. On the other hand, when a foundation species lowered the metabolic rate of only consumer species, all species, or no species the resultant webs were species poor and the subsequent removal of the foundation species webs resulted in the further loss of species and complexity. This suggests that in nature we should look for foundation species to predominantly facilitate basal species.
DOI: 10.15468/cgzpdc
title: A revision of the water beetle genus Hydraena Kugelann for southern Africa (Coleoptera: Hydraenidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article PERKINS, PHILIP D. (2014): A revision of the water beetle genus Hydraena Kugelann for southern Africa (Coleoptera: Hydraenidae). Zootaxa 3758 (1): 1-92, DOI: http://dx.doi.org/10.11646/zootaxa.3758.1.1, URL: http://dx.doi.org/10.11646/zootaxa.3758.1.1
DOI: 10.6084/m9.figshare.14787420
title: Whitt 2021 LES paper, Data for plotting MITgcm results, updated June 28 2021

description: Regional ocean model output necessary for plotting figures in manuscript of Whitt et al. (2021).<br>Updated June 28, 2021.
DOI: 10.6084/m9.figshare.14787420.v1
title: Whitt 2021 LES paper, Data for plotting MITgcm results

description: Regional ocean model output necessary for plotting figures in manuscript of Whitt et al. (2021).
DOI: 10.5517/ccdc.csd.cc26nt3t
title: CCDC 2045786: Experimental Crystal Structure Determination

description: Related Article: Nour Dissem, Mohamed Essalhi, Najmeddine Ferhi, Adela Abidi, Thierry Maris, Adam Duong|2021|Dalton Trans.|50|8727|doi:10.1039/D1DT00426C
DOI: 10.5517/ccdc.csd.cc26nt4v
title: CCDC 2045787: Experimental Crystal Structure Determination

description: Related Article: Nour Dissem, Mohamed Essalhi, Najmeddine Ferhi, Adela Abidi, Thierry Maris, Adam Duong|2021|Dalton Trans.|50|8727|doi:10.1039/D1DT00426C
DOI: 10.5517/ccdc.csd.cc26nt5w
title: CCDC 2045788: Experimental Crystal Structure Determination

description: Related Article: Nour Dissem, Mohamed Essalhi, Najmeddine Ferhi, Adela Abidi, Thierry Maris, Adam Duong|2021|Dalton Trans.|50|8727|doi:10.1039/D1DT00426C
DOI: 10.5517/ccdc.csd.cc26nt6x
title: CCDC 2045789: Experimental Crystal Structure Determination

description: Related Article: Nour Dissem, Mohamed Essalhi, Najmeddine Ferhi, Adela Abidi, Thierry Maris, Adam Duong|2021|Dalton Trans.|50|8727|doi:10.1039/D1DT00426C
DOI: 10.5517/ccdc.csd.cc26nt7y
title: CCDC 2045790: Experimental Crystal Structure Determination

description: Related Article: Nour Dissem, Mohamed Essalhi, Najmeddine Ferhi, Adela Abidi, Thierry Maris, Adam Duong|2021|Dalton Trans.|50|8727|doi:10.1039/D1DT00426C
DOI: 10.5517/ccdc.csd.cc26nt8z
title: CCDC 2045791: Experimental Crystal Structure Determination

description: Related Article: Nour Dissem, Mohamed Essalhi, Najmeddine Ferhi, Adela Abidi, Thierry Maris, Adam Duong|2021|Dalton Trans.|50|8727|doi:10.1039/D1DT00426C
DOI: 10.5517/ccdc.csd.cc26pmj2
title: CCDC 2046574: Experimental Crystal Structure Determination

description: Related Article: Xiaoyi Zhu, Ruibo Li, Hequan Yao, Aijun Lin|2021|Org.Lett.|23|4630|doi:10.1021/acs.orglett.1c01369
DOI: 10.5517/ccdc.csd.cc26r9bm
title: CCDC 2048180: Experimental Crystal Structure Determination

description: Related Article: Behrouz Notash, Mona Farhadi Rodbari, Gianpiero Gallo, Robert Dinnebier|2021|Inorg.Chem.|60|9212|doi:10.1021/acs.inorgchem.1c01360
DOI: 10.5517/ccdc.csd.cc26xz9f
title: CCDC 2053635: Experimental Crystal Structure Determination

description: Related Article: Shingo Masahara, Hiromichi Yokoyama, Yuji Suzaki, Tomohito Ide|2021|Dalton Trans.|50|8889|doi:10.1039/D1DT01571K
DOI: 10.5517/ccdc.csd.cc273rx1
title: CCDC 2059203: Experimental Crystal Structure Determination

description: Related Article: Richard Holzner, Amelie Porzelt, Uhut S. Karaca, Fiona Kiefer, Philipp Frisch, Daniel Wendel, Max C. Holthausen, Shigeyoshi Inoue|2021|Dalton Trans.|50|8785|doi:10.1039/D1DT01629F
DOI: 10.5517/ccdc.csd.cc273ry2
title: CCDC 2059204: Experimental Crystal Structure Determination

description: Related Article: Richard Holzner, Amelie Porzelt, Uhut S. Karaca, Fiona Kiefer, Philipp Frisch, Daniel Wendel, Max C. Holthausen, Shigeyoshi Inoue|2021|Dalton Trans.|50|8785|doi:10.1039/D1DT01629F
DOI: 10.6073/pasta/1622fee307532af343d8491b73004ff1
title: Radiocarbon Measurements at Harvard Forest 1996-2010

description: Long-term datasets on soil C stocks, radiocarbon content, and CO2 efflux from the Harvard forest, MA were applied to the ForCent model to examine soil C dynamics over long term timescales and under warming and nitrogen amendments. The objective was to determine if manipulations of soil temperature and nitrogen supply affect the relative age of respired soil C substrates. Heating of the soil increased decomposition of all soil C pools, the absolute amount of increased decomposition from the older pools was not large enough to make a difference in 14C composition of respired C from model results. Further the high spatial variation observed in 14C from temperature and nitrogen amendments made it difficult to detect changes in respired C sources over this short a study period.
DOI: 10.3886/e135801v1-90382
title: The Women on High Courts Database

description: This study provides over-time and cross-national data on women on high courts. The dataset includes information on the year the first woman was appointed and the gender composition of the high court. High courts include single peak courts as found in many common law countries and constitutional courts and highest appellate courts as found in many civil law countries. Information on the year of the first woman spans the period, 1945 to 2020. Data coverage on the number and percentage of women on high courts starts in 1970 or when the court is created, whichever comes first. Countries included have a population of 200,000 or greater. The data were compiled by the authors and their research teams drawing on a combination of secondary sources and information from countries' courts and judges. <br>
description: The sample includes country high courts in sovereign countries with a population of 200,000 or greater (in 2010). <br><br>For the year the first woman was appointed, the sample includes 210 country high courts between 1946 and 2020.<br><br>The data on the number and percentage of women on high courts is an unbalanced cross-national time-series between 1970 and 2013. In Version 1.0 of our dataset, we have 5,675 observations for the number of women on high courts (63.2% coverage) and 5,655 observations on the percentage of women on high courts (63.0%).<br><br>For more information on the sample, please consult the Appendix 1 of Escobar-Lemmon, Maria C., Valerie J. Hoekstra, Alice J. Kang, and Miki Caul Kittilson. Reimagining the Judiciary: Women’s Representation on High Courts Worldwide. Oxford, UK.: Oxford University Press, 2021.<br>
description: Country high courts in independent countries with a population greater than 200,000. Smallest Geographic Unit: country
DOI: 10.6084/m9.figshare.14867190.v1
title: Parental Cognitive Apprenticeship in a History Museum Item

description: This data involve sets of citations of interactions between a parent and his/her child while visiting a history museum. The analysis of the data yielded 39 parental activity – types classified into three core themes: museum conduct & learning, museum's characteristics and museum's content. This evidence constituted a basis for elaborating on the framework of cognitive apprenticeship.
DOI: 10.6084/m9.figshare.14867190
title: Parental Cognitive Apprenticeship in a History Museum Item

description: This data involve sets of citations of interactions between a parent and his/her child while visiting a history museum. The analysis of the data yielded 39 parental activity – types classified into three core themes: museum conduct & learning, museum's characteristics and museum's content. This evidence constituted a basis for elaborating on the framework of cognitive apprenticeship.
DOI: 10.6073/pasta/22a1daf1577df37ba49770e56b6b9de6
title: Forest Inventory for Tree Demography and Carbohydrate Reserves at Harvard Forest 2009-2011

description: The objective of this study is to establish a network of forest plots spanning the eastern U.S. focused on understanding how regional scale climate patterns affect patterns of tree demography (e.g. growth, mortality, dieback). Within each research site we also aim to understand the landscape-scale variability in demographic rates and how these rates are affected by edaphic variables by aligning plots along primary environmental gradients (elevation, soils, hydrology, fire return interval). The demographic data obtained will also be compared to regional and landscape-scale patterns in carbon reserves in adults and sapling by sampling root and stem concentrations of nonstructural carbohydrates (TNC) and relate these to demographic patterns, life-history traits, and plant C:N ratios. Besides addressing important ecological questions directly, this study is designed to improve the representations of vegetation dynamics and carbohydrate reserves in regional and landscape-scale forest ecosystem models--two of the least data-constrained processes in such models--by parameterizing and validating the modules for these processes in the Ecosystem Demography model (ED v2.1). This data set contains two years of census data for eight mapped plots distributed across Harvard Forest along the aforementioned primary environmental gradients.
DOI: 10.5281/zenodo.4903340
title: Global CHIRPS MCWD (Maximum Cumulative Water Deficit) Dataset

description: <strong>Global CHIRPS MCWD Dataset</strong> The MCWD (Maximum Cumulative Water Deficit) is a measure of drought severity, which corresponds to the maximum value of the monthly accumulated water deficit reached for each pixel within the year. The MCWD is a useful indicator of meteorologically induced water stress without taking into account local soil conditions and plant adaptations, which are poorly understood in Amazonia. The full method of MCWD is described in Aragão et al. (2007; https://doi.org/10.1029/2006GL028946). Detail about CHIRPS (Rainfall Estimates from Rain Gauge and Satellite Observations) can be found in Funk et al. (2015; https://doi.org/10.1038/sdata.2015.66). <strong>Coverage:</strong> Spanning 50°S-50°N (and all longitudes/land areas) <strong>Period:</strong> 1981 to 2020 <strong>Spatial resolution:</strong> 0.05-degree <strong>Temporal resolution:</strong> Annual <strong>Coordinate reference system:</strong> Geographic Coordinate System (Datum WGS84) <strong>File format:</strong> The zip file containing 40 files (one per year) in compressed TIFF format. <strong>Code:</strong> https://zenodo.org/record/5034650 <strong>Dataset usage</strong>: It is free to use, but if you use this dataset in your work, please make sure to cite the repository and our paper properly. We also welcome users to invite us for collaboration. <strong>For the use of this dataset, please cite:</strong> Silva Junior, C.H.L. et al. Global CHIRPS MCWD (Maximum Cumulative Water Deficit) Dataset. <em>Zenodo</em> (2021). DOI: 10.5281/zenodo.4903340. https://doi.org/10.5281/zenodo.4903340 Silva Junior, C.H.L. et al. Fire Responses to the 2010 and 2015/2016 Amazonian Droughts. <em>Front. Earth Sci</em>. (2019). DOI: 10.3389/feart.2019.00097. https://doi.org/10.3389/feart.2019.00097 Funk, C. et al. The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. <em>Scientific Data</em> (2015). DOI: 10.1038/sdata.2015.66. https://doi.org/10.1038/sdata.2015.66
DOI: 10.5281/zenodo.4903339
title: Global CHIRPS MCWD (Maximum Cumulative Water Deficit) Dataset

description: <strong>Global CHIRPS MCWD Dataset</strong> The MCWD (Maximum Cumulative Water Deficit) is a measure of drought severity, which corresponds to the maximum value of the monthly accumulated water deficit reached for each pixel within the year. The MCWD is a useful indicator of meteorologically induced water stress without taking into account local soil conditions and plant adaptations, which are poorly understood in Amazonia. The full method of MCWD is described in Aragão et al. (2007; https://doi.org/10.1029/2006GL028946). Detail about CHIRPS (Rainfall Estimates from Rain Gauge and Satellite Observations) can be found in Funk et al. (2015; https://doi.org/10.1038/sdata.2015.66). <strong>Coverage:</strong> Spanning 50°S-50°N (and all longitudes/land areas) <strong>Period:</strong> 1981 to 2020 <strong>Spatial resolution:</strong> 0.05-degree <strong>Temporal resolution:</strong> Annual <strong>Coordinate reference system:</strong> Geographic Coordinate System (Datum WGS84) <strong>File format:</strong> The zip file containing 40 files (one per year) in compressed TIFF format. <strong>Code:</strong> https://zenodo.org/record/5034650 <strong>Dataset usage</strong>: It is free to use, but if you use this dataset in your work, please make sure to cite the repository and our paper properly. We also welcome users to invite us for collaboration. <strong>For the use of this dataset, please cite:</strong> Silva Junior, C.H.L. et al. Global CHIRPS MCWD (Maximum Cumulative Water Deficit) Dataset. <em>Zenodo</em> (2021). DOI: 10.5281/zenodo.4903340. https://doi.org/10.5281/zenodo.4903340 Silva Junior, C.H.L. et al. Fire Responses to the 2010 and 2015/2016 Amazonian Droughts. <em>Front. Earth Sci</em>. (2019). DOI: 10.3389/feart.2019.00097. https://doi.org/10.3389/feart.2019.00097 Funk, C. et al. The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. <em>Scientific Data</em> (2015). DOI: 10.1038/sdata.2015.66. https://doi.org/10.1038/sdata.2015.66
DOI: 10.7284/129006
title: Splitbeam Echosounder data collected during research cruise AR25 using a Kongsberg EK80 instrument system onboard the platform RV Neil Armstrong

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141088
title: Splitbeam Echosounder data collected during research cruise AR49 using a Kongsberg EK80 instrument system onboard the platform RV Neil Armstrong

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142321
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise AR52-A using a Hawaii UHDAS instrument system onboard the platform RV Neil Armstrong

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142331
title: Multiplexed data collected during research cruise AR52-A using a WHOI dsLog gyro instrument system onboard the platform RV Neil Armstrong

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142335
title: Flowmeter data collected during research cruise AR52-A using a Thiel Thiel Flowmeter instrument system onboard the platform RV Neil Armstrong

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/142314
title: Fluorometer data collected during research cruise AR52-A using a WET Labs WETStar instrument system onboard the platform RV Neil Armstrong

description: Original (unprocessed) data collected during a Field_expedition