cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6600687
title: mar-file-system/GUFI-Filesystem-Traces: GUFI Filesystem Traces

description: The GUFI Filesystem Traces are a series of formatted text files containing metadata taken from the filesystems of LANL HPC systems. Each line is an entry from the filesystem, containing the entry's name, stat(2) data, link name (if applicable), several filesystem specific fields (unused in these traces), and the entry's pinode. The entry name, link name, uid, and gid fields have been anonymized to preserve privacy. These traces allow for source filesystem trees (without any file contents) to be regenerated in various ways, allowing for experiments with filesystem metadata from real HPC systems without needing access to the real filesystems. yellusers is a scan of the yellow NFS home directory from April 2019. yellprojs is a scan of the yellow NFS projects directory from April 2019. ttscratch and anony are Trinitite user scratch space scans from March 2019 and April 2019, respectively. scr4 is from the yellow Lustre scratch space in June 2020. LA-UR-21-21017
DOI: 10.5281/zenodo.6600686
title: mar-file-system/GUFI-Filesystem-Traces: GUFI Filesystem Traces

description: The GUFI Filesystem Traces are a series of formatted text files containing metadata taken from the filesystems of LANL HPC systems. Each line is an entry from the filesystem, containing the entry's name, stat(2) data, link name (if applicable), several filesystem specific fields (unused in these traces), and the entry's pinode. The entry name, link name, uid, and gid fields have been anonymized to preserve privacy. These traces allow for source filesystem trees (without any file contents) to be regenerated in various ways, allowing for experiments with filesystem metadata from real HPC systems without needing access to the real filesystems. yellusers is a scan of the yellow NFS home directory from April 2019. yellprojs is a scan of the yellow NFS projects directory from April 2019. ttscratch and anony are Trinitite user scratch space scans from March 2019 and April 2019, respectively. scr4 is from the yellow Lustre scratch space in June 2020. LA-UR-21-21017
DOI: 10.6073/pasta/7806dc1c36c2e11430ddee2705199df5
title: Jornada Basin LTER: Wireless meteorological station at NPP G-SUMM site: 1-hour summary data: 2013 - ongoing

description: Hourly summary data at NPP G-SUMM met station. Average/maximum/minimum air temperature; average relative humidity and wind direction; average/maximum wind speed; solar radiation; albedo. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP G-SUMM site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Solar radiation is measured at 3m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.17909/jygk-yg53
title: TESS Target Pixel Files: Sector 27

description: All target pixel files for (2-minute cadence) observations from Sector 27.
DOI: 10.17909/8y4z-qk04
title: TESS Light Curves: Sector 27

description: All light curve files for (2-minute cadence) observations from Sector 27.
DOI: 10.17909/7910-m537
title: TESS Raw Full Frame Images: Sector 27

description: All raw full frame images from Sector 27.
DOI: 10.17909/c6h2-z687
title: TESS Calibrated Full Frame Images: Sector 27

description: All calibrated full frame images from Sector 27.
DOI: 10.17909/4hxw-0338
title: TESS Data Validation Files: Sector 27

description: All data validation files from Sector 27.
DOI: 10.5281/zenodo.6604129
title: Sample ECCOH OH Parameterization

description: A sample parameterization of OH for July created to be used with the ECCOH module of the GEOS Earth System Model. The methodology to generate the parameterization is described in detail in the GMD article "A Machine Learning Methodology for the Generation of a Parameterization of the Hydroxyl Radical". The parameterization is included as an example and should not be used for research purposes without consulting the publication and/or the authors. We have also included the dataset used to train the parameterization (OHParameterization_TrainingSet_1980_2019_M07.dat) as well as the training targets (OHParameterization_Targets_1980_2019_M07.dat). The training data are from the NASA MERRA2 GMI simulation (https://acd-ext.gsfc.nasa.gov/Projects/GEOSCCM/MERRA2GMI/). The scripts used to generate the training dataset and the parameterization can be found at https://zenodo.org/record/6046037.
DOI: 10.6073/pasta/6c4faeedbe4372fb6675b027d959f19a
title: Jornada Basin LTER: Wireless meteorological station at NPP G-SUMM site: 30-minute summary data: 2013 - ongoing

description: 30-minute summary data at NPP G-SUMM met station. Average air temperature, relative humidity, wind speed, wind direction, and solar radiation are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP G-SUMM site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Solar radiation is measured at 3m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.5519/qd.yscy8vih
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (7692 records)
DOI: 10.5519/qd.kzpejcf5
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (14797 records)
DOI: 10.5519/qd.6nw76tg3
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (772 records)
DOI: 10.5519/qd.z6eiwogv
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (7153 records)
DOI: 10.6073/pasta/fb2cb3621b95e821a6075e40572fa8ac
title: Jornada Basin LTER: Wireless meteorological station at NPP G-SUMM site: Daily summary data: 2013 - ongoing

description: Daily summary data at NPP G-SUMM met station. Average/maximum/minimum air temperature; average/maximum relative humidity and wind speed and average wind direction; solar radiation; albedo. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP G-SUMM site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Solar radiation is measured at 3m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.57771/6xrd-nd45
title: iLISTEN dataset
title: iLISTEN

description: The iLISTEN dataset collects 60 dialogue transcripts (about 22,000 words) annotated for the speech act of each turn. The dialogues were collected using a Wizard of Oz tool as dialogue manager and involved sixty subjects (aged between 21–28).<p>The dataset has been used in the context of the iLISTEN task (https://ilisten2018.github.io), organised as part of EVALITA 2018 (http://www.evalita.it/2018). It is split into a development and a test data set, containing 40 and 20 dialogues, respectively.
DOI: 10.13026/wn66-m424
title: A Wearable Exam Stress Dataset for Predicting Cognitive Performance in Real-World Settings

description: Preliminary datasets containing skin conductance recordings where experiments
involve artificial stimuli are available online. However, recordings of a
longer duration acquired during real-world cognitive stressors are lacking
significantly. This dataset seeks to bridge the gap between a body of
knowledge concerning the human stress response primarily built up on
laboratory acquired data, and how people's skin conductance fluctuates in
reality when they undergo a stressful exam experience. The data contains
**electrodermal activity** , **heart rate** , **blood volume pulse** , **skin
surface temperature** , **inter beat interval** and **accelerometer data**
recorded during **three exam sessions** (midterm 1, midterm 2 and  finals) as
well as their corresponding grades. The purpose of this dataset is to gauge
the influence of stress on exam performance.
DOI: 10.13026/kvkb-aj90
title: A Wearable Exam Stress Dataset for Predicting Cognitive Performance in Real-World Settings

description: Preliminary datasets containing skin conductance recordings where experiments
involve artificial stimuli are available online. However, recordings of a
longer duration acquired during real-world cognitive stressors are lacking
significantly. This dataset seeks to bridge the gap between a body of
knowledge concerning the human stress response primarily built up on
laboratory acquired data, and how people's skin conductance fluctuates in
reality when they undergo a stressful exam experience. The data contains
**electrodermal activity** , **heart rate** , **blood volume pulse** , **skin
surface temperature** , **inter beat interval** and **accelerometer data**
recorded during **three exam sessions** (midterm 1, midterm 2 and  finals) as
well as their corresponding grades. The purpose of this dataset is to gauge
the influence of stress on exam performance.
DOI: 10.6084/m9.figshare.19952822
title: AppendixA.xlsx

description: Metadata for song recordings used
DOI: 10.6084/m9.figshare.19952822.v1
title: AppendixA.xlsx

description: Metadata for song recordings used
DOI: 10.17909/srcz-2b67
title: A Wide-Field WFC3 Imaging Survey with Grism Spectroscopy in the COSMOS Field ("3D-DASH")

description: The 3D-Drift And SHift (3D-DASH) program is a Hubble Space Telescope WFC3 F160W imaging and G141 grism survey of the equatorial COSMOS field. 3D-DASH is the widest HST/WFC3 imaging survey in the F160W filter to date, subsuming the COSMOS-DASH pilot survey. 3D-DASH extends the legacy of HST near-infrared imaging and spectroscopy to degree-scale swaths of the sky, enabling the identification and study of distant galaxies (z > 2) that are rare or in short-lived phases of galaxy evolution at rest-frame optical wavelengths.
DOI: 10.6073/pasta/568fbbdae3724fa99b2cf81b0ddca805
title: Jornada Basin LTER: Wireless meteorological station at NPP M-NORT site: 5-minute summary air temperature data: 2013 - ongoing

description: 5-minute summary data at NPP M-NORT met station. Average air temperature measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP M-NORT site. Air temperature is measured at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.57771/2549-sm04
title: IronITA
title: IronITA

description: The IronITA dataset collects 4,849 tweets annotated for irony and sarcasm. The dataset has been used in the IroniTA task (http://www.di.unito.it/~tutreeb/ironita-evalita18), organised as part of EVALITA 2018 (http://www.evalita.it/2018). <p>The dataset is divided into training and test data, constituted of respectively 3,977 and 872 tweets. In order to comply with GDPR privacy rules and Twitter’s policies, the identifiers of tweets and users have been anonymized and replaced by unique identifiers.
DOI: 10.57771/9erf-2417
title: ITAmoji dataset
title: ITAmoji

description: The ITAmoji dataset collects 275, 000 tweets that contain one and only one emoji over the 25 most frequent emojis. The dataset has been created and used in the context of the ITAmoji task (https://sites.google.com/view/itamoji/), organised as part of EVALITA 2018(http://www.evalita.it/2018). The task challenged participants to develop automatic systems that predict, given an Italian tweet, its most likely associ- ated emoji, selected in a wide and heterogeneous emoji space. The dataset is split into training set (250,000 tweets) and test set (25,000 tweets).<p>In order to comply with GDPR privacy rules and Twitter’s policies, the identifiers of tweets and users have been anonymized and replaced by unique identifiers.  <p>
DOI: 10.57771/yfdt-xg68
title: Khresmoi manually annotated reference corpus
title: Corpus de référence annoté manuellement Khresmoi

description: The Manually Annotated Reference Corpus is a collection of English web documents annotated with key entities (such as disease, drug), built in the framework of the Khresmoi project, funded by the European Commission. It has been constructed by first annotating these entities with an imperfect automatic process through GATE pipelines. Then, automatic annotations have been corrected by several human operators. The differences between these human operators were resolved to give the final reference corpus. <p><p>The corpus is divided into two parts:<p>1. The initial corpus: 625 documents from the Genetics Home Reference data set, automatically annotated with anatomical locations and diseases, and manually corrected by 3-4 annotators. Size of documents: between 26 and 8,306 tokens each. <p>2. The main corpus: 6,950 English documents from the Khresmoi crawl and 5,518 English Wikipedia pages, automatically annotated through the GATE Platform for Anatomy, Disease, Drug and Investigation. Size of documents: between 200 and 2,000 tokens each. Of these, 1,783 documents have been manually corrected by up to 7 people, to give 68,799 agreed consensus annotations. <p><p>The corpus is using the GATE XML format.
description: Le corpus de référence annoté manuellement est une collection de documents web en anglais annotés en entités-clés (telles que maladie, médication), réalisée dans le cadre du projet Khresmoi, financé par la Commission européenne. Il a été construit d’abord en annotant ces entités avec un procédé automatique imparfait via le réseau GATE. Puis, les annotations automatiques ont été corrigées par plusieurs opérateurs humains. Les différences entre les opérateurs humains ont été résolues afin d’offrir un corpus de référence final. 

Le corpus se divise en deux parties:
1. Le corpus initial: 625 documents provenant de l’ensemble de données Genetics Home Reference, annoté automatiquement avec les emplacements anatomiques et les maladies, et corrigé manuellement par 3-4 annotateurs. Taille des documents: entre 26 et 8,306 tokens par document. 
2. Le corpus principal: 6,950 documents provenant de données crawlées dans Khresmoi et  5,518 pages Wikipedia, annotées automatiquement via la plate-forme GATE dédiée à l’anatomie, la maladie, la médication et l’investigation. Taille des documents: entre 200 et 2,000 tokens par document. A partir de cela, 1,783 documents ont été corrigés manuellement par un maximum de 7 personnes, pour offrir 68,799 annotations agréées par consensus. 

Le corpus utilise le format XML GATE.
DOI: 10.57771/4vtq-n730
title: KIPoS corpus
title: KIPoS

description: The KIPoS corpus provides data extracted from the KIParla spoken corpus of Italian (www.kiparla.it) and manually annotated with Part of Speech tags. The dataset consists of approximately 200K tokens, with an equal proportion of informal and formal speech. It has been used as dataset for the KIPoS task (http://www.di.unito.it/~tutreeb/kipos-evalita2020/) during the EVALITA 2020 evaluation campaign (http://www.evalita.it/2020).
DOI: 10.57771/e7z1-ry47
title: Lexical Substitution Task Test Set 

description: The Lexical Substitution Task Test Set comprehends the test set and the gold labels used in the Lexical Substitution Task (https://www.evalita.it/2009/tasks/lexical), organised as part of the  EVALITA 2009 evaluation campaign (http://www.evalita.it/2009). The task challenged participants to build systems that could automatically find synonyms for a set of 231 words appearing in different contexts.<p>The data set contains 1710 sentences  extracted from the Italian Syntactic Semantic Treebank (ISST) in which the target words occur and a list of the synonyms (manually annotated), that constitute the gold labels. <p>
DOI: 10.6073/pasta/878f8664ef752c6504e73b6b100b6f29
title: Jornada Basin LTER: Wireless meteorological station at NPP M-NORT site: 1-hour summary data: 2013 - ongoing

description: Hourly summary data at NPP M-NORT met station. Average/maximum/minimum air temperature; average relative humidity. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP M-NORT site. Air temperature and relative humidity are measured at approximately 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.57771/fatk-5n22
title: Mbochi speech corpus
title: Corpus oral mbochi

description: The Mbochi speech corpus was developed in the framework of ANR-DFG BULB project. This project aims to provide field linguists (eg working on morphology) with tools for less or not written languages. The provided corpus is a subset from the corpus developed in this framework.<p><p>The provided corpus consists of 5131 sentences recorded in mbochi, together with their transcription and French translation, as well as the results from the work made during  JSALT workshop (within one of the topics which was "the speaking Rosetta stone - Discovering Grounded Linguistic Units for Languages without Orthography"): alignments at the phonetic level and various results of unsupervised word segmentation from audio. The audio corpus is made up of 4,5 hours, downsampled at 16kHz, 16bits, with Linear PCM encoding. Data is distributed into 2 parts, one for training consisting of 4617 sentences, and one for development consisting of 514 sentences.
description: Le corpus oral mbochi a été développé dans le cadre du projet ANR-DFG BULB. Ce projet a pour but de fournir des outils pour les linguistes de terrain pour des langues peu ou pas écrites, par exemple en découverte de la morphologie. Le corpus fourni est une partie du corpus développé dans ce cadre.

Le corpus fourni comprend 5131 phrases enregistrées en mbochi avec leur transcription, et leur traduction en français, ainsi que le résultat du travail réalisé pendant le workshop JSALT (dont l’un des sujets était "the speaking Rosetta stone - Discovering Grounded Linguistic Units for Languages without Orthography"): alignements au niveau phonétique, et divers résultats de segmentation en mots non supervisée à partir de l'audio. Le corpus audio contient 4,5 heures, échantillonnées à 16kHz, 16bits, avec codage Linear PCM. Les données sont séparées en 2 parties, une pour l'apprentissage (train) contenant 4617 phrases, et une pour le développement (dev) contenant 514 phrases.
DOI: 10.57771/pkjw-8p49
title: MCL - Multifunctional Computational Lexicon of Contemporary Portuguese
title: MCL- Lexique informatique multifonctionnel du portugais contemporain

description: MCL is a 26,443 lemma Frequency Lexicon with 140,315 tokens, with the minimum lemma frequency of 6, extracted from CORLEX, a contemporary Portuguese corpus (16,210,438 words). CORLEX is a subcorpus of the Reference Corpus of Contemporary Portuguese and contains written and spoken texts of several types, being genre diversity a characteristic of this corpus. CORLEX contains mainly journalistic texts (56% of the written corpus and 53% of the whole corpus). In order to extract the lexicon, all the different lexical forms occurring in the corpus were indexed and subsequently tagged morphosyntactically and lemmatised by PALAVROSO.<p><p>Each lemma in MCL is followed by morphosyntactic and quantitative information. The same information is given regarding each lemma token (inflected forms and some compounds). The lexicon indexations are listed in alphabetical order or decreasing frequency order.
description: MCL est un lexique de fréquences de lemmes qui contient 140,315 mots, avec une fréquence minimale d’apparition égale à 6. Le lexique a été extrait de CORLEX, un corpus du portugais contemporain (16,210,438 mots). CORLEX est un sous-corpus du Corpus de Référence du Portugais Contemporain, lequel comprend plusieurs types de textes. CORLEX comprend principalement des textes journalistiques (56% du corpus écrit et 53% du corpus total). Afin d'extraire le lexique, toutes les formes lexicales dans le corpus ont été indexées et ensuite étiquetées et lemmatisées avec PALAVROSO.

Chaque lemme dans MCL est suivi d'informations morphosyntaxiques et quantitatives. Ces informations sont aussi fournies pour les formes fléchies et pour certains mots composés. Les indexations du lexique sont listées alphabétiquement ou par ordre décroissant des fréquences.
DOI: 10.57771/p2n7-f015
title: MIC21 image dataset
title: MIC21 dataset

description: <p>The <strong>Multilingual Image Corpus</strong> provides fully annotated objects within images with segmentation masks, classified according to an Ontology of Visual Objects, thus offering data to train models specialised in object detection, segmentation and classification. </p><p>The Ontology of visual objects allows easy integration of annotated images in different datasets as well as learning the associations between objects in images. </p><p>The Ontology classes are translated into 25 languages and supplied with definitions and usage examples. The explicit association of objects and images with appropriate text fragments is relevant for multilingual image caption generation, image-to-text alignment and automatic question answering for images and video. </p>
DOI: 10.57771/a0w5-8480
title: MIC21 ontology of visual objects

description: The Ontology contains classes (706 representing visual objects and 147 representing their hypernyms), relations and axioms. Classes correspond (but are not limited) to WordNet concepts which can be represented by visual objects. Part of the relations and their properties are also inherited from WordNet. Axioms serve to model statements that are always true. A separate resource is available with the translations of the classes into 25 languages. 
		The Ontology of visual objects allows easy integration of annotated images in different datasets as well as learning the associations between objects in images and can be used for tasks such as multilingual image caption generation, image-to-text alignment and automatic question answering for images and video. 
		The ontology has been used for the annotation of the MIC21 Multilingual image corpus. <p></p>
DOI: 10.57771/zwa3-kf02
title: Multi-Language Vocabulary Evaluation Data Set
title: MuLVE

description: <p>Multi-Language Vocabulary Evaluation Data Set (MuLVE) is a data set consisting of vocabulary cards and real-life user answers, labeled whether the user answer is correct or incorrect. The data's source is user learning data from the Phase6 vocabulary trainer. The data set contains vocabulary questions in German and English, Spanish, and French as target language and is available in four different variations regarding pre-processing and deduplication.</p><p> </p><p>It is split up into four tab-separated files, one for each variation, per train and test set. The files include the following columns:</p><ul><li>cardId - numeric card ID</li><li>question - vocabulary card question</li><li>answer - vocabulary card answer</li><li>userAnswer - answer the user input</li><li>Label - True if user answer is correct, False if not</li><li>language - target language (English, French or Spanish)</li></ul><p>The processed data set variations do not include the include \textbf{userAnswer} columns but the following additional columns:</p><ul><li>question_norm - question normalized</li><li>answer_norm - answer normalized</li><li>userAnswer_norm - user answer normalized<br> </li></ul>