cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3711403
title: Mapping the Local Spatial Charge in Defective Diamond by Means of N-V Sensors—A Self-Diagnostic Concept

description: Mapping the Local Spatial Charge in Defective Diamond by Means of N-V Sensors—A Self-Diagnostic Concept Electrically active defects have a significant impact on the performance of electronic devices based on wide-band-gap materials. This issue is ubiquitous in diamond science and technology, since the presence of charge traps in the active regions of different classes of diamond-based devices (detectors, power diodes, transistors) can significantly affect their performance, due to the formation of space charge, memory effects, and the degradation of the electronic response associated with radiation-induced damage. Among the most common defects in diamond, the nitrogen-vacancy (N-V) center possesses unique spin properties that enable high-sensitivity field sensing at the nanoscale. Here, we demonstrate that N-V ensembles can be successfully exploited to perform direct local mapping of the internal electric-field distribution of a graphite-diamond-graphite junction exhibiting electrical properties dominated by trap- and space-charge-related conduction mechanisms. By means of optically detected magnetic resonance measurements, we performed both point-by-point readout and spatial mapping of the electric field in the active region at different bias voltages. In this novel “self-diagnostic” approach, defect complexes represent not only the source of detrimental space-charge effects but also a unique tool for their direct investigation, by providing an insight on the conduction mechanisms that could not be inferred in previous studies on the basis of conventional electrical and optical characterization techniques.
description: This work was supported by the Joint Research Project SIQUST (17FUN06). This project received funding from the European Metrology Programme for Innovation and Research (EMPIR) cofinanced by the Participating States and from the European Unions Horizon 2020 research and innovation programme.
DOI: 10.5281/zenodo.3711602
title: Supplemental information for "Creating thin magnetic layers at the surface of 2 Sb2Te3 topological insulators using a low-energy chromium ion beam"

description: A test upload of the data repository to Zenodo
description: This dataset is the Monte Carlo dose calculation of the Cr-40 keV ions stopping in Sb2Te3.
DOI: 10.3886/e118261v1
title: Inflation Targeting in Emerging Market Economies

description: In this project, we investigate the macroeconomic effects of inflation targeting in 44 emerging market economies (EMEs) during 1970-2017. Specifically, we explore the following issues: the effects of inflation targeting on output and inflation, the determinants of inflation targeting, and the relationship between inflation targeting and sacrifice ratio. We use annual data for 44 emerging market economies from 1970 to 2017.
description: web scraping~~
description: Smallest Geographic Unit: country
DOI: 10.5281/zenodo.3711601
title: Supplemental information for "Creating thin magnetic layers at the surface of 2 Sb2Te3 topological insulators using a low-energy chromium ion beam"

description: A test upload of the data repository to Zenodo
description: This dataset is the Monte Carlo dose calculation of the Cr-40 keV ions stopping in Sb2Te3.
DOI: 10.15468/kux9yn
title: New Antarctic stenothoids sensu lato (Amphipoda, Crustacea)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Krapp-Schickel, Traudl (2011): New Antarctic stenothoids sensu lato (Amphipoda, Crustacea). European Journal of Taxonomy 2: 1-17, DOI: http://dx.doi.org/10.5852/ejt.2011.2
DOI: 10.18112/openneuro.ds002635.v1.0.0
title: 7T ocular dominance layers of LGN
DOI: 10.15468/wojdum
title: A new species of Anadia (Reptilia, Squamata) from the Venezuelan ' Lost World', northern South America

description: This dataset contains the digitized treatments in Plazi based on the original journal article Kok, Philippe J. R., Rivas, Gilson A. (2011): A new species of Anadia (Reptilia, Squamata) from the Venezuelan ' Lost World', northern South America. European Journal of Taxonomy 3: 1-18, DOI: http://dx.doi.org/10.5852/ejt.2011.3
DOI: 10.5281/zenodo.3711629
title: CMUSTRUDEL/need-for-tweet-data: Initial release

description: This dataset contains 70,427 cross-linked Twitter-GHTorrent user pairs identified as likely belonging to the same users. The dataset accompanies our research paper (PDF preprint here): <pre><code>@inproceedings{fang2020tweet, author = {Fang, Hongbo and Klug, Daniel and Lamba, Hemank and Herbsleb, James and Vasilescu, Bogdan}, title = {Need for Tweet: How Open Source Developers Talk About Their GitHub Work on Twitter}, booktitle = {International Conference on Mining Software Repositories (MSR)}, year = {2020}, pages = {to appear}, publisher = {ACM}, }</code></pre> The data cannot be used for any purpose other than conducting research. Due to privacy concerns, we only release the user IDs in Twitter and GHTorrent, respectively. We expect that users of this dataset will be able to collect other data using the Twitter API and GHTorrent, as needed. Please see below for an example. To query the Twitter API for a given user_id, you can: Apply for Twitter developer account here. Create an APP with your Twitter developer account, and create an "API key" and "API secret key". Obtain an access token. Given the previous API keys, run: <code>curl -u "&lt;API key&gt;:&lt;API secret key&gt;" --data "grant_type=client_credentials" "https://api.twitter.com/oauth2/token"</code> The response looks like this: <code>{"token_type":"bearer","access_token":"&lt;...&gt;"}</code> Copy the "access_token". Given the previous access token, run: <code>curl --request GET --url "https://api.twitter.com/1.1/users/show.json?user_id=&lt;user_id&gt;" --header "authorization: Bearer &lt;access_token&gt;"</code> The GHTorrent user ids map to the users table in the MySQL version of GHTorrent. To use GHTorrent, please follow instructions on the GHTorrent website.
DOI: 10.5281/zenodo.3711630
title: CMUSTRUDEL/need-for-tweet-data: Initial release

description: This dataset contains 70,427 cross-linked Twitter-GHTorrent user pairs identified as likely belonging to the same users. The dataset accompanies our research paper (PDF preprint here): <pre><code>@inproceedings{fang2020tweet, author = {Fang, Hongbo and Klug, Daniel and Lamba, Hemank and Herbsleb, James and Vasilescu, Bogdan}, title = {Need for Tweet: How Open Source Developers Talk About Their GitHub Work on Twitter}, booktitle = {International Conference on Mining Software Repositories (MSR)}, year = {2020}, pages = {to appear}, publisher = {ACM}, }</code></pre> The data cannot be used for any purpose other than conducting research. Due to privacy concerns, we only release the user IDs in Twitter and GHTorrent, respectively. We expect that users of this dataset will be able to collect other data using the Twitter API and GHTorrent, as needed. Please see below for an example. To query the Twitter API for a given user_id, you can: Apply for Twitter developer account here. Create an APP with your Twitter developer account, and create an "API key" and "API secret key". Obtain an access token. Given the previous API keys, run: <code>curl -u "&lt;API key&gt;:&lt;API secret key&gt;" --data "grant_type=client_credentials" "https://api.twitter.com/oauth2/token"</code> The response looks like this: <code>{"token_type":"bearer","access_token":"&lt;...&gt;"}</code> Copy the "access_token". Given the previous access token, run: <code>curl --request GET --url "https://api.twitter.com/1.1/users/show.json?user_id=&lt;user_id&gt;" --header "authorization: Bearer &lt;access_token&gt;"</code> The GHTorrent user ids map to the users table in the MySQL version of GHTorrent. To use GHTorrent, please follow instructions on the GHTorrent website.
DOI: 10.15468/3kdvje
title: Review of Neurepyris Kieffer, 1905 (Hymenoptera, Bethylidae), a new synonym of Pristocera Klug, 1808

description: This dataset contains the digitized treatments in Plazi based on the original journal article Alencar, Isabel D. C. C., Azevedo, Celso O. (2011): Review of Neurepyris Kieffer, 1905 (Hymenoptera, Bethylidae), a new synonym of Pristocera Klug, 1808. European Journal of Taxonomy 4: 1-12, DOI: http://dx.doi.org/10.5852/ejt.2011.4
DOI: 10.21227/32ab-9884
title: Datasets, Results and Figures about Biomedical Classification Problems

description: Fifteen datasets of biomedical classification problems are provided, together with the experimental results of applying automated evolution of kernels functions for support vector machines.
DOI: 10.21227/eb9p-g996
title: Datasets, Results and Figures about Biomedical Classification Problems

description: Fifteen datasets of biomedical classification problems are provided, together with the experimental results of applying automated evolution of kernels functions for support vector machines.
DOI: 10.25919/5e6edd5e53cfc
title: WAMSI 2 - Dredging Science Node - Project 5.3 - Natural Dynamics

description: The Theme 5.3 study was undertaken to improve our understanding of the spatial and temporal patterns in seagrass composition, abundance and reproductive phenology in the Pilbara region. Key environmental parameters, especially light, that influence seagrass survival and can be altered by dredging were also characterised. From August 2013 to March 2015 (18 months), surveys of seagrass abundance were undertaken in the Exmouth Gulf region. The locations surveyed (South Muiron Island, Bundegi and Exmouth Gulf) encompassed a range in water clarity from clear to turbid. Less frequent surveys were undertaken at other locations in the Pilbara: Thevenard Island, Rosemary Island and Balla. Measurements of seagrass abundance were also obtained from monitoring conducted as part of the dredging and dredge-spoil management plan for Chevron Australia’s Wheatstone Liquefied Natural Gas (LNG) Project. During each survey measurements were made in the field, photographs were taken or samples were collected in order to measure the following variables: 1. percentage cover of seagrass and other benthos; 2. above- and below-ground biomass, shoot density, leaf length, leaf width and number of flowers; 3. density of seagrass seeds; 4. sediment grain size; 5. stable isotope ratios (13C and 15N) of seagrass leaf tissue; and 6. water quality (light, conductivity, temperature, salinity, nutrients, suspended particulate matter and chlorophyll).
DOI: 10.5281/zenodo.3711639
title: Urbane Feldforschung: Urban Fieldwork: Quba-Lezgi

description: The recordings enclosed were conducted by William-Philip Hesse with Lezgian native speaker and informant Elvin Ahmadov from Azerbaijan in partial fulfillment of the requirements of the course "Urbane Feldforschung" at the University of Cologne, which was under the instruction of Dr. Frank Seifart, at the Institute of Linguistics during the Winter term 2019/2020. This repository contains: <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_20.11.2019_40_words_of_Swadesh_list_in_Kuba_Lezgic</strong><strong>:</strong><strong> </strong>40 ASJP words, as a shortened excerpt of the Swadesh-list providing an exemplary basic vocabulary of the language .eaf _final_cut.wav Metadaten - .pdf (metadata and background information) <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_20.11.2019_children_poem_in_Kuba_Lezgic</strong><strong>:</strong> short, traditional children poem about the relation between apricots and friendship with morphological segmentation and glossing .eaf .wav Metadaten - .pdf (metadata and background information) <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_20.11.2019_song_in_Kuba_Lezgic</strong><strong>:</strong> traditional folk song with transliteration and translation .eaf .wav Metadaten - .pdf (metadata and background information) <strong>Documentation: </strong>elaboration and metadata<strong> </strong>about this elicitation project as well as the informant <strong>William-Philip_Hesse_Feldforschung_Uni_Köln_2019_Ethno-Soziolinguistische_Beschreibung_von_Quba_Lesgisch_und_dessen_Sprechern.pdf</strong>: An introductory PDF document with identification of the language and sociolinguistic information. <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_Feldforschung_Uni_Köln_2019_separate_Beschreibung_der_Ergebnisse_der_Ellizitationssession.pdf</strong>: separate description and evaluation of theellicitation sessions’s results, together with the informant <strong>Personenmetadaten - Elvin Ahmadov - W.P.Hesse_und_E.Ahmadov_Quba_Lezgi.txt</strong>: Information about the informant (filled out by him) <strong>Projektmetadaten - W.P.Hesse_und_E.Ahmadov_Quba_Lezgi.txt</strong>: Information abot the project and its’ purpose <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_Projektinformationsblatt und Einverständniserklärung signiert.jpg</strong>: Informant's signed declaration of consent and the project information providedto him prior to the conduction
description: Cordial Thanks to Elvin Ahmadov and the numerous Lezgians who supportet me on this work!
DOI: 10.5281/zenodo.3711640
title: Urbane Feldforschung: Urban Fieldwork: Quba-Lezgi

description: The recordings enclosed were conducted by William-Philip Hesse with Lezgian native speaker and informant Elvin Ahmadov from Azerbaijan in partial fulfillment of the requirements of the course "Urbane Feldforschung" at the University of Cologne, which was under the instruction of Dr. Frank Seifart, at the Institute of Linguistics during the Winter term 2019/2020. This repository contains: <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_20.11.2019_40_words_of_Swadesh_list_in_Kuba_Lezgic</strong><strong>:</strong><strong> </strong>40 ASJP words, as a shortened excerpt of the Swadesh-list providing an exemplary basic vocabulary of the language .eaf _final_cut.wav Metadaten - .pdf (metadata and background information) <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_20.11.2019_children_poem_in_Kuba_Lezgic</strong><strong>:</strong> short, traditional children poem about the relation between apricots and friendship with morphological segmentation and glossing .eaf .wav Metadaten - .pdf (metadata and background information) <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_20.11.2019_song_in_Kuba_Lezgic</strong><strong>:</strong> traditional folk song with transliteration and translation .eaf .wav Metadaten - .pdf (metadata and background information) <strong>Documentation: </strong>elaboration and metadata<strong> </strong>about this elicitation project as well as the informant <strong>William-Philip_Hesse_Feldforschung_Uni_Köln_2019_Ethno-Soziolinguistische_Beschreibung_von_Quba_Lesgisch_und_dessen_Sprechern.pdf</strong>: An introductory PDF document with identification of the language and sociolinguistic information. <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_Feldforschung_Uni_Köln_2019_separate_Beschreibung_der_Ergebnisse_der_Ellizitationssession.pdf</strong>: separate description and evaluation of theellicitation sessions’s results, together with the informant <strong>Personenmetadaten - Elvin Ahmadov - W.P.Hesse_und_E.Ahmadov_Quba_Lezgi.txt</strong>: Information about the informant (filled out by him) <strong>Projektmetadaten - W.P.Hesse_und_E.Ahmadov_Quba_Lezgi.txt</strong>: Information abot the project and its’ purpose <strong>William-Philip_Hesse_mit_Elvin_Ahmadov_Projektinformationsblatt und Einverständniserklärung signiert.jpg</strong>: Informant's signed declaration of consent and the project information providedto him prior to the conduction
description: Cordial Thanks to Elvin Ahmadov and the numerous Lezgians who supportet me on this work!
DOI: 10.5281/zenodo.3711552
title: Wikidata Dump Articles published in Nature

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3711553
title: Wikidata Dump Articles published in Nature

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3711494
title: Deleted

description: deleted
DOI: 10.5281/zenodo.3711495
title: Deleted

description: deleted
DOI: 10.21227/gj3n-mt64
title: Datasets, Results and Figures about Biomedical Classification Problems

description: Fifteen datasets of biomedical classification problems are provided, together with the experimental results of applying automated evolution of kernels functions for support vector machines.
DOI: 10.5281/zenodo.3711499
title: Need for Tweet: How Open Source Developers Talk About Their GitHub Work on Twitter

description: This dataset contains 70,427 cross-linked Twitter-[GHTorrent](http://ghtorrent.org) user pairs identified as likely belonging to the same users. The dataset accompanies our research paper: @inproceedings{fang2020tweet, author = {Fang, Hongbo and Klug, Daniel and Lamba, Hemank and Herbsleb, James and Vasilescu, Bogdan}, title = {Need for Tweet: How Open Source Developers Talk About Their GitHub Work on Twitter}, booktitle = {International Conference on Mining Software Repositories (MSR)}, year = {2020}, pages = {to appear}, publisher = {ACM}, } The data <strong>cannot</strong> be used for any purpose other than conducting research. Due to privacy concerns, we only release the user IDs in Twitter and GHTorrent, respectively. We expect that users of this dataset will be able to collect other data using the Twitter API and GHTorrent, as needed. Please see below for an example. To query the Twitter API for a given user_id, you can: Apply for Twitter developer account here. Create an APP with your Twitter developer account, and create “API key” and “API secret key”. Obtain an access token. Given the previous &lt;API key&gt;:&lt;API secret key&gt;, run: curl -u "&lt;API key&gt;:&lt;API secret key&gt;" --data "grant_type=client_credentials" "https://api.twitter.com/oauth2/token" The response looks like this: {"token_type":"bearer","access_token":"&lt;...&gt;"} Copy the "access_token". Given the previous access token, run: curl --request GET --url "https://api.twitter.com/1.1/users/show.json?user_id=&lt;user_id&gt;" --header "authorization: Bearer &lt;access_token&gt;" The GHTorrent user ids map to the users table in the MySQL version of GHTorrent. To use GHTorrent, please follow instructions on the GHTorrent website.
DOI: 10.5281/zenodo.3711500
title: Need for Tweet: How Open Source Developers Talk About Their GitHub Work on Twitter

description: This dataset contains 70,427 cross-linked Twitter-[GHTorrent](http://ghtorrent.org) user pairs identified as likely belonging to the same users. The dataset accompanies our research paper: @inproceedings{fang2020tweet, author = {Fang, Hongbo and Klug, Daniel and Lamba, Hemank and Herbsleb, James and Vasilescu, Bogdan}, title = {Need for Tweet: How Open Source Developers Talk About Their GitHub Work on Twitter}, booktitle = {International Conference on Mining Software Repositories (MSR)}, year = {2020}, pages = {to appear}, publisher = {ACM}, } The data <strong>cannot</strong> be used for any purpose other than conducting research. Due to privacy concerns, we only release the user IDs in Twitter and GHTorrent, respectively. We expect that users of this dataset will be able to collect other data using the Twitter API and GHTorrent, as needed. Please see below for an example. To query the Twitter API for a given user_id, you can: Apply for Twitter developer account here. Create an APP with your Twitter developer account, and create “API key” and “API secret key”. Obtain an access token. Given the previous &lt;API key&gt;:&lt;API secret key&gt;, run: curl -u "&lt;API key&gt;:&lt;API secret key&gt;" --data "grant_type=client_credentials" "https://api.twitter.com/oauth2/token" The response looks like this: {"token_type":"bearer","access_token":"&lt;...&gt;"} Copy the "access_token". Given the previous access token, run: curl --request GET --url "https://api.twitter.com/1.1/users/show.json?user_id=&lt;user_id&gt;" --header "authorization: Bearer &lt;access_token&gt;" The GHTorrent user ids map to the users table in the MySQL version of GHTorrent. To use GHTorrent, please follow instructions on the GHTorrent website.
DOI: 10.5281/zenodo.3711160
title: Wikidata Dump paises

description: RDF dump of wikidata produced with wdumps. descargado de tools wmflabs org<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3711161
title: Wikidata Dump paises

description: RDF dump of wikidata produced with wdumps. descargado de tools wmflabs org<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3711645
title: Co-localization and confinement ofecto-nucleotidases modulate extracellularadenosine nucleotide distributions

description: "dataset.zip" includes all of notebooks and data files needed for our manuscript with title "Co-localization and confinement ofecto-nucleotidases modulate extracellularadenosine nucleotide distributions".
DOI: 10.5281/zenodo.3711509
title: JTeC: A Large Collection of Java Test Classes forTest Code Analysis and Processing

description: The recent push towards test automation and test-driven development continues to scale up the dimensions of test code that needs to be maintained, analysed, and processed side-by-side with production code. As a consequence, on the one side regression testing techniques, e.g., for test suite prioritization or test case selection, capable to handle such large-scale test suites become indispensable; on the other side, as test code exposes own characteristics, specific techniques for its analysis and refactoring are actively sought. We present JTeC, a large-scale dataset of test cases that researchers can use for benchmarking the above techniques or any other type of tool expressly targeting test code. JTeC collects more than 2.5M+ test classes belonging to 31K+ GitHub projects and summing up to more than 430 Million LOCs of ready-to-use real-world test code.
description: Companion page for the JTeC dataset at https://github.com/JTeCDataset/JTeC
DOI: 10.5281/zenodo.3711649
title: Co-localization and confinement ofecto-nucleotidases modulate extracellularadenosine nucleotide distributions

description: "dataset.zip" includes all of the notebooks and data files needed for manuscript "Co-localization and confinement ofecto-nucleotidases modulate extracellularadenosine nucleotide distributions".
DOI: 10.21227/85wv-7w27
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 10.9 Million plus (collecting since Feb 1, 2020)Each database (*.db) contain three columns.First column: date and time of the tweetSecond column: tweetThird column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live.To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. New databases will be added to this dataset every week. Bookmark this page for further updates. [1] https://sentiment.live/ [2] https://textblob.readthedocs.io/en/dev/