cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/c25nh9nfxp.4
title: Data for: Development of a new code for stopping power and CSDA range calculation of incident charged particles, Part A: electron and positron

description: these data present the stopping power and range of electron and positron in selected matters
DOI: 10.5281/zenodo.3676916
title: Lobster Benchmark

description: These are the files to reproduce the benchmark of the new Lobster version that can deal with time-reversal symmetry. This benchmark published here: dx.doi.org/10.1002/jcc.26353. ALL_RESULTS_ABINIT.zip contains the data for all ABINIT/Lobster calculations, ALL_RESULTS_QE.zip contains the data for all Quantum Espresso/Lobster calculations, and ALL_RESULTS_VASP_without_POTCAR.zip contains the data for all VASP/Lobster calculations. In the latter zip folder, we have removed all POTCAR files. Those can be reconstructed with the help of the vasprun.xml and the OUTCAR files.
DOI: 10.5281/zenodo.3676915
title: Lobster Benchmark

description: These are the files to reproduce the benchmark of the new Lobster version that can deal with time-reversal symmetry. This benchmark published here: dx.doi.org/10.1002/jcc.26353. ALL_RESULTS_ABINIT.zip contains the data for all ABINIT/Lobster calculations, ALL_RESULTS_QE.zip contains the data for all Quantum Espresso/Lobster calculations, and ALL_RESULTS_VASP_without_POTCAR.zip contains the data for all VASP/Lobster calculations. In the latter zip folder, we have removed all POTCAR files. Those can be reconstructed with the help of the vasprun.xml and the OUTCAR files.
DOI: 10.5281/zenodo.3891803
title: Doubly vinylogous and doubly rearomative functionalization of 2-alkyl-3-furfurals - computational data

description: Computational data concerning geometries and energies of substrates, transition states and product for four possible approaches of quinone substrate to enamine.
DOI: 10.5281/zenodo.3841879
title: Oracles data-set

description: This repository collects fthe ollwoing data-sets: blocks data-set, transactions data-set, Oracles' predictions data-set, User-centered predictions data-set
DOI: 10.15161/oar.it/30424
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.5281/zenodo.3892498
title: Oracles data-set

description: This repository collects fthe ollwoing data-sets: blocks data-set, transactions data-set, Oracles' predictions data-set, User-centered predictions data-set
DOI: 10.5281/zenodo.3892589
title: Oracles data-set

description: This repository collects fthe ollwoing data-sets: blocks data-set, transactions data-set, Oracles' predictions data-set, User-centered predictions data-set
DOI: 10.5281/zenodo.3892598
title: M4 Yearly Dataset

description: This dataset contains 23000 yearly time series used in the M4 forecasting competition.
description: {"references": ["Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2020. The m4 competition: 100,000 time series and 61 forecasting methods. International Journal of Forecasting 36 (1), 54 \u2013 74.", "Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2018. The m4 competition: results, findings, conclusion and way forward, International Journal of Forecasting 34 (4), 802 \u2013 808."]}
DOI: 10.5281/zenodo.3892623
title: M4 Quarterly Dataset

description: This dataset contains 24000 quarterly time series used in the M4 forecasting competition.
description: {"references": ["Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2018. The m4 competition: results, findings, conclusion and way forward, International Journal of Forecasting 34 (4), 802 \u2013 808.", "Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2020. The m4 competition: 100,000 time series and 61 forecasting methods. International Journal of Forecasting 36 (1), 54 \u2013 74."]}
DOI: 10.5281/zenodo.3892521
title: LDV-beat dataset

description: The dataset consisted of:(i) one folder and (ii) one .csv file. The folder contain 28 signal aquisitions (one for each subject) in .csv format. Each file is one simoultaneously recording of II lead ECG and common carotid LDV at 500 Hz sampling rate. The LDV-beat dataset.csv contain segment of LDV signal for a length of 75 point each. The LDV segment were labeled as "1" in the "beat" column when the first point was in correspandence of the R peak of the ECG, and labeled as "0" otherwise.
DOI: 10.5281/zenodo.3892520
title: LDV-beat dataset

description: The dataset consisted of:(i) one folder and (ii) one .csv file. The folder contain 28 signal aquisitions (one for each subject) in .csv format. Each file is one simoultaneously recording of II lead ECG and common carotid LDV at 500 Hz sampling rate. The LDV-beat dataset.csv contain segment of LDV signal for a length of 75 point each. The LDV segment were labeled as "1" in the "beat" column when the first point was in correspandence of the R peak of the ECG, and labeled as "0" otherwise.
DOI: 10.5281/zenodo.3892635
title: M4 Monthly Dataset

description: This dataset contains 48000 monthly time series used in the M4 forecasting competition. The series are belonging to 6 different domains: demographic, micro, macro, industry, finance and other.
description: {"references": ["Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2018. The m4 competition: results, findings, conclusion and way forward, International Journal of Forecasting 34 (4), 802 \u2013 808.", "Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2020. The m4 competition: 100,000 time series and 61 forecasting methods. International Journal of Forecasting 36 (1), 54 \u2013 74."]}
DOI: 10.5281/zenodo.3892676
title: M4 Weekly Dataset

description: This dataset contains 359 weekly time series used in the M4 forecasting competition.
description: {"references": ["Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2018. The m4 competition: results, findings, conclusion and way forward, International Journal of Forecasting 34 (4), 802 \u2013 808.", "Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2020. The m4 competition: 100,000 time series and 61 forecasting methods. International Journal of Forecasting 36 (1), 54 \u2013 74."]}
DOI: 10.5281/zenodo.3892689
title: M4 Daily Dataset

description: This dataset contains 4227 daily time series used in the M4 forecasting competition.
description: {"references": ["Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2018. The m4 competition: results, findings, conclusion and way forward, International Journal of Forecasting 34 (4), 802 \u2013 808.", "Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2020. The m4 competition: 100,000 time series and 61 forecasting methods. International Journal of Forecasting 36 (1), 54 \u2013 74."]}
DOI: 10.5281/zenodo.3892721
title: M4 Hourly Dataset

description: This dataset contains 414 hourly time series used in the M4 forecasting competition.
description: {"references": ["Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2018. The m4 competition: results, findings, conclusion and way forward, International Journal of Forecasting 34 (4), 802 \u2013 808.", "Makridakis, S., Spiliotis, E., Assimakopoulos, V., 2020. The m4 competition: 100,000 time series and 61 forecasting methods. International Journal of Forecasting 36 (1), 54 \u2013 74."]}
DOI: 10.21227/6d7h-d447
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets were captured by an on-going project deployed at https://live.rlamsal.com.np. The geolocation data was extracted from the tweets which mentioned anything about “corona”, "coronavirus", "covid" and possible variants of "sarscov2", "nCov", "covid-19", "ncov2019". Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).Note: I started sharing the IDs of the tweets that had exact 'point' location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs (above 180+ million tweets) shared in the Coronavirus (COVID-19) Tweets Dataset.If you need the geolocation-based data starting March 20, 2020, then use the Coronavirus (COVID-19) Tweets Dataset and hydrate the IDs while adding the following condition:data = json.loads(data)if data["coordinates"]: longitude, latitude = data["coordinates"]["coordinates"]The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-june5.zip will contain tweet ID and sentiment score of the tweets (in CSV and JSON formats) that were created between April 28, 2020, and June 05, 2020.Why are only tweet IDs being shared? Twitter's content redistribution policy restricts the sharing of tweet information other than tweet IDs and/or user IDs. Twitter wants researchers always to pull fresh data. It is because a user might delete a tweet or make their profile protected. If the same tweet has already been pulled and shared on a public domain, it might make the user/community vulnerable to many inferences coming out of the shared data which currently does not exist or is private.
DOI: 10.5281/zenodo.3892749
title: Melbourne Pedestrian Counts Dataset

description: This dataset contains hourly pedestrian counts captured from 66 sensors in Melbourne city starting from May 2009. The original dataset is regularly updated when a new set of observations become available. The dataset uploaded here contains pedestrian counts up to 2020-04-30.
description: {"references": ["City of Melbourne, 2017. Pedestrian counting system \u2013 2009 to present (counts per hour). URL https://data.melbourne.vic.gov.au/Transport/Pedestrian-Counting-System-2009-to-Present-counts-/b2ak-trbp"]}
DOI: 10.5281/zenodo.3892859
title: Dataset for Manthan: A Data Driven Approach for Boolean Function Synthesis (CAV-20 paper)

description: The data set consists of 609 benchmarks used for experimental evaluation of paper titled 'Manthan: A Data-Driven Approach for Boolean Function Synthesis" published in International Conference of Computer-Aided Verification (CAV), 2020 . The benchmarks are from following sources: Prenex-2QBF track of QBFEval-17 and QBFEval-18 Arithmetic set (Srivastava, Gulwani, Foster 2013). Disjunctive set (Akshay, Charkraborty, John, Shah 2017). Factorization set (Akshay, Charkraborty, John, Shah 2017).
DOI: 10.5281/zenodo.3892858
title: Dataset for Manthan: A Data Driven Approach for Boolean Function Synthesis (CAV-20 paper)

description: The data set consists of 609 benchmarks used for experimental evaluation of paper titled 'Manthan: A Data-Driven Approach for Boolean Function Synthesis" published in International Conference of Computer-Aided Verification (CAV), 2020 . The benchmarks are from following sources: Prenex-2QBF track of QBFEval-17 and QBFEval-18 Arithmetic set (Srivastava, Gulwani, Foster 2013). Disjunctive set (Akshay, Charkraborty, John, Shah 2017). Factorization set (Akshay, Charkraborty, John, Shah 2017).
DOI: 10.5281/zenodo.3892469
title: ZhangChao0104/Article-data V1

description: This is the data repository for JGR-Atmos paper "Light absorption and fluorescence properties of water-soluble organic compounds in carbonaceous particles at a typical remote site of the southeast Himalayas and Tibetan Plateau"
DOI: 10.5281/zenodo.3892468
title: ZhangChao0104/Article-data V1

description: This is the data repository for JGR-Atmos paper "Light absorption and fluorescence properties of water-soluble organic compounds in carbonaceous particles at a typical remote site of the southeast Himalayas and Tibetan Plateau"
DOI: 10.5281/zenodo.3892116
title: Systematic mapping study on software product line experiments: extracted data, conceptual model and mind maps

description: Systematic mapping study on software product line experiments - primary studies and respective extracted data and created conceptual model and mind maps.
description: Funded by CAPES/Brazil code 001
DOI: 10.5281/zenodo.3892681
title: 20200227

description: ns2
DOI: 10.5281/zenodo.3892680
title: 20200227

description: ns2
DOI: 10.18170/dvn/xbwsdv
title: Replication Data for: Imaging Shallow Fault Structures by Three-Dimensional Reverse Time Migration of Ground Penetration Radar Data

description: Data for the paper.
DOI: 10.5281/zenodo.3892955
title: MAOn: A Data-driven Methodology to Generate Living Ontologies

description: This repository presents the MAnto Lite ontology created with our MAOn methodology in the context of transport and public and the accessibility it provides. Besides, a set of annotated data with the ontology as a validation method is presented. The MAOn methodology is characterized by being data-based, by creating live ontologies and by a thorough evaluation process of the created ontology.
DOI: 10.5281/zenodo.3892954
title: MAOn: A Data-driven Methodology to Generate Living Ontologies

description: This repository presents the MAnto Lite ontology created with our MAOn methodology in the context of transport and public and the accessibility it provides. Besides, a set of annotated data with the ontology as a validation method is presented. The MAOn methodology is characterized by being data-based, by creating live ontologies and by a thorough evaluation process of the created ontology.
DOI: 10.5281/zenodo.3892919
title: Kaggle Wikipedia Web Traffic Daily Dataset (without Missing Values)

description: This dataset was used in the Kaggle Wikipedia Web Traffic forecasting competition. It contains 145063 daily time series representing the number of hits or web traffic for a set of Wikipedia pages from 2015-07-01 to 2017-09-10. The original dataset contains missing values. They have been simply replaced by zeros.
description: {"references": ["Google, 2017. Web traffic time series forecasting. URL https://www.kaggle.com/c/web-traffic-time-series-forecasting"]}
DOI: 10.5281/zenodo.3892814
title: Kaggle Wikipedia Web Traffic Daily Dataset (with Missing Values)

description: This dataset was used in the Kaggle Wikipedia Web Traffic forecasting competition. It contains 145063 daily time series representing the number of hits or web traffic for a set of Wikipedia pages from 2015-07-01 to 2017-09-10.
description: {"references": ["Google, 2017. Web traffic time series forecasting. URL https://www.kaggle.com/c/web-traffic-time-series-forecasting"]}
DOI: 10.5281/zenodo.3892977
title: Kaggle Wikipedia Web Traffic Weekly Dataset

description: This is the aggregated version of the daily dataset used in the Kaggle Wikipedia Web Traffic forecasting competition. It contains 145063 time series representing the number of hits or web traffic for a set of Wikipedia pages from 2015-07-01 to 2017-09-05, after aggregating them into weekly. The original dataset contains missing values. They have been simply replaced by zeros before aggregation.
description: {"references": ["Google, 2017. Web traffic time series forecasting. URL https://www.kaggle.com/c/web-traffic-time-series-forecasting"]}
DOI: 10.5281/zenodo.3892922
title: Recording of video on demand traffic

description: The recording was created with the General Purpose Network Testing Framework: https://github.com/vs-uulm/General-Purpose-Network-Testing-Framework
DOI: 10.5281/zenodo.3892921
title: Recording of video on demand traffic

description: The recording was created with the General Purpose Network Testing Framework: https://github.com/vs-uulm/General-Purpose-Network-Testing-Framework
DOI: 10.5281/zenodo.3892879
title: Recording of one directional marketplace traffic

description: The recording was created with the General Purpose Network Testing Framework: https://github.com/vs-uulm/General-Purpose-Network-Testing-Framework
DOI: 10.5281/zenodo.3892878
title: Recording of one directional marketplace traffic

description: The recording was created with the General Purpose Network Testing Framework: https://github.com/vs-uulm/General-Purpose-Network-Testing-Framework
DOI: 10.5281/zenodo.3892937
title: Recording of web browsing traffic

description: The recording was created with the General Purpose Network Testing Framework: https://github.com/vs-uulm/General-Purpose-Network-Testing-Framework
DOI: 10.5281/zenodo.3892936
title: Recording of web browsing traffic

description: The recording was created with the General Purpose Network Testing Framework: https://github.com/vs-uulm/General-Purpose-Network-Testing-Framework
DOI: 10.5281/zenodo.3892935
title: Recording of filesharing traffic

description: The recording was created with the General Purpose Network Testing Framework: https://github.com/vs-uulm/General-Purpose-Network-Testing-Framework
DOI: 10.5281/zenodo.3892934
title: Recording of filesharing traffic

description: The recording was created with the General Purpose Network Testing Framework: https://github.com/vs-uulm/General-Purpose-Network-Testing-Framework
DOI: 10.5281/zenodo.3893022
title: PA 2017 ACS Congressional Districting Plans via SFSR

description: 11,206 Congressional redistricting plans for Pennsylvania, using the 2017 American Community Survery (ACS) census data, and assuming 17 districts. All generated with an implementation of the SFSR algorithm, originated by the author.
DOI: 10.5281/zenodo.3893021
title: PA 2017 ACS Congressional Districting Plans via SFSR

description: 11,206 Congressional redistricting plans for Pennsylvania, using the 2017 American Community Survery (ACS) census data, and assuming 17 districts. All generated with an implementation of the SFSR algorithm, originated by the author.
DOI: 10.5281/zenodo.3892999
title: Dataset for IDS testing

description: Dataset constructed to trigger IDS rules based on the community data set of the Snort Intrusion Detection System
DOI: 10.5281/zenodo.3892998
title: Dataset for IDS testing

description: Dataset constructed to trigger IDS rules based on the community data set of the Snort Intrusion Detection System
DOI: 10.5281/zenodo.3891888
title: Supplemental to Masterthesis: Comparative Genome analysis of borontolerant and -sensitive bacterial isolates

description: Supplemental data and result files of the Masterthesis: Comparative Genome analysis of borontolerant and -sensitive bacterial isolates
DOI: 10.5281/zenodo.3891887
title: Supplemental to Masterthesis: Comparative Genome analysis of borontolerant and -sensitive bacterial isolates

description: Supplemental data and result files of the Masterthesis: Comparative Genome analysis of borontolerant and -sensitive bacterial isolates
DOI: 10.21227/5n77-vw04
title: Testing data of dynamic response of maglev rotary table

description: This data gives the testing data of the 6-DoF maglev rotary table including step response, slope tracking, multi-axis motion. With the numerical wrench model and harmonic force model employed in the control system, the dynamic responses have some differences. Each opj file contains the test group (numerical wrench model) and control group (analytical harmonic model).
DOI: 10.21227/c5hc-r824
title: Testing data of dynamic response of maglev rotary table

description: This data gives the testing data of the 6-DoF maglev rotary table including step response, slope tracking, multi-axis motion. With the numerical wrench model and harmonic force model employed in the control system, the dynamic responses have some differences. Each opj file contains the test group (numerical wrench model) and control group (analytical harmonic model).
DOI: 10.5281/zenodo.3892899
title: Post-partum intrauterine device insertion

description: Complete data set for PPIDU use post CS
DOI: 10.5281/zenodo.3892898
title: Post-partum intrauterine device insertion

description: Complete data set for PPIDU use post CS
DOI: 10.5281/zenodo.3893072
title: Thermodynamical Modeling of Liquid Fe-Si-Mg-O:Molten Magnesium Silicate Release from the Core (Table S3)

description: Supplementary Information Table S3. Contains full EMPA analyses of coexisting liquid metal and silicate melt in ELSI runs partially reported by Badro, J., Aubert, J., Hirose, K., Nomura, R., Blanchard, I., Borensztajn, S., & Siebert, J. (2018). Magnesium partitioning between Earth’s mantle and core and its potential to drive an early exsolution geodynamo. Geophys. Res. Lett., 45. doi: https://doi.org/10.1029/2018GL080405.
description: Funding provided by JSPS grant 16H06285.
DOI: 10.5281/zenodo.3893071
title: Thermodynamical Modeling of Liquid Fe-Si-Mg-O:Molten Magnesium Silicate Release from the Core (Table S3)

description: Supplementary Information Table S3. Contains full EMPA analyses of coexisting liquid metal and silicate melt in ELSI runs partially reported by Badro, J., Aubert, J., Hirose, K., Nomura, R., Blanchard, I., Borensztajn, S., & Siebert, J. (2018). Magnesium partitioning between Earth’s mantle and core and its potential to drive an early exsolution geodynamo. Geophys. Res. Lett., 45. doi: https://doi.org/10.1029/2018GL080405.
description: Funding provided by JSPS grant 16H06285.
DOI: 10.5281/zenodo.3893085
title: Ooh Na Na Synonyms

description: This is a gzipped three-column TSV file that has prefixes, identifiers, and synonyms for lots of biomedical entities drawn from the terminologies and ontologies in PyOBO. It was generated with the following code in the shell: <pre>pip install git+https://github.com/pyobo/pyobo.git obo synonymdb</pre> Any silly name suggestions that include literary references are welcome :)
DOI: 10.5281/zenodo.3893078
title: Ancillary files for generating and processing PA districting plans with 2017 ACS data

description: Files PA census tracts 2017 data.csv and tl_2010_42_tract10.zip were downloaded from the US Bureau of the Census and so are publicly owned. They are here for the sake of archiving purposes. They were used to generate the PA Congressional districting plans at https://doi.org/10.5281/zenodo.3893022. File IDsPopsFull.csv was generated by the author. It maps Pennsylvania census tract IDs to demographic data and to counties in Pennsylvania. This is useful for post-processing plans.
DOI: 10.5281/zenodo.3893077
title: Ancillary files for generating and processing PA districting plans with 2017 ACS data

description: Files PA census tracts 2017 data.csv and tl_2010_42_tract10.zip were downloaded from the US Bureau of the Census and so are publicly owned. They are here for the sake of archiving purposes. They were used to generate the PA Congressional districting plans at https://doi.org/10.5281/zenodo.3893022. File IDsPopsFull.csv was generated by the author. It maps Pennsylvania census tract IDs to demographic data and to counties in Pennsylvania. This is useful for post-processing plans.
DOI: 10.21227/7v5p-5t70
title: Stair GPD 2020 (LMGA)

description: Stair ambulation of 21 healthy subjects collected in Monash University for validating gait phase detection algorithms. raw text files and matlab data files are included.
DOI: 10.21227/p5rp-6y19
title: Stair GPD 2020 (LMGA)

description: Stair ambulation of 21 healthy subjects collected in Monash University for validating gait phase detection algorithms. raw text files and matlab data files are included.