cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14272/sfyoeomjocguae-uhfffaoysa-n/chmo0000763
title: attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) (N-tert-butyl-9,11,17-triazatetracyclo[8.7.0.02,7.011,16]heptadeca-1(10),2,4,6,8,12,14,16-octaen-8-amine)
title: InChI=1S/C18H18N4/c1-18(2,3)21-16-13-9-5-4-8-12(13)15-17(20-16)22-11-7-6-10-14(22)19-15/h4-11H,1-3H3,(H,20,21)

description: dataset for attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) IR (ATR, ṽ) = 3312 (w), 3047 (w), 2962 (m), 2924 (m), 2870 (w), 2856 (w), 1664 (w), 1632 (w), 1621 (m), 1582 (m), 1560 (m), 1536 (m), 1504 (vs), 1483 (m), 1449 (s), 1421 (vs), 1378 (s), 1346 (vs), 1302 (vs), 1271 (s), 1258 (vs), 1225 (vs), 1221 (vs), 1205 (vs), 1154 (m), 1147 (s), 1123 (m), 1082 (m), 1071 (s), 1028 (s), 1004 (m), 938 (m), 929 (m), 860 (w), 823 (m), 802 (m), 788 (m), 765 (vs), 741 (vs), 732 (vs), 707 (s), 694 (m), 669 (vs), 650 (s), 635 (s), 611 (m), 591 (m), 565 (m), 521 (vs), 486 (m), 439 (vs), 422 (s), 404 (s), 381 (vs) cm–1.
DOI: 10.14272/sfyoeomjocguae-uhfffaoysa-n.1
title: N-(tert-butyl)pyrido[2',1':2,3]imidazo[4,5-c]isoquinolin-5-amine
title: InChI=1S/C18H18N4/c1-18(2,3)21-16-13-9-5-4-8-12(13)15-17(20-16)22-11-7-6-10-14(22)19-15/h4-11H,1-3H3,(H,20,21)

description: This dataset contains experimental data from a sample (N-tert-butyl-9,11,17-triazatetracyclo[8.7.0.02,7.011,16]heptadeca-1(10),2,4,6,8,12,14,16-octaen-8-amine, InChI=1S/C18H18N4/c1-18(2,3)21-16-13-9-5-4-8-12(13)15-17(20-16)22-11-7-6-10-14(22)19-15/h4-11H,1-3H3,(H,20,21)). The datasets from the following experiments are available: attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) high resolution fast-atom bombardment mass spectrometry (HRFABMS) fast-atom bombardment mass spectrometry (FABMS) 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR)
DOI: 10.14272/sfyoeomjocguae-uhfffaoysa-n/chmo0000726
title: high resolution fast-atom bombardment mass spectrometry (HRFABMS) (N-tert-butyl-9,11,17-triazatetracyclo[8.7.0.02,7.011,16]heptadeca-1(10),2,4,6,8,12,14,16-octaen-8-amine)
title: InChI=1S/C18H18N4/c1-18(2,3)21-16-13-9-5-4-8-12(13)15-17(20-16)22-11-7-6-10-14(22)19-15/h4-11H,1-3H3,(H,20,21)

description: dataset for high resolution fast-atom bombardment mass spectrometry (HRFABMS) HRMS‑FAB (m/z): [M+H]+ calcd. for C18H19N4, 291.1604; found, 291.1602.
DOI: 10.14272/sfyoeomjocguae-uhfffaoysa-n/chmo0000563
title: fast-atom bombardment mass spectrometry (FABMS) (N-tert-butyl-9,11,17-triazatetracyclo[8.7.0.02,7.011,16]heptadeca-1(10),2,4,6,8,12,14,16-octaen-8-amine)
title: InChI=1S/C18H18N4/c1-18(2,3)21-16-13-9-5-4-8-12(13)15-17(20-16)22-11-7-6-10-14(22)19-15/h4-11H,1-3H3,(H,20,21)

description: dataset for fast-atom bombardment mass spectrometry (FABMS) FAB‑MS m/z (%): 292 (22), 291 [M+H]+ (100), 290 (83), 289 (6), 275 (7), 236 (6), 235 (26), 234 (32), 133 (16).HRMS‑FAB (m/z): [M+H]+ calcd. for C18H19N4, 291.1604; found, 291.1602.
DOI: 10.14272/sfyoeomjocguae-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (N-tert-butyl-9,11,17-triazatetracyclo[8.7.0.02,7.011,16]heptadeca-1(10),2,4,6,8,12,14,16-octaen-8-amine)
title: InChI=1S/C18H18N4/c1-18(2,3)21-16-13-9-5-4-8-12(13)15-17(20-16)22-11-7-6-10-14(22)19-15/h4-11H,1-3H3,(H,20,21)

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, CDCl3 [7.26 ppm], ppm) δ = 8.65 (dt, J = 8.1, 1.1 Hz, 1H, CHAr), 8.60 (dt, J = 6.8, 1.3 Hz, 1H, CHAr), 7.84 (dt, J = 8.4, 0.9 Hz, 1H, CHAr), 7.78 (ddd, J = 8.1, 7.0, 1.1 Hz, 1H, CHAr), 7.70 (dt, J = 9.2, 1.1 Hz, 1H, CHAr), 7.54 (ddd, J = 8.4, 7.0, 1.3 Hz, 1H, CHAr), 7.27 (ddd, J = 9.2, 6.6, 1.3 Hz, 1H, CHAr), 6.87 (td, J = 6.7, 1.1 Hz, 1H, CHAr), 5.33 (s, 1H, NH), 1.69 (s, 9H, CH3). Spectrum contains signals of ethyl acetate (4.12, 2.05, 1.26 ppm) and H-grease. The yield has been adjusted accordingly.
DOI: 10.6084/m9.figshare.21939674
title: Chapter3_edgelist_of_PPI

description: Chapter3_edgelist_of_PPI
DOI: 10.6084/m9.figshare.21939674.v1
title: Chapter3_edgelist_of_PPI

description: Chapter3_edgelist_of_PPI
DOI: 10.5281/zenodo.7559936
title: ARtwin dissemination related data

description: This dataset contains website and social media analytics of the ARtwin project, as well as an assessment of KPIs related to dissemination.
DOI: 10.5281/zenodo.7559935
title: ARtwin dissemination related data

description: This dataset contains website and social media analytics of the ARtwin project, as well as an assessment of KPIs related to dissemination.
DOI: 10.6084/m9.figshare.21939680
title: Chapter3_Node Table of HPPI Network

description: Node Table of HPPI Network
DOI: 10.6084/m9.figshare.21939680.v1
title: Chapter3_Node Table of HPPI Network

description: Node Table of HPPI Network
DOI: 10.6084/m9.figshare.21939686
title: Chapter3_Results of R_TFs_CAZymes

description: Chapter3_Results of R_TFs_CAZymes
DOI: 10.6084/m9.figshare.21939686.v1
title: Chapter3_Results of R_TFs_CAZymes

description: Chapter3_Results of R_TFs_CAZymes
DOI: 10.5255/ukda-sn-856187
title: Irish Civil Parishes: 1841 and 1851 Digitized and Mapped, 1821-1851

description: This data collection contains data primarily from both the 1841 and 1851 Census of Ireland used in Fernihough and Ó Gráda (2022). Also contained, where available, are population counts from the 1821 and 1831 censuses. The data collection also includes an amended version of the Civil Parish Shapefile from townlands.ie (OpenStreetMap Ireland, 2020). Both data sources were adjusted to ensure concordance. The towlands.ie data is open data is open data, licensed under the Open Data Commons Open Database License (ODbL). Please contact Alan Fernihough for further details or queries. The “shapefile” files are the GIS files one needs to load the spatial boundaries. The census data is included in the “data.csv” file and one must merge this to the shapefiles to work with these data. However, this is a simple process. The file “load and join.R” is an example of how this could be performed using the R statistical software package.
DOI: 10.6084/m9.figshare.21939692
title: Chapter3_Gene_ontology_subnetwork

description: Gene_ontology_subnetwork
DOI: 10.6084/m9.figshare.21939692.v1
title: Chapter3_Gene_ontology_subnetwork

description: Gene_ontology_subnetwork
DOI: 10.34740/kaggle/dsv/4887175
title: AutoXGB
DOI: 10.6084/m9.figshare.21939695
title: Chapter3_Gene expression PPI network

description: Gene expression PPI network
DOI: 10.6084/m9.figshare.21939695.v1
title: Chapter3_Gene expression PPI network

description: Gene expression PPI network
DOI: 10.6084/m9.figshare.21939710
title: Chapter3_BiNGo results of Gene expression network

description: Chapter3_BiNGo results of Gene expression network
DOI: 10.6084/m9.figshare.21939710.v1
title: Chapter3_BiNGo results of Gene expression network

description: Chapter3_BiNGo results of Gene expression network
DOI: 10.6084/m9.figshare.19312262
title: Metadata for Alpha chain clonotypes

description: Metadata of the samples listed in the alpha clonotype dataset, which can be found here: 10.6084/m9.figshare.19287506<br>
DOI: 10.6084/m9.figshare.19312262.v1
title: Metadata for alpha chain clonotypes

description: Metadata of the samples listed in the alpha clonotype dataset, which can be found here: 10.6084/m9.figshare.19287506<br>
DOI: 10.6084/m9.figshare.21939713
title: Chapter3_Subcellular Localization

description: Chapter3_Subcellular Localization
DOI: 10.6084/m9.figshare.21939713.v1
title: Chapter3_Subcellular Localization

description: Chapter3_Subcellular Localization
DOI: 10.6084/m9.figshare.21939791
title: Chapter3_Results of Pathogenicity proteins

description: Chapter3_Results of Pathogenicity proteins
DOI: 10.6084/m9.figshare.21939791.v1
title: Chapter3_Results of Pathogenicity proteins

description: Chapter3_Results of Pathogenicity proteins
DOI: 10.6084/m9.figshare.21939923
title: Chapter3_DESeq_rsesults_of_RNA-Seq_datasets

description: Chapter3_DESeq_rsesults_of_RNA-Seq_datasets
DOI: 10.6084/m9.figshare.21939923.v1
title: Chapter3_DESeq_rsesults_of_RNA-Seq_datasets

description: Chapter3_DESeq_rsesults_of_RNA-Seq_datasets
DOI: 10.6084/m9.figshare.21939704
title: RMSD values of SARS-CoV-2's RBDs calculated by the "structalign" command

description: <strong>RMSD values of all 'single mutant' of SARS-CoV-2's RBD (S protein) region in 7 lineages calculated by the "structalign" command</strong> wuhan_ref: X-ray structure was the reference self_ref: itself base variants structure was the reference <br> RMSD: Root-mean-square deviation RBD: Receptor-binding domain <br>
DOI: 10.5281/zenodo.6546226
title: Cold Region Data Accessibility Portal for Québec (CRDAP-QC)

description: The Cold Region Data Accessibility Portal for Quebec is a collection of public data query platforms to display, analyze, and compare freeze and thaw, as well as climate data, for the province of Quebec. This suite of products was made by the Water Security and Climate Change Lab, located at Concordia University. To visit the portal, please check http://wscc.encs.concordia.ca/home.html.
DOI: 10.5281/zenodo.7449056
title: PROGpedia

description: This dataset consists of the submissions to 16 programming exercises in Mooshak proposed in multiple years within the 2003-2020 timespan to undergraduate Computer Science students at the Faculty of Sciences from the University of Porto. In particular, we extract their code property graphs and store them as CSV files along with the source code. The analysis of this data can enable, for instance, the generation of more concise and personalized feedback based on similar accepted submissions in the past, the identification of different strategies to solve a problem, and the understanding of a student's thinking process, among many other findings.
DOI: 10.17632/4g2xfsbmnr.1
title: Range map dataset for terrestrial vertebrates across Taiwan

description: This dataset provides up-to-date, high-precision species distribution maps for 379 terrestrial vertebrates in Taiwan. 
We used species distribution modeling as the base and then aggregated multiple open datasets describing species occurrence and environmental factors as data sources. Thereafter, we estimated the primary broad-scale and high spatial resolution species range maps using the MaxEnt modeling algorithm, and then consulted experts on each taxa to refine these maps.

There are three files in this dataset:
model_metadata.csv - metadata of models and information of species, including species taxonomic information, and model arguments.
range_maps.shp - species range maps in the shapefile format, each species has its own polygon.
DOI: 10.17632/j5zfp5vdz4.1
title: The Stream Daylighting Literature Review & The Stream Daylighting and Climate Change Literature Review Datasets (Datasets I and II)

description: These two datasets spread over two Microsoft Excel Documents. The first, The Stream Daylighting Literature Review Dataset (Dataset I) compiles information gathered from a systematic review of the literature sources on the daylighting of streams. In total, we reviewed 115 English language sources (with one exception: a Swiss-German Report on the City of Zürich's unique daylighting policy). The systematic review was combined with content analysis to extract from these sources the latent content in reference to the sources' less obvious characteristics and information that can be uncovered only by a thorough reading of each source’s text. This "Stream Daylighting Literature Review Dataset" also dubbed by our research team as Dataset I, is in the form of a Microsoft Excel document spreading over seven separate sheets that are united by a unique primary key (PK) number for each literature source. Dataset I consists in total of 19 variables that we extracted from the 115 literature sources of which 10 are manifest data in reference to the literature’s obvious and indisputable attributes, such as: authors’ names and affiliations, title and year of the source’s publication. The remaining nine are extracted from the sources’ latent content through careful reading, leading to notes that are then transferred and coded in the Excel document. The research team collected the latent data around four subject matters, namely: the literature sources’ underlying themes and sub-themes, the daylighting case studies/projects discussed, and the geographic coverage or scope addressed in the literature sources. Dataset I served as the backbone for the research project’s dashboard produced in Tableau --i.e., one of the manifestations of Dataset I in the form of visual analyses, which can be viewed through the following links: https://uwaterloo.ca/stream-daylighting/literature-review-database and/or https://public.tableau.com/profile/nathan.woodcock5796#!/ The second, The Stream Daylighting and Climate Change Literature Review Dataset (Dataset II) delves deeper into one of the latent content variables extracted from the literature’s sources namely, the climate change theme. Dataset II identifies how the 16 literature sources on stream daylighting discuss climate change, specifically: 1) How is stream daylighting addressed in relation to climate change in these sources? And how do these literature sources tackle climate adaptation and/or mitigation? This Dataset II is in the form of a Microsoft Excel document organized over nine columns. The PK number, each source's unique number, connects Datasets I and II. Role of the funding source: The funding for this research project was provided by the Social Sciences and Humanities Research Council of Canada (SSHRC) under file number 435-2016-0243. SSHRC was not involved in the study design nor in the collection, analysis and interpretation of data.
DOI: 10.17632/ng33vg479n.1
title: Experimental data on trial-by-trial AI assistance, feedback, human confidence and decisions during an AI-assisted decision-making chess puzzle task

description: The data are collected from a human subjects experiment to examine how human confidence in AI and self-confidence change and impact their decision-making during an AI-assisted decision-making task. The experimental task includes three practice and 30 experimental chess puzzle problems, which 100 participants are asked to solve with AI assistance. For each problem, the goal is to make the best next chess move given a board state. The participants first select an independent move (bmove1), receive AI suggestion (aisugg), make a final move (bmove2) , receive feedback on the final move (feedback2), and report their self-confidence (selfconf) and confidence in AI (aiconf). All of these data indicated in the parentheses are recorded in the dataset, as well as some other information including opponent's last move (wmove),  top seven moves with the highest evaluation scores (allgoodmoves), ranking of the AI suggestion (multiPV), goodness of the independent move (feedback1), chess board state before opponent's last move (fen before white move), and chess board state before the participants' move (fen before black move). There are two experimental conditions which differ in the order in which the AI performance (i.e., accuracy of AI suggestions) changes: 1) high-performing (80% accuracy) to low-performing AI (20% accuracy) and 2) low-performing (20%) to high-performing (80%) AI. Each CSV datafile ("data#_#") contains each participant's data, where the first # in the filename indicates the participant number and the second # indicates the condition number. For more detailed description of the dataset and the experiment, please refer to the Data In Brief article (publication in process) and the original research article (https://doi.org/10.1016/j.chb.2021.107018). This dataset can be utilized in various domains such as human-computer interaction, psychology, computer science, and team management in engineering/business that seek to understand human cognition and behavior in human-AI collaboration contexts.
DOI: 10.20387/bonares-40kc-2661
title: Provision of Metadata of European Agricultural Long-Term Experiments through BonaRes and EJP SOIL Collaboration

description: The dataset includes the meta-information of 616 LTEs from 30 different countries across Europe with a minimum duration of typically 20 years, including clustered information of the European LTEs in different categories (management operations, land use, duration, status, etc.). It consists of the updated version of the dataset published by Grosse et al., 2020 (https://doi.org/10.20387/BonaRes-3TR6-MG8R) but is extended by further LTE metadata, categories and research themes within a collaboration of BonaRes and EJP SOIL.

Research domain: Soil Sciences
DOI: 10.25919/943n-vk11
title: Australian chloride deposition rate (1937-2021)

description: Chloride deposition (kg/hectare/year) gridded at a resolution of 0.05° x 0.05° across Australia, in GeoTiff format. This collection supersedes https://doi.org/10.4225/08/545BEE54CD4FC Also included are results from a Monte-Carlo analysis indicating the uncertainty in the chloride deposition: standard deviation and skewness of deposition and log10(deposition), and 5th and 95th percentile of deposition, all in GeoTiff format. In these files chloride deposition has units kg/hectare/year. The dataset can be used for various purposes including: estimating groundwater recharge through the use of the chloride mass-balance method; catchment salt balance estimates; regional investigations of groundwater hydrochemistry; and, corrosion prediction.
DOI: 10.25919/m529-q062
title: Pipeline for simulating integrations

description: A computational pipeline for simulating integrations of a virus or vector genome into a host genome, as well as example data simulating 100 integrations of Adeno-Associated Virus 2 (AAV2) into human chromosome 1.
DOI: 10.5281/zenodo.4244926
title: Italian vineyards database

description: The database contains geo-spatial (block shape, block length/width ratio, mean and max slope) and management (training system, row spacing and headland size) information of 3686 sample vineyards throughout Italian territory.
DOI: 10.5281/zenodo.5820134
title: Combined Article Tables & Figures

description: This spreadsheet includes all the tables and figures presented in the paper: "Selected ‘Starter kit’ energy system modelling data for selected countries in Africa, East Asia, and South America (#CCG, 2021)"
DOI: 10.5281/zenodo.5851407
title: A Multilingual Dataset of COVID-19 Vaccination Attitudes on Twitter

description: This dataset consists of the IDs of 2,198,090 tweets collected from Western Europe, of which 17,934 are annotated with labels indicating the originators' affective vaccination stances, including Positive (PO), Negative (NG), Positive but dissatisfaction (PD), Neutral (NE) and Off-topic (OT). all_tweets.txt contains all the ids of the collected tweets, annotated_tweets.txt contains the ids of the annotated tweets and the categories they are annotated to.
DOI: 10.5281/zenodo.6024913
title: Supplementary files for Collection of Datasets with DNS over HTTPS Traffic

description: The DNS over HTTPS (DoH) is becoming a default option for domain resolution in modern privacy-aware software. Therefore, research has already focused on various aspects; however, a comprehensive dataset from an actual production network is still missing. In this paper, we present a novel dataset, which comprises multiple PCAP files of DoH traffic. The captured traffic is generated towards various DoH providers to cover differences of various DoH server implementations and configurations. In addition to generated traffic, we also provide real network traffic captured on high-speed backbone lines of a large Internet Service Provider with around half a million users. Network identifiers (excluding network identifiers of DoH resolvers) in the real network traffic (e.g., IP addresses and transmitted content) were anonymized, but still, the important characteristics of the traffic can still be obtained from the data that can be used, e.g., for network traffic classification research. The real network traffic dataset contains DoH and also non-DoH HTTPS traffic as observed at the collection points in the network. This repository provides supplementary files for the "Collection of Datasets with DNS over HTTPS Traffic" : <pre><code>─── supplementary_files | - Directory with supplementary files (scripts, DoH resolver list) used for dataset creation ├── chrome | - Generation scripts for Chrome browser and visited websites during generation ├── doh_resolvers | - The list of DoH resolvers used for filter creation during ISP backbone capture ├── firefox | - Generation scripts for Firefox browser and visited websites during generation └── pcap-anonymizer | - Anonymization script of real backbone captures</code></pre> Collection of datasets: <strong>DoH-Gen-F-AABBC</strong> --- https://doi.org/10.5281/zenodo.5957277 <strong>DoH-Gen-F-FGHOQS</strong> --- https://doi.org/10.5281/zenodo.5957121 <strong>DoH-Gen-F-CCDDD</strong> --- https://doi.org/10.5281/zenodo.5957420 <strong>DoH-Gen-C-AABBCC </strong>--- https://doi.org/10.5281/zenodo.5957465 <strong>DoH-Gen-C-DDD</strong> -- https://doi.org/10.5281/zenodo.5957676 <strong>DoH-Gen-C-CFGHOQS</strong> --- https://doi.org/10.5281/zenodo.5957659 <strong>DoH-Real-world</strong> --- https://doi.org/10.5281/zenodo.5956043
description: This research was funded by the Ministry of Interior of the Czech Republic, grant No. VJ02010024: Flow-Based Encrypted Traffic Analysis and also by the Grant Agency of the CTU in Prague, grant No. SGS20/210/OHK3/3T/18 funded by the MEYS of the Czech Republic, and also by Brno University of Technolgy, Faculty of Information Technology internal grant FIT-S-20-6293, and also by Technology Agency of the Czech Republic, grant No. FW03010099: Context-based Encrypted Traffic Analysis Using Flow Data.
DOI: 10.5281/zenodo.6402160
title: Maritime routes and vessel tracklet dataset for vessel-to-route association

description: With an ever-increasing number of vessels at sea, the modelling, analysis and visualisation of maritime traffic are of paramount importance to support the monitoring tasks of maritime stakeholders. Sensors have been developed in this respect to track vessels and capture the maritime traffic at the global scale. The Automatic Identification System (AIS) is transmitting maritime positional and nominative information at highest frequency rate, making it a valuable source for maritime traffic modelling. From an original AIS dataset covering the area of Brest, France, we extracted a set of 17 maritime routes, connecting ports in this area. Two different representations for the routes are provided: (1) clusters of AIS contacts, and (2) route prototypes, representing the nominal trajectory of the vessels following the route. Additionally, a set of tracklets (built by five consecutive AIS contacts from the same vessel trajectory) has been extracted from the set of routes and the original dataset, and labelled either with the route name to which they belong or as off-route tracklets. This dataset provides thus some ground truth on the routes followed by vessels and is aimed at testing and validating vessel-to-route or track-to-route association algorithms.
DOI: 10.17632/6gjyr6vm9g.1
title: Dataset_RTOCs_Datainbrief

description: Data in Brief dataset: Hospitality Education Evolution Observed in Online Learning Dataset.  Data were collected by recruiting 956 respondents; 926 responses were adopted after the valid screening through a cooperative survey company. A random sampling of targeted groups was required when outsourcing the data collection to the survey company Wenjuanxing, a platform with a majority of population database providing functions equivalent to Amazon Mechanical Turk. We asked the company to deliver the designed questionnaire to teachers and students in hospitality programs. Reliability and validity of all constructs showed that the questionnaire is proper for measurement.