cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/fnf8b85kr6.1
title: Behaviour Biometrics Dataset

description: The dataset provides a collection of behaviour biometrics data (commonly known as Keyboard, Mouse and Touchscreen (KMT) dynamics).  The data was collected for use in a FinTech research project undertaken by academics and researchers at Computer Science Department, Edge Hill University, United Kingdom. The project called CyberSIgnature uses KMT dynamics data to distinguish between legitimate card owners and fraudsters.  An application was developed that has a graphical user interface (GUI) similar to a standard online card payment form including fields for card type, name, card number, card verification code (cvc) and expiry date. Then, user KMT dynamics were captured while they entered fictitious card information on the GUI application. 

The dataset consists of 1,760 KMT dynamic instances collected over 88 user sessions on the GUI application.  Each user session involves 20 iterations of data entry in which the user is assigned a fictitious card information (drawn at random from a pool) to enter 10 times and subsequently presented with 10 additional card information, each to be entered once. The 10 additional card information is drawn from a pool that has been assigned or to be assigned to other users.  A KMT data instance is collected during each data entry iteration. Thus, a total of 20 KMT data instances (i.e., 10 legitimate and 10 illegitimate) was collected during each user entry session on the GUI application. 

The raw dataset is stored in .json format within 88 separate files. The root folder named `behaviour_biometrics_dataset' consists of two sub-folders `raw_kmt_dataset' and `feature_kmt_dataset'; and a Jupyter notebook file (kmt_feature_classificatio.ipynb). Their folder and file content is described below: 

--  `raw_kmt_dataset': this folder contains 88 files, each named `raw_kmt_user_n.json', where n is a number from 0001 to 0088. Each file contains 20 instances of KMT dynamics data corresponding to a given fictitious card; and the data instances are equally split between legitimate (n = 10) and illegitimate (n = 10) classes. The legitimate class corresponds to KMT dynamics captured from the user that is assigned to the card detail; while the illegitimate class corresponds to KMT dynamics data collected from other users entering the same card detail.

--  `feature_kmt_dataset': this folder contains two sub-folders, namely: `feature_kmt_json' and `feature_kmt_xlsx'. Each folder contains 88 files (of the relevant format: .json or .xlsx) , each named `feature_kmt_user_n', where n is a number from 0001 to 0088. Each file contains 20 instances of features extracted from the corresponding `raw_kmt_user_n' file including the class labels (legitimate = 1 or illegitimate = 0). 

--  `kmt_feature_classification.ipynb': this file contains python code necessary to generate features from the raw KMT files and apply simple machine learning classification task to generate results. The code is designed to run with minimal effort from the user.
DOI: 10.17632/whdgyc7j5z.1
title: Data for: Consumer Demand for Ethical Products and the Role of Cultural Worldviews: The Case of Direct-Trade Coffee

description: Full dataset
DOI: 10.17632/s69rwrhprm.1
title: Single cell transcriptomics of organoids

description: Organoids were pooled and each cell aggregate were minced using a sterile scalpel. The dissociated cells were strained using 40 µm cell strainer and collected in a 15 ml falcon tube. The cells were kept on ice and final concentration was approximately 1000 cells/µl with > 90% cell viability. scRNA-Seq cDNA library was prepared using the chromium single cell system (10X Genomics). 10,000-16,000 cells per sample were added to a single cell master mix, following the Chromium Single Cell 3’ Reagent kits v3.1 protocol. The libraries were sequenced paired end on Illumina NovaSeq 6000 to a read depth of more than 30,000 reads per cell. All samples had sequencing yields of more than 143 million read per sample. The sequencing run was setup as a 28 cycles + 90 cycles non-symmetric run. Demultiplexing was done allowing 1 mismatch in the barcodes. Over 95.5% of bases in the barcode regions have Q30 or above and at least 93.2% of bases in the read have Q30 or above. More than 95.4% of bases in the UMI have Q30 or above. The analysis was performed with the Cell Ranger 6.1.2 software using the default parameters. Cells with extremely low number of UMI counts were filtered out. The aggregated.tar files contain the gene matrix files for performing single cell-RNAseq analysis.
DOI: 10.17632/5kn9m9cwg5.2
title: Supplementary data of "Blood Lipid Metabolic Profiles and Causal Links to Site-Specific Cancer Risks"

description: Observational and Mendelian randomization (MR) studies have established links between dyslipidemia and select cancer susceptibilities. However, there is a lack of comprehensive exploration of causal relationships spanning diverse cancer types. Here, we conducted a two-sample MR analysis to elucidate the causative connections between 9 blood lipid metabolic profiles (namely, adiponectin, leptin, lipoprotein A, apolipoprotein A1, apolipoprotein B, cholesterol, triglycerides, LDL-cholesterol, and HDL-cholesterol) and 21 site-specific cancer risks. Our findings reveal genetically predicted adiponectin levels to be associated with a reduced ovarian cancer risk, while genetically determined leptin increases bladder cancer risk but decreases prostate cancer risk. Lipoprotein A elevates risk of prostate cancer while diminishing risk of endometrial cancer, while apolipoprotein A1 heightens risks of breast and cervical cancers. Furthermore, elevated levels of cholesterol are positively correlated with kidney cancer, and triglycerides demonstrate a positive association with non-melanoma skin cancer but a negative association with breast cancer. Protective effects of genetically predicted LDL-cholesterol on endometrial cancer and adverse effects of HDL-cholesterol on breast cancer are also observed. Our study conclusively establishes that blood lipid metabolic profiles exert causal effects on cancer susceptibility, providing more robust evidence for cancer prevention and prompting contemplation regarding the future health of the human populace.
DOI: 10.17632/945z9xkc8d.1
title: Fake News Dataset

description: This is some collections of fake news dataset that has been cleaned, augmented, and preprocessed. Each of the datasets has been split into train and test data with an 80:20 ratio.
There are four folders in the file:

1. ISOT Fake News Dataset
H. Ahmed, I. Traore, S. Saad, Detection of Online Fake News Using N-Gram Analysis and Machine Learning Techniques, in: Lect. Notes Comput. Sci. (Including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), 2017: pp. 127–138. https://doi.org/10.1007/978-3-319-69155-8_9.

2. Fake News Dataset
UTK Machine Learning Club, Fake News, (2018). https://www.kaggle.com/c/fake-news/overview.

3. Fake or Real News Dataset
G. McIntire, Fake or Real News, (2017). https://github.com/joolsa/fake_real_news_dataset.

4. Fake News Detection Dataset
Jruvika, Fake News Detection, (2017). https://www.kaggle.com/jruvika/fake-news-detection/version/1.
DOI: 10.15468/dl.ydft45
title: Occurrence Download

description: A dataset containing 2218 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pyrus pyrifolia (Burm.fil.) Nakai",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 2218 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009382-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/3jh73nmxf2.1
title: Data for: When trees don't act their age: size-deterministic tree ring standardization for long-term trend estimation in shade tolerant tree

description: Tree ring data and associated metadata from seven mature sugar maple stands in Ontario, Canada. Data is associated with the following publication: Dietrich, R. and Anand, M. (2019). When trees don't act their age: size-deterministic tree ring standardization for shade tolerant tree species. Biogeosciences. (In print).
DOI: 10.17632/z45txpdp7f.2
title: Graph-Based Social Media Data on Mental Health Topics

description: This dataset is structured as a graph, where nodes represent users and edges capture their interactions, including tweets, retweets, replies, and mentions. Each node provides detailed user attributes, such as unique ID, follower and following counts, and verification status, offering insights into each user's identity, role, and influence in the mental health discourse. The edges illustrate user interactions, highlighting engagement patterns and types of content that drive responses, such as tweet impressions. This interconnected structure enables sentiment analysis and public reaction studies, allowing researchers to explore engagement trends and identify the mental health topics that resonate most with users.

The dataset consists of three files:
1. Edges Data: Contains graph data essential for social network analysis, including fields for UserID (Source), UserID (Destination), Post/Tweet ID, and Date of Relationship. This file enables analysis of user connections without including tweet content, maintaining compliance with Twitter/X’s data-sharing policies.
2. Nodes Data: Offers user-specific details relevant to network analysis, including UserID, Account Creation Date, Follower and Following counts, Verified Status, and Date Joined Twitter. This file allows researchers to examine user behavior (e.g., identifying influential users or spam-like accounts) without direct reference to tweet content.
3. Twitter/X Content Data: This file contains only the raw tweet text as a single-column dataset, without associated user identifiers or metadata. By isolating the text, we ensure alignment with anonymization standards observed in similar published datasets, safeguarding user privacy in compliance with Twitter/X's data guidelines. This content is crucial for addressing the research focus on mental health discourse in social media. (References to prior Data in Brief publications involving Twitter/X data informed the dataset's structure.)
DOI: 10.17632/858bmcf7j6.1
title: GeoTaichi: A Taichi-powered high-performance numerical simulator for multiscale geophysical problems

description: This study introduces GeoTaichi, an open-source high-performance numerical simulator designed for addressing multiscale geophysical problems. By leveraging the power of the Taichi parallel language, GeoTaichi maximizes the utilization of modern computer resources on multicore CPU and GPU architectures. It offers robust and reliable modules for the discrete element method (DEM), material point method (MPM), and coupled material point-discrete element method (MPDEM). These modules enable efficient solving of large-scale problems while being implemented in pure Python. The design philosophy of GeoTaichi focuses on creating a framework that is readable, extensible, and user-friendly. This paper highlights the coupling procedure of MPDEM, the code structures, and the most important features of GeoTaichi. Rigorous benchmark tests have been conducted to verify the validity and robustness of GeoTaichi. Additionally, the performance of GeoTaichi is compared with similar software tools in the field, underscoring a notable improvement in both computational efficiency and memory savings when compared to existing alternatives.
DOI: 10.17632/2rjd8zy9rv.1
title: Development of the Digital Parental Mediation Scale - Survey Data (2020)

description: The goal of this study was to develop and validate a measure of parents’ attitudes about the mediation of digital technology. An internet-based survey was administered to 554 parents of children and adolescents in the US. Exploratory bifactor analysis revealed one general factor and four digital-specific factors: discursive mediation, restrictive mediation and monitoring, participatory mediation, and mediation by modeling. Confirmatory factor analysis supported a bifactor model of the Digital Parental Mediation Scale (DPMS); the general factor explained shared variance related to parenting style and skills in general, while the mediation factor represented digital-specific attitudes. Mediation factors were predicted differentially by perceived parenting efficacy and influence, parental worry about technology, child age, and parent and child technology use patterns.
DOI: 10.17632/9pkxzpcsm7.1
title: (Dataset) Web accessibility COVID-19 website

description: Web accessibility analysis using data from websites with information from covid 19.
DOI: 10.17632/jwkk44trj3.2
title: Panel Data Generated from Governance, Trade, and Competitiveness Indicators of World Bank Group Platforms

description: This dataset was compiled using the hdData360r R package.

Please cite as:
• Kurbucz, M. T. (2023). hdData360r: A high-dimensional panel data compiler for governance, trade, and competitiveness indicators of World Bank Group platforms. SoftwareX, 21, 101297.

More information can be found at:
• https://github.com/mtkurbucz/hdData360r
DOI: 10.17632/jrtt73npzw.1
title: Fission fragment decay simulations with the CGMF code

description: The CGMF code implements the Hauser-Feshbach statistical nuclear reaction model to follow the de-excitation of fission fragments by successive emissions of prompt neutrons and γ rays. The Monte Carlo technique is used to facilitate the analysis of complex distributions and correlations among the prompt fission observables. Starting from initial configurations for the fission fragments in mass, charge, kinetic energy, excitation energy, spin, and parity, Y(A,Z,KE,U,J,π), CGMF samples neutron and γ-ray probability distributions at each stage of the decay process, conserving energy, spin and parity. Nuclear structure and reaction input data from the RIPL3 library are used to describe fission fragment properties and decay probabilities. Characteristics of prompt fission neutrons, prompt fission γ rays, and independent fission yields can be studied consistently. Correlations in energy, angle and multiplicity among the emitted neutrons and γ rays can be easily analyzed as a function of the emitting fragments. In its current version, CGMF is limited to certain spontaneous fission reactions on Pu and Cf isotopes, as well as neutron-induced fission reactions up to 20 MeV on U, Np, and Pu isotopes.
DOI: 10.17632/g4kznvfh67.1
title: TPCF

description: Tensile and installation data
DOI: 10.17632/h8s5mn52j6.1
title: Multispectral Images on Paddy- Sri Lanka

description: There are 336 multispectral images in this dataset. Each shot of the multispectral camera captures four bands (green, red, red edge, and near-infrared) with RGB image in separated JPG files. 20MP, 4/3 CMOS RGB camera captures the RGB images. The names of the multispectral images are organized as “DJI_DateTime_imgNumber_MS_bandNumber''. For example, “DJI_20230814123320_0001_MS_G'' is band 1 (green) of image number 001 of the flight on August 14, 2023, at 12.33.20 p.m. and “DJI_20231005124002_0001_D” is RGB image number 001 of the flight on October 05, 2023, at 12.40.02 p.m.
DOI: 10.17632/jx37kt2rjj.1
title: Flood vulnerability index of Korea in 2022

description: This data set contains both raw and processed data from the flood vulnerability assessment of 228 districts in Korea as of 2022. The study aims to analyze regional disparities in flood vulnerability using a multidimensional, indicator-based approach that incorporates regional resilience. Based on the IPCC's climate change vulnerability concept, 30 indicators across social, economic, physical, and infrastructural dimensions were constructed. The raw data were standardized and weighted using the entropy method to enhance objectivity.
The results indicate that highly vulnerable areas often exhibit high social and physical sensitivity, combined with low economic adaptive capacity. Additionally, it was found that 69.23% of the highly vulnerable districts are located in metropolitan areas, suggesting that urban regions are at greater risk of flood damage when social, economic, physical, and infrastructural factors are collectively considered. Moreover, over 90% of the vulnerable districts outside metropolitan areas were identified as population-declining regions, highlighting the potential negative impact of depopulation on local flood resilience.
DOI: 10.17632/cn7vtxdm97.1
title: Online learning during COVID-19 Pandemic- Dataset from Vietnam

description: The dataset provides information on different aspects of students’ online learning experience during the COVID-19 school closure in Vietnam. Data collection was enabled via the use of an online survey that was administered between September and December 2021 to 5,327 Grade 6 to Grade 9 students (2,898 females and 2,429 males) from five provinces. The survey tool consisted of 64 selected-response and Likert items that were informed by Picciano’s (2021) Online Education Framework and Theories and an extensive literature review of online education during the COVID-19 pandemic. The data collected were categorized into four themes, namely (a) students’ demographic information, (b) students’ access to online learning platforms, (c) online learning activities, modalities, and assessments, and (d) students’ perceptions of the effectiveness of online learning.

Insights from the dataset can benefit local and international researchers, policymakers, and educators who are interested in researching or developing support, intervention, or adjustment programs to enhance educational quality via online learning, particularly in COVID-19 situations.



The dataset provides information about middle school students' online learning experiences during school closure time. The data covers comprehensive dimensions from students' sharing of online learning from learning condition, learning reality to effectiveness. The questionnaire for this data is anchored in Online Education Framework and Theories and the literature review of online education in the area of COVID-19 Pandemic. The questionnaire consists of four main domains. The first domain is about students' demographic information. The second domain mentions students' online learning conditions with basic elements of learning devices, equipment, used digital platforms and applications, and their technical skills. The third domain displays students' experiences of learning activities, modality, and assessment. The last domain is about students' evaluation of online learning effectiveness. 
The data was collected online via google form from September 2021 to December 2021. 5327 middle school students participated in the survey, with 2898 females and 2429 males living in various areas of Vietnam such as rural areas, urban areas, and mountainous areas. The data was mainly collected in 5 provinces in Vietnam, including Hanoi, Can Tho, Nam Dinh, Dak Lak and  Quang Binh
DOI: 10.15468/dl.uhu3za
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((35.89842 -25.27817,58.10158 -25.27817,58.10158 -9.72183,35.89842 -9.72183,35.89842 -25.27817))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Perrierbambus A.Camus"
 ]
}

 The dataset includes 31 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009383-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/jxwsp9ng5c.4
title: Datasets for Drone Routing Problem

description: This dataset is set for paper "A learning based algorithm for drone routing"
DOI: 10.17632/n35gn9w8nc.1
title: Extreme Weather Events and Spatio-temporal Characterization of Climate Change Variables in Bangladesh during 1975 - 2019

description: Bangladesh is susceptible to climate change, thus a detailed study, including the analyses of trends, sub-trends, extreme events and indices was conducted to obtain a complete picture of the climate change pattern in Bangladesh utilizing daily rainfall, maximum, minimum and average temperature data of 26 stations from 1975 to 2019 using R 4.0.2 software. For the trend analysis Mann Kendal (MK), modified Mann Kendall (mMK), Innovative Trend Analysis (ITA) and Sen’s slope methods were used. Sub-trend analysis was conducted using ITA. Standard Anomaly Index (SAI) has been used to identify the frequency and severity of extreme events. ClimPACT2 software was used to check the homogeneity and calculate the extremes of temperature and rainfall data. Our analysis showed that during the last four decades, climate variables changed their patterns and trend heterogeneously over Bangladesh. Most stations showed decremental rainfall trend when central part of the country showed a substantial decrease. The northern and central parts of the country showed significant growth of trend for annual average temperature. The temperature in the monsoon season increased, whereas those in dry season decreased. The rainfall and maximum temperature were inversely related during monsoon whereas during dry season both of them decrease. The pre-monsoon and post-monsoonal rainfall also showed decreasing trends, indicating prevailing drought conditions especially in northern and central parts of the country. The SAI analysis showed alternating drought and wet years in almost all the stations. In the past 20 years, the country’s western region experienced more drought years than before whereas the coastal region experienced more wet years. The analysis of climate extreme indices suggests that, Consecutive Dry Days (CDD), Hot Days (TX90P) and Hot Nights (TN90P) show significant increasing trend throughout the country. The agricultural productivity, water resource management and food security are anticipated to benefit from this study.

All the raw and analyzed data of this study is attached here