cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e225821
title: Nuclear Biscuit

description: These files contain transcripts of participant actions in a Virtual Reality experience and the post-experience interview. The ethics review committee of Princeton University
approved these studies. 

"National Security Crisis Decision
Making" (13957) was approved on October 8, 2021, and "National
Security Crisis Decision Making – Washington, DC" (14128) was approved on
October 22, 2021, under Principal Investigator Alexander Glaser. Written informed consent for inclusion in
this research was obtained from all participants prior to participation in the
study.
DOI: 10.3886/e225821v1
title: Nuclear Biscuit

description: These files contain transcripts of participant actions in a Virtual Reality experience and the post-experience interview. The ethics review committee of Princeton University
approved these studies. 

"National Security Crisis Decision
Making" (13957) was approved on October 8, 2021, and "National
Security Crisis Decision Making – Washington, DC" (14128) was approved on
October 22, 2021, under Principal Investigator Alexander Glaser. Written informed consent for inclusion in
this research was obtained from all participants prior to participation in the
study.
DOI: 10.26030/6wmk-9m06
title: Draft Genome Sequences of Two Fusarium oxysporum Isolates Cultured from Infected Zinnia hybrida Plants Grown on the International Space Station

description: Draft genome sequences of two Fusarium oxysporum isolates cultured from infected Zinnia hybrida plants grown on the International Space Station
DOI: 10.18120/62j6-m215
title: ICMS Safety
DOI: 10.6084/m9.figshare.28745801
title: JAGS model to predict disease prevalence with imperfect detection.

description: JAGS model to predict disease prevalence with imperfect detection.
DOI: 10.3886/icpsr03334.v2
title: Aging, Status, and Sense of Control (ASOC), 1995, 1998, 2001 [United States]
title: Version 2

description: The Aging, Status, and Sense of Control (ASOC) was conducted
 during 1995, 1998 and 2001 and examined the relationship between age and
 changes in the sense of control over one's life. Part I contains data for
 Waves I and II. Respondents were queried about their physical health,
 including activities of daily living such as shopping, walking, and doing
 housework, along with medical conditions such as heart disease, high blood
 pressure, lung disease, breast cancer, diabetes, arthritis or rheumatism,
 osteoporosis, and allergies or asthma. Questions regarding mental health
 investigated difficulties staying focused, feelings of sadness or anxiety,
 and enjoyment of life. Respondents were also asked about their health
 behaviors, including use of tobacco and alcohol, frequency of exercise, use
 of medical services including insurance coverage, and the number of
 prescription medications used. Also examined was respondents' sense of
 control over their lives, including social support and participation, and
 history of adversity, which covered such topics as home or apartment
 break-ins or assaults, major natural disasters, unemployment longer than
 six months, and times without enough money for clothes, food, rent, bills,
 or other necessities. Demographic questions included age, sex, marital
 status, education, work status, marital and family relations, and
 socioeconomic status. Wave III (Part 2) was collected in 2001 and contains
 data on the same questions such as physical health, mental health and
health behaviors.
description: Probability sample with oversampling of persons aged 60 and
older.
description: Datasets: 
DS0: Study-Level Files
DS1: Waves I and II
DS2: Wave III
description: English-speaking adults aged 18 or older in the United
States.
description: telephone interview(1) These are longitudinal data. Answers from the first
 wave of interviews in 1995 (N=2,593) were merged with those from the second
 wave in 1998 (N=1,378 reinterviewed). Wave II can be identified by the
 variable INTYR2. (2) Part 2 (Wave III N=1,444) can be merged with Part 1 on
CASEID. The same questions were asked in all three waves.
DOI: 10.34740/kaggle/dsv/11315212
title: VR Immersion EEG and ECG Data for Stress Study
DOI: 10.3886/icpsr04354.v1
title: Resources for Enhancing Alzheimer's Caregiver Health (REACH II), 2001-2004
title: Version 1

description: Built upon the findings of RESOURCES FOR ENHANCING
ALZHEIMER'S CAREGIVER HEALTH, 1996-2001, BASELINE AND FOLLOW-UP DATA
[ICPSR 3678], REACH II designed and tested a single multi-component
intervention among family caregivers of persons with Alzheimer's
disease or related disorders. The overall objectives were (1) to
identify and reduce modifiable risk factors among diverse family
caregivers of patients with Alzheimer's Disease or a related disorder,
(2) to enhance the quality of care provided to the care recipients,
and (3) to enhance the well-being of the caregivers. REACH II is the
first project to simultaneously test a comprehensive caregiver
intervention in three distinct racial/ethnic groups: Hispanic/Latino,
Black/African-American, and White/Caucasian. The intervention was
based on a risk-appraisal approach in which five areas of
risk--depression, burden, self-care, social support, and patient
problem behaviors--that are central to caregiver well-being and
quality of life were matched to corresponding intervention
components. These components included education, skills to manage
troublesome care-recipient behaviors, social support, cognitive
strategies for reframing negative emotional responses, and strategies
for enhancing healthy behaviors and managing stress. Consistent with
this approach, the primary outcome was a multivariate quality of life
indicator that assessed caregiver depression, burden, self-care,
social support, and patient problem behaviors. Two hallmarks of
caregiver intervention studies--caregiver clinical depression and
patient institutionalization--were assessed as secondary outcomes. The
dataset names listed in this collection include the shortened name of
the form administered.
description: Convenience sample
description: Datasets: 
DS0: Study-Level Files
DS1: AE: Caregiver/Care Recipient Acute Baseline Alerts/Adverse Events Forms Guidebook
DS2: AF: Acute Baseline Alerts/Adverse Events Follow-Up Report Guidebook
DS3: BA: Baseline Battery Guidebook
DS4: BR: Bereavement Battery Guidebook
DS5: DA: Intervention Delivery Assessment
DS6: DC: Discontinued Battery
DS7: FO: Follow-Up Battery
DS8: IC: Interventionist Characteristics
DS9: OP: Off Protocol Form
DS10: PL: Placement Battery
DS11: RF: Randomization Form
DS12: RT: Care Recipient Tracking Form
DS13: SC: Screening Form
DS14: SP: Short Portable Mental Status Questionnaire (SPMSQ)
description: Family caregivers of people with Alzheimer's disease or a
related dementia who reside in noninstitutional settings.
description: personal interviewAll datasets can be linked using the variable: ID.
Dataset 1 (AE: Caregiver/Care Recipient Acute Baseline Alerts/Adverse
Events) can be linked to Dataset 2 (AF: Acute Baseline Alerts/Adverse
Events Follow-Up Report) using variables: ID, EVENT, and EVEDAT.
DOI: 10.3886/icpsr03255.v2
title: Religion, Aging, and Health Survey, 2001, 2004 [United States]
title: Version 2

description: This data collection looks at religion, self-rated health,
 depression, and psychological well-being in a sample of older Blacks
 and older Whites (aged 65 and over) within the United States.
 Questions were asked regarding religious status, activities, and
 beliefs among those who currently practice the Christian faith, those
 who used to be Christian but are not now, and those who have never
 been associated with any religion during their lifetimes. Demographic
 variables include age, race, sex, education, and income. Wave II was
 collected in 2004 and reinterviewed 1,024 respondents. There were 75
 respondents who refused to participate, 112 who could not be located,
 70 that were too ill for participation, 11 who had moved to nursing
homes and 208 were deceased.
description: The variable "weight" should be used with Wave I data. Wave
 II contains the variable "postwtw2" which should be used when both
 races are combined and the variable "genwtw2" which is to be used when
looking within either race.
description: Random probability sample.
description: Datasets: 
DS0: Study-Level Files
DS1: Wave I
DS2: Wave II
description: All Black or White, English-speaking household
 (noninstitutionalized) residents aged 66 and over in the United States
in 2001.
description: face-to-face interviewWave I and Wave II may be merged together on the
variable ID.
DOI: 10.6073/pasta/f1e4cbcd79ebbbb0b0cbb79ab2ff8901
title: MCR LTER: Coral Reef: Coupled Natural-Human Systems: GPS Benthic Data

description: This dataset includes cover of benthic organisms and substrates in more than 600,000 photographic samples of Moorea’s lagoon habitats, collected between 2018 and 2021. In summer of each year swimmers towed downward facing cameras, taking 1.5 photos per second of habitats they passed over. The resulting pictures were processed through a computer vision algorithm (CoralNet), resulting in percent cover estimates in each photo of organisms such as coral and algae and substrates such as sand and rubble. These data were georeferenced based on simultaneously collecting GPS data. Data are presented here on the scale of the photograph, and are also aggregated to the scale of a minute of sampling and a transect of swimming. The latter scales are chosen to coincide with fish counting data which was simultaneously collected but is presented in a different data set (EDI data package ID: knb-lter-mcr.4013.1) doi:10.6073/pasta/ff3de88334edda65fef26de45ff26c1d
 These data were collected as part of CNH-L: Multiscale Dynamics of Coral Reef Fisheries: Feedbacks Between Fishing Practices, Livelihood Strategies, and Shifting Dominance of Coral and Algae (BCS-1714704) with additional support from the Moorea Coral Reef LTER (OCE- 1637396).
DOI: 10.25574/29814
title: Chandra X-ray Observatory ObsId 29814

description: Probing the First Gamma-ray Bursts with Chandra
DOI: 10.6084/m9.figshare.28745813
title: Hematoxylin and eosin (H&E) stained ovarian tissue images from Foxl2 haploinsufficiency model mice

description: H&E-stained histological images of ovarian tissue collected from Foxl2 haploinsufficiency model mice.
DOI: 10.25824/redu/r0c4wy
title: Concentrations of outdoor total volatile organic compounds in Barão Geraldo, Campinas, Brazil

description: This file contains the concentrations of Total volatile organic compounds (TVOC) outdoors in Barão Geraldo, Campinas, Brazil. The data was collected through the ARDUÍNO NANO microcontroller, CCS811 micromachined metal oxide (MOX) gas sensor for air quality monitoring, with a TVOC range from 0ppb to 1187ppb (0 ppm to 1.187ppm). The sensor, while not discriminating the quantity and diversity of VOCs in the air, provides a low-cost technique for real-time air quality monitoring. The dataset shows hourly outdoor TVOC concentrations over one year (2022).
DOI: 10.15139/s3/qyttgv
title: Replication Data for: Food Waste Among Young Adults: Behaviors, Barriers, and Opportunities for Intervention

description: This repository includes the dataset, Stata do files, and survey codebook to reproduce the analysis of the manuscript "Food Waste Among Young Adults: Behaviors, Barriers, and Opportunities for Intervention." This was a cross-sectional online survey with a convenience sample of 2,132 US young adults ages 18-25 years old. The survey measured self-reported food waste, difficulty reducing food waste, food waste-related behaviors, perceptions, intentions, and sociodemographic characteristics.
DOI: 10.5281/zenodo.15170519
title: Tech Trends from The Guardian: Articles Dataset

description: Dataset generat mitjançant tècniques de web scraping, recollint titulars i metadades de notícies de la secció "Technology" del diari The Guardian. S'utilitza amb finalitats educatives dins del Màster en Ciència de Dades de la UOC.
DOI: 10.5281/zenodo.15170520
title: Tech Trends from The Guardian: Articles Dataset

description: Dataset generat mitjançant tècniques de web scraping, recollint titulars i metadades de notícies de la secció "Technology" del diari The Guardian. S'utilitza amb finalitats educatives dins del Màster en Ciència de Dades de la UOC.
DOI: 10.25574/30879
title: Chandra X-ray Observatory ObsId 30879

description: Probing the First Gamma-ray Bursts with Chandra
DOI: 10.25574/30880
title: Chandra X-ray Observatory ObsId 30880

description: Probing the First Gamma-ray Bursts with Chandra
DOI: 10.6073/pasta/ff3de88334edda65fef26de45ff26c1d
title: MCR LTER: Coral Reef: Coupled Natural-Human Systems: GPS-enabled survey of fish in Moorea’s lagoons

description: This dataset includes counts and sizes of fish within Moorea’s lagoons, with more than 130,000 fish recorded between 2018 and 2021. In summer of each year observers swim through Moorea’s lagoons, observing a 5-m wide swath and recording species and sizes of fish encountered in every minute of swim (about 10 linear meters of sampling). The fish counts are limited to a fixed species list (57 taxa) which was chosen to capture most of the reef associated species targeted in Moorea’s fishery, as well as important herbivores. Only fish larger than 10 cm were recorded, a size chosen to match the small end of fish observed in the catch. The resulting counts were georeferenced based on simultaneously collecting GPS data. Data are presented here on the scale of a minute of sampling. This scale coincides with benthic data which was simultaneously collected but is presented in a different data set (EDI data package: knb-lter-mcr.4014.1) doi:10.6073/pasta/f1e4cbcd79ebbbb0b0cbb79ab2ff8901
 These data were collected as part of CNH-L: Multiscale Dynamics of Coral Reef Fisheries: Feedbacks Between Fishing Practices, Livelihood Strategies, and Shifting Dominance of Coral and Algae (BCS-1714704) with additional support from the Moorea Coral Reef LTER (OCE- 1637396).
DOI: 10.5281/zenodo.15167847
title: AI-Augmented SAR for Ground Deformation Under External Forces Datasets

description: Please note that the Zenodo record is currently under embargo and the files are not yet publicly accessible. It will be made publicly available once the scientific article is published. Upon your request, access permission can be evaluated and granted accordingly.


 

AI-Augmented SAR for Ground Deformation Under External Forces Datasets is a comprehensive dataset that compiles bibliometric and systematic literature review data on the monitoring of ground deformation under the influence of external forces using Synthetic Aperture Radar (SAR) technologies and Artificial Intelligence (AI) algorithms.

📁 Dataset Contents:





Bibliometric_Analysis_Results.xlsx→ Detailed outputs of the bibliometric analysis.




Bibliometrics_Data.zip→ Sub-level bibliometric data including author productivity, citation statistics, and content analyses (e.g., title, abstract, and keyword lengths).




Data_Raw.zip→ Raw datasets retrieved from Web of Science (WOS) and Scopus databases.




DOI_Algorithms_Metrics.xlsx→ Comparative performance data and success metrics (e.g., R², RMSE, MAE, AUC) of AI algorithms used in the 62 reviewed articles.




DOI_External_Forces.xlsx→ Classification of external forces (tectonic, hydrological, anthropogenic, climatic, etc.) modeled in the 62 reviewed articles.




DOI_Weaknesses_Suggestions.xlsx→ Methodological limitations and future research suggestions reported by the authors in the 62 reviewed studies.



This dataset provides a valuable resource for researchers aiming to conduct a comprehensive assessment of SAR+AI-based deformation monitoring literature spanning the years 1984 to 2024.
DOI: 10.5281/zenodo.15167848
title: AI-Augmented SAR for Ground Deformation Under External Forces Datasets

description: Please note that the Zenodo record is currently under embargo and the files are not yet publicly accessible. It will be made publicly available once the scientific article is published. Upon your request, access permission can be evaluated and granted accordingly.


 

AI-Augmented SAR for Ground Deformation Under External Forces Datasets is a comprehensive dataset that compiles bibliometric and systematic literature review data on the monitoring of ground deformation under the influence of external forces using Synthetic Aperture Radar (SAR) technologies and Artificial Intelligence (AI) algorithms.

📁 Dataset Contents:





Bibliometric_Analysis_Results.xlsx→ Detailed outputs of the bibliometric analysis.




Bibliometrics_Data.zip→ Sub-level bibliometric data including author productivity, citation statistics, and content analyses (e.g., title, abstract, and keyword lengths).




Data_Raw.zip→ Raw datasets retrieved from Web of Science (WOS) and Scopus databases.




DOI_Algorithms_Metrics.xlsx→ Comparative performance data and success metrics (e.g., R², RMSE, MAE, AUC) of AI algorithms used in the 62 reviewed articles.




DOI_External_Forces.xlsx→ Classification of external forces (tectonic, hydrological, anthropogenic, climatic, etc.) modeled in the 62 reviewed articles.




DOI_Weaknesses_Suggestions.xlsx→ Methodological limitations and future research suggestions reported by the authors in the 62 reviewed studies.



This dataset provides a valuable resource for researchers aiming to conduct a comprehensive assessment of SAR+AI-based deformation monitoring literature spanning the years 1984 to 2024.
DOI: 10.5281/zenodo.15170515
title: Improving Business Processes with Blockchain - Evaluation Results

description: This repository contains the results of the evaluation of the tool SecBPMN2BC Online Editor, performed during the Copenhagen Fintech project "Improving Business Processes with Blockchain: Model-driven Generation of Secure Smart Contract Code": https://www.copenhagenfintech.dk/projects/improving-business-processes-with-blockchain
DOI: 10.5281/zenodo.15170516
title: Improving Business Processes with Blockchain - Evaluation Results

description: This repository contains the results of the evaluation of the tool SecBPMN2BC Online Editor, performed during the Copenhagen Fintech project "Improving Business Processes with Blockchain: Model-driven Generation of Secure Smart Contract Code": https://www.copenhagenfintech.dk/projects/improving-business-processes-with-blockchain
DOI: 10.5281/zenodo.15170537
title: Data related job offers in Glassdoor (2025)

description: The collected dataset contains a sample of active job offers related to data science in Spain, extracted from the Glassdoor portal. This compilation includes both the search terms used and the specific title published for each offer, as well as additional information associated with the advertising company: its average rating, the geographical location of the position, the estimated salary (when available), the age of the listing, and the direct link to its original publication.

This dataset is particularly useful for identifying potential mismatches between the profiles being sought and those actually appearing in the market, as well as for analyzing which companies are leading the hiring of digital profiles in Spain. Moreover, it enables the study of geographical and temporal patterns that may reflect specific dynamics within the technological and analytical job sector.
DOI: 10.5281/zenodo.15170538
title: Data related job offers in Glassdoor (2025)

description: The collected dataset contains a sample of active job offers related to data science in Spain, extracted from the Glassdoor portal. This compilation includes both the search terms used and the specific title published for each offer, as well as additional information associated with the advertising company: its average rating, the geographical location of the position, the estimated salary (when available), the age of the listing, and the direct link to its original publication.

This dataset is particularly useful for identifying potential mismatches between the profiles being sought and those actually appearing in the market, as well as for analyzing which companies are leading the hiring of digital profiles in Spain. Moreover, it enables the study of geographical and temporal patterns that may reflect specific dynamics within the technological and analytical job sector.
DOI: 10.25574/30881
title: Chandra X-ray Observatory ObsId 30881

description: Probing the First Gamma-ray Bursts with Chandra
DOI: 10.5281/zenodo.15170584
title: Wind energy circular economy papers and indicators

description: Wind energy circular economy papers and indicators
DOI: 10.5281/zenodo.15170585
title: Wind energy circular economy papers and indicators

description: Wind energy circular economy papers and indicators
DOI: 10.5281/zenodo.15170560
title: Global and U.S. Box Office Performance Data

description: This dataset, titled Global and U.S. Box Office Performance Data, was created as part of an academic project focused on the automated extraction of financial performance data from the film industry. The data was collected from Box Office Mojo by IMDbPro, a widely recognized source for box office statistics. The project uses a custom web scraping pipeline developed in Python, combining Selenium and BeautifulSoup to systematically explore various sections of the website (e.g., brands, franchises, weekly/monthly reports) and extract structured information from HTML tables.

The dataset contains 14,086 records with 35 fields, covering key financial and commercial metadata of movies such as lifetime gross, opening weekend revenue, release date, number of theaters, distributor, and more. Each entry includes a source URL and a category field that indicates the specific section of the website where the data was obtained. The dataset spans from 1972 to early 2025, with a particular focus on daily, monthly, and quarterly data from 2024–2025 and aggregated statistics by brand, genre, holiday, and franchise.

This dataset can support various use cases, including market analysis, trend detection in the film industry, or the development of predictive models for commercial movie success. Due to the heterogeneity of the original website, the data has not been extensively cleaned or normalized—allowing future users to define their own preprocessing steps depending on the analytical goal.

Important Note: The dataset was created for educational purposes only and follows ethical guidelines including minimal server load, respect for website structure, and explicit non-commercial intent. The scraping process was limited in scope and rate, and all data references the original source (IMDb) with proper attribution. The dataset is distributed under the Creative Commons BY-NC-ND 4.0 license with additional restrictions detailed in the LICENSE file of the project’s GitHub repository.