cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/95ee6f7b-3cf7-4c01-a461-860e6f9485bf.v1
title: VBi2Te4 dataset underlying the publication: Phase Separation Prevents the Synthesis of VBi2Te4 by Molecular Beam Epitaxy

description: This dataset contains the collection of experimental data on attempts to deposit VBi2Te4 by molecular beam epitaxy (MBE). The data is published in:Altena M., Jansen T., Tsvetanova M., Brinkman A. Nanomaterials 2023<br>The published data covers samples deposited with different vanadium fluxes during the MBE growth, deposited with the following settings:General:Substrate: (0001)-Al2O3Temp_sub = 150CφBi = 0.0027 Å/sφTe = 0.072 Å/sThickness buffer layer Bi2Te3: 1 nm<br>TJ_VBT01 - φV = 1800 C (temperature of the Knudsen cell)TJ_VBT02 - φV = 1750 CTJ_VBT03 - φV = 1850 CTJ_VBT04 - φV = 1900 CMA_VBT14 - φV = 1800 C, no buffer layer<br>The dataset is a .zip file covering the following data:- XRD data (TJ_VBT01, TJ_VBT02, TJ_VBT03, TJ_VBT04)- STEM + EDX data (MA_VBT14)- RHEED data (TJ_VBT02)- AFM data (TJ_VBT01, TJ_VBT02, TJ_VBT03, TJ_VBT04)<br>
DOI: 10.7910/dvn/497dwe
title: Human Resource Challenges in Odisha's Education Sector

description: Odisha, nestled amidst the rich tapestry of India, pulsates with a vibrant cultural heritage and a burgeoning economy. However, navigating the landscape of its education sector, particularly towards Human Resource (HR) practices, unveils a complex maze of challenges and opportunities. This paper delves into the labyrinthine realm of HR issues plaguing this crucial domain, shedding light on the intricate web of factors hindering its optimal functioning. Through a lens of scholarly references and insightful analysis, we embark on a quest to comprehend the multifaceted nature of these issues and chart a path towards potential solutions.
DOI: 10.5281/zenodo.10478710
title: Global SGD and CO2 data

description: This dataset is a global compilation of 40 coastal ecosystems across 14 countries. It consists of continuous time series for carbon dioxide and radon. Other parameters included are latitude, longitude, depth, temperature, salinity, dissolved oxygen, and water-air flux for carbon dioxide. Timestamps of each measurement correspond to the local time zone. Carbon dioxide and radon were measured using Licor and RAD7, respectively. Depth, temperature, salinity, and dissolved oxygen were measured using probes. This dataset was used to interpret the impact of SGD on CO2 dynamics in globally distributed coastal ecosystems. 

Data sources are mentioned in the sheet References. 

Column names in the "Master File" sheet: 



Location: Name of the location of measurement

Location ID: ID of the location 

Country: Country of location 

Ecosystem Type: categorical ecosystem type 

Latitude: Latitudinal coordinate of the location (DD)

Longitude: Longitudinal coordinate of the location (DD)

Date (DD/MM/YYYY): Date when the measurement was taken (DD/MM/YYYY)

Time (hh:mm): Local time of when the measurement was taken

Time since start (Days): Duration of the continuous measurement since the first measurement was started (days)

Wind Speed (m/s): Wind speed at the location at the time of measurement

Depth (m): Depth at which the measurement was taken (m)

Temperature (°C): Temperature at the point of radon/carbon dioxide measurement

Salinity: Salinity of water at the point of radon/carbon dioxide measurement

DO (%): Dissolved oxygen in the water at the point where radon measurement was taken (%)

Radon (dpm/L): Radon measurement in water (dpm/L). Measured using Durridge RAD7 

CO2 (µatm) at sst: measurement of Carbon Dioxide dissolved in water at sea surface temperature (µatm). Measured using LiCor.  

Water-air CO2 flux (mmol m-2 day-1): Calculated water-air flux of carbon dioxide.
DOI: 10.5281/zenodo.10478711
title: Global SGD and CO2 data

description: This dataset is a global compilation of 40 coastal ecosystems across 14 countries. It consists of continuous time series for carbon dioxide and radon. Other parameters included are latitude, longitude, depth, temperature, salinity, dissolved oxygen, and water-air flux for carbon dioxide. Timestamps of each measurement correspond to the local time zone. Carbon dioxide and radon were measured using Licor and RAD7, respectively. Depth, temperature, salinity, and dissolved oxygen were measured using probes. This dataset was used to interpret the impact of SGD on CO2 dynamics in globally distributed coastal ecosystems. 

Data sources are mentioned in the sheet References. 

Column names in the "Master File" sheet: 



Location: Name of the location of measurement

Location ID: ID of the location 

Country: Country of location 

Ecosystem Type: categorical ecosystem type 

Latitude: Latitudinal coordinate of the location (DD)

Longitude: Longitudinal coordinate of the location (DD)

Date (DD/MM/YYYY): Date when the measurement was taken (DD/MM/YYYY)

Time (hh:mm): Local time of when the measurement was taken

Time since start (Days): Duration of the continuous measurement since the first measurement was started (days)

Wind Speed (m/s): Wind speed at the location at the time of measurement

Depth (m): Depth at which the measurement was taken (m)

Temperature (°C): Temperature at the point of radon/carbon dioxide measurement

Salinity: Salinity of water at the point of radon/carbon dioxide measurement

DO (%): Dissolved oxygen in the water at the point where radon measurement was taken (%)

Radon (dpm/L): Radon measurement in water (dpm/L). Measured using Durridge RAD7 

CO2 (µatm) at sst: measurement of Carbon Dioxide dissolved in water at sea surface temperature (µatm). Measured using LiCor.  

Water-air CO2 flux (mmol m-2 day-1): Calculated water-air flux of carbon dioxide.
DOI: 10.5281/zenodo.10478808
title: An auto-ethnography of living with smart home technology

description: This dataset contains an auto-ethnographic diary about installing and living with smart home technology, written over the course of 20 months from spring 2017 to September 2020. The language of the diary is Danish. The diary was written as part of the eCAPE project (New energy consumer roles and smart technologies – actors, practices and equality) running from 2018-2023. eCAPE is financed by the European Research Council (ERC), as an ERC-advanced grant, under the European Union´s Horizon 2020 research and innovation program (grant agreement number 786643). The project is led by Professor Kirsten Gram-Hanssen from Department of the Built Environment, Aalborg University, and she is also the author of the diary. The smart technology which are included in the diary includes a smart alarm, including some control of lighting, smart control of heating and an electric vehicle. The name of the writer, and her husband, is not anonymized, and both have given full consent to this material being published as part of FAIR data principles. To this date, the auto-ethnography data have been analyzed in one journal paper, where further details about the diary writing as well as analysis of this related to learning process is described in:

Aagaard L.K., Christensen T.H., Gram-Hanssen K. (2023) My smart home: an auto-ethnography of learning to live with smart technologies. Personal and Ubiquitous Computing, 27 (6), pp. 2121 - 2131
DOI: 10.5281/zenodo.10478809
title: An auto-ethnography of living with smart home technology

description: This dataset contains an auto-ethnographic diary about installing and living with smart home technology, written over the course of 20 months from spring 2017 to September 2020. The language of the diary is Danish. The diary was written as part of the eCAPE project (New energy consumer roles and smart technologies – actors, practices and equality) running from 2018-2023. eCAPE is financed by the European Research Council (ERC), as an ERC-advanced grant, under the European Union´s Horizon 2020 research and innovation program (grant agreement number 786643). The project is led by Professor Kirsten Gram-Hanssen from Department of the Built Environment, Aalborg University, and she is also the author of the diary. The smart technology which are included in the diary includes a smart alarm, including some control of lighting, smart control of heating and an electric vehicle. The name of the writer, and her husband, is not anonymized, and both have given full consent to this material being published as part of FAIR data principles. To this date, the auto-ethnography data have been analyzed in one journal paper, where further details about the diary writing as well as analysis of this related to learning process is described in:

Aagaard L.K., Christensen T.H., Gram-Hanssen K. (2023) My smart home: an auto-ethnography of learning to live with smart technologies. Personal and Ubiquitous Computing, 27 (6), pp. 2121 - 2131
DOI: 10.5281/zenodo.10478601
title: Observational characterization of atmospheric disturbances generating meteotsunamis in the Balearic Islands: data

description: This dataset contains all data used in the article:

Observational characterization of atmospheric disturbances generating meteotsunamis in the Balearic Islands

Joan Villalonga*(1,2), Sebastià Monserrat (1), Damià Gomis (1,3), Gabriel Jordà*(2)

(1) Departament de Física (UIB), Palma, Spain.

(2) Centre Oceanogràfic de Balears, CN-Instituto Español de Oceanografía (IEO-CSIC), Palma, Spain.

(3) Institut Mediterrani d’Estudis Avançats (UIB-CSIC), Esporles, Spain.

Corresponding email: joan.villalonga@uib.cat

There are 7 data files:





Atm_pres_all: containing the atmospheric pressure time series measured in the different meteorological stations used in the work. Each station contain its name and position in coordinates. All the time series have a temporal resolution of 1 min. The data have been obtained from BalearsMeteo (http://balearsmeteo.com/) and from SOCIB (https://www.socib.es/).




ciutadella_SL_AtmPres: containing the sea level and atmospheric pressure records in Ciutadella from 2018 to 2021. All the time series have a temporal resolution of 1 min. The data have been provided by PortIB (https://www.portsib.es/ca/paginas/inici).




ciutadella_SL_long: containing the sea level records in Ciutadella from 2014 to 2021. All the time series have a temporal resolution of 1 min. The data have been provided by PortIB (https://www.portsib.es/ca/paginas/inici).




ciutadella_spectral_data: containing the sea level and atmospheric pressure power wavelet spectra in Ciutadella from 2018 to 2021. Computed from the data in ciutadella_SL_AtmPres.




corr_rissagues_1min_allfreq_12h: containing the maximum lagged correlation matrices between the atmospheric pressure time series measured at the 12h surrounding each meteotsunami event in 2021. They have been computed from the data in Atm_pres_all.




sepic_index_vars: containing the five ERA5 1-hour time series of the variables used to compute the meteotsunami index as described in Sepic, et al,. 2016.




wind_ciutadella: containing the time series of the wind speed and direction provided by ERA5 reanalysis over Ciutadella during the period of study.



For more details, please consult the manuscript of the article
DOI: 10.18712/nsd-nsd3158-v1
title: Norwegian Election Campaign Survey 2021

description: The Norwegian Election Campaign Survey was conducted during the summer and autumn of 2021. The purpose of the survey was to describe the different issues people care about during election campaigns and the parliamentary elections, and how people acquire this information. The survey was funded by the Institute for Social Research (ISF). 

For the survey, a selection of 10 000 individuals from the age of 18 and upwards were collected from the National Population Register.

The survey was a web-based, self-administered panel survey, collected in five separate rounds. The data collection for each round lasted for one week. The first round was collected in June 2021 and the last round in November 2021.
DOI: 10.3886/icpsr38972.v1
title: Survey of Consumer Attitudes and Behavior, September 2020
title: Version 1

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter.
The surveys conducted in 2020 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, computers, and other durables. Also explored in this survey, were respondents' types of savings and financial investments, loan use, family income, retirement planning, political affiliation, the coronavirus, and vehicle financing insurance.
Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this survey series is to forecast changes in aggregate consumer behavior.
description: This survey is a rotating panel design. For each monthly sample, an independent cross-section sample of households is drawn. The respondents chosen in this drawing are then reinterviewed six months later. The result is a rotating panel design, and the total sample for any one survey is normally made up of 60 percent new respondents with 40 percent being interviewed for the second time.
description: The data are not weighted, however, this collection contains three weight variables; <b>WT_AD</b> (Adult weight), <b>WT_HH</b> (Household weight), <b>WT</b> (Household weight (WT_HH renamed)) and that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Surveys of Consumers Website.
description: National sample of telephone numbers from cell (RDD) sampling frame.
description: Datasets: 
DS0: Study-Level Files
DS1: Public-Use Data
DS2: Restricted-Use Data
description: Persons aged 18 years or older living in households with telephones in the coterminous United States. Smallest Geographic Unit: FIPS code
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the P.I. Codebook.Additional information on the Surveys of Consumers can be found by visiting the Surveys of Consumers Website.
DOI: 10.3886/icpsr38972
title: Survey of Consumer Attitudes and Behavior, September 2020
title: Archival Version

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter.
The surveys conducted in 2020 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, computers, and other durables. Also explored in this survey, were respondents' types of savings and financial investments, loan use, family income, retirement planning, political affiliation, the coronavirus, and vehicle financing insurance.
Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this survey series is to forecast changes in aggregate consumer behavior.
description: This survey is a rotating panel design. For each monthly sample, an independent cross-section sample of households is drawn. The respondents chosen in this drawing are then reinterviewed six months later. The result is a rotating panel design, and the total sample for any one survey is normally made up of 60 percent new respondents with 40 percent being interviewed for the second time.
description: The data are not weighted, however, this collection contains three weight variables; <b>WT_AD</b> (Adult weight), <b>WT_HH</b> (Household weight), <b>WT</b> (Household weight (WT_HH renamed)) and that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Surveys of Consumers Website.
description: National sample of telephone numbers from cell (RDD) sampling frame.
description: Datasets: 
DS0: Study-Level Files
DS1: Public-Use Data
DS2: Restricted-Use Data
description: Persons aged 18 years or older living in households with telephones in the coterminous United States. Smallest Geographic Unit: FIPS code
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the P.I. Codebook.Additional information on the Surveys of Consumers can be found by visiting the Surveys of Consumers Website.
DOI: 10.5281/zenodo.10449363
title: Comprehensive evaluation of smoking exposures and their interactions on DNA methylation

description: Data from up to 15,014 adults were meta-analyzed across 5 cohorts with DNA methylation measured in blood using Illumina’s EPIC array for current smoking (2,560 exposed), quit <1 year (500 exposed), in utero (286 exposed), and environmental tobacco smoke (ETS) exposure (676 exposed). Using false discovery rate (FDR<0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4,025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. There was also evidence that 4-71 smoking related CpGs may be modified by sex or dietary intake (i.e., fibre, folate, and vitamin C).
DOI: 10.5281/zenodo.10449364
title: Comprehensive evaluation of smoking exposures and their interactions on DNA methylation

description: Data from up to 15,014 adults were meta-analyzed across 5 cohorts with DNA methylation measured in blood using Illumina’s EPIC array for current smoking (2,560 exposed), quit <1 year (500 exposed), in utero (286 exposed), and environmental tobacco smoke (ETS) exposure (676 exposed). Using false discovery rate (FDR<0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4,025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. There was also evidence that 4-71 smoking related CpGs may be modified by sex or dietary intake (i.e., fibre, folate, and vitamin C).
DOI: 10.5281/zenodo.7025003
title: Dataset to 'Altered correlation of concurrently recorded EEG-fMRI connectomes in temporal lobe epilepsy '

description: Dataset to 'Altered correlation of concurrently recorded EEG-fMRI connectomes in temporal lobe epilepsy ' <em>eeg-fmri_$dataset$_$group$_connectomes_desikan_scrubbed.mat</em><br> datasets with filename truncTo5min hold static connectivities based on timeseries truncated<br> to 5min. All other datasets are based on static connectivities derived from the total session<br> timeseries. <br> subj: subject<br> subj.name: name of the subject<br> subj.sess: session<br> subj.sess.sess_name: name of the session<br> subj.sess.fMRI: vector of upper triangular of fMRI connectivity<br> subj.sess.EEG: EEG connectomes<br> subj.sess.EEG.name: name of connectivity measure used (corrected imaginary part of the coherency: iCoh)<br> subj.sess.EEG.bands: EEG frequency bands<br> subj.sess.EEG.bands.name: name of frequency band (delta, theta, alpha, beta, gamma)<br> subj.sess.EEG.bands.name.conn: vector of upper triangular of EEG connectivity<br> subj.atlas: Atlas<br> subj.atlas.name: name of atlas used (Desikan)<br> subj.atlas.regions: number of regions <em>$dataset$_$group$_</em>particpants.tsv: Subject metadata <em>$dataset$_$group$_spikes.mat: Interictal epileptoform discharges (IEDs) marked for each session of TLE patients</em> <em>aparc_aseg_yeoR7_68reg_eeg_nosubc_cmfg2dan.mat: mapping of Desikan regions to Yeo7-networks (Yeo et al. 2011, JNP)</em> <em>For the related code to this dataset please clone: </em>https://github.com/jwirsich/eeg-fmri-tle
description: We acknowledge support from Swiss National Science Foundation (SNSF, under grants CRSII5_209470, and 192749 to SV, 163398 and 180365 to MS and 188769 to FG, P500PM_206720 to LS). JW is supported by a research position of the Faculty of Medicine, University of Geneva. This work was supported by Centre d'Imagerie BioMédicale (CIBM) of the UNIL, UNIGE, HUG, CHUV, EPFL and the Leenaards and Jeantet Foundations, the CNRS, the ANR CONNECTEPI (grant number ANR-07-NEUR-0010).
DOI: 10.5281/zenodo.10015179
title: Large-scale annotated dataset for cochlear hair cell detection and classification

description: This is the dataset behind the Hair Cell Analysis Toolbox (HCAT)
DOI: 10.5281/zenodo.7937970
title: Large scale annotated dataset for cochlear hair cell detection and classification

description: This is the dataset behind the Hair Cell Analysis Toolbox (HCAT)
DOI: 10.5281/zenodo.8250820
title: Large-scale annotated dataset for cochlear hair cell detection and classification

description: This is the dataset behind the Hair Cell Analysis Toolbox (HCAT)
DOI: 10.5281/zenodo.10041854
title: Large-scale annotated dataset for cochlear hair cell detection and classification

description: Our sense of hearing is mediated by cochlear hair cells, of which there are two types organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains 5 - 15 thousand terminally differentiated hair cells, and their survival is essential for hearing as they do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. Machine learning can be used to automate the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, rat, guinea pig, pig, primate, and human cochlear tissue, from normal conditions and following in-vivo and in-vitroototoxic drug application. The dataset includes over 107,000 hair cells which have been manually identified and annotated as either inner or outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair-cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to give other hearing research groups the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease. 
Associated code is provided here: https://github.com/indzhykulianlab/hcat-data