cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1398397.10fu
title: SH1398397.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1398400.10fu
title: SH1398400.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.xn4tjr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Caudofoveata)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-160 30,-150 30,-150 40,-160 40,-160 30))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024336-251009101135966/datasets/export for details.
DOI: 10.15468/dl.r5n37t
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bivalvia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-150 -50,-140 -50,-140 -40,-150 -40,-150 -50))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024334-251009101135966/datasets/export for details.
DOI: 10.15468/dl.sx59tw
title: Occurrence Download

description: A dataset containing 27560 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Passeriformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((30 10,40 10,40 20,30 20,30 10))"
 ]
}

 The dataset includes 27560 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024335-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/iw73uu/nhpebg
title: TAS_A_hour.csv

description: Uploaded with pyDataverse 2024-01-03 19:05
DOI: 10.22008/fk2/iw73uu/7vh6sh
title: NAU_day.csv

description: Uploaded with pyDataverse 2024-01-03 19:05
DOI: 10.22008/fk2/iw73uu/a7uhr8
title: NAU_month.nc

description: Uploaded with pyDataverse 2024-01-03 19:05
DOI: 10.22008/fk2/iw73uu/jfelsd
title: NAU_hour.csv

description: Uploaded with pyDataverse 2024-01-03 19:05
DOI: 10.22008/fk2/iw73uu/u8vabv
title: NAU_hour.nc

description: Uploaded with pyDataverse 2024-01-03 19:06
DOI: 10.22008/fk2/iw73uu/a3nexk
title: NAU_month.csv

description: Uploaded with pyDataverse 2024-01-03 19:06
DOI: 10.22008/fk2/iw73uu/stoqca
title: NAU_day.nc

description: Uploaded with pyDataverse 2024-01-03 19:06
DOI: 10.22008/fk2/iw73uu/chiezh
title: DY2_hour.csv

description: Uploaded with pyDataverse 2024-01-03 19:06
DOI: 10.22008/fk2/iw73uu/0mvymt
title: DY2_day.csv

description: Uploaded with pyDataverse 2024-01-03 19:06
DOI: 10.22008/fk2/iw73uu/zmilfv
title: DY2_month.nc

description: Uploaded with pyDataverse 2024-01-03 19:06
DOI: 10.22008/fk2/iw73uu/0ej7e3
title: DY2_month.csv

description: Uploaded with pyDataverse 2024-01-03 19:06
DOI: 10.22008/fk2/iw73uu/sgikzj
title: DY2_hour.nc

description: Uploaded with pyDataverse 2024-01-03 19:06
DOI: 10.22008/fk2/iw73uu/0hveqy
title: DY2_day.nc

description: Uploaded with pyDataverse 2024-01-03 19:07
DOI: 10.22008/fk2/iw73uu/kb0b30
title: EGP_month.csv

description: Uploaded with pyDataverse 2024-01-03 19:07
DOI: 10.22008/fk2/iw73uu/qcm9xz
title: EGP_month.nc

description: Uploaded with pyDataverse 2024-01-03 19:07
DOI: 10.22008/fk2/iw73uu/mkt6uj
title: EGP_day.nc

description: Uploaded with pyDataverse 2024-01-03 19:07
DOI: 10.22008/fk2/iw73uu/7l93yh
title: EGP_hour.nc

description: Uploaded with pyDataverse 2024-01-03 19:07
DOI: 10.22008/fk2/iw73uu/dn1mjx
title: EGP_day.csv

description: Uploaded with pyDataverse 2024-01-03 19:07
DOI: 10.22008/fk2/iw73uu/0m3jcd
title: EGP_hour.csv

description: Uploaded with pyDataverse 2024-01-03 19:07
DOI: 10.22008/fk2/iw73uu/icm9nq
title: HUM_day.nc

description: Uploaded with pyDataverse 2024-01-03 19:07
DOI: 10.5281/zenodo.18665367
title: Tryptophan-related Gut Microbes are Linked with Neural and Behavioral Autism Phenotypes

description: Metadata for the manuscript "Tryptophan-related Gut Microbes are Linked with Neural and Behavioral Autism Phenotypes".
DOI: 10.5281/zenodo.18665368
title: Tryptophan-related Gut Microbes are Linked with Neural and Behavioral Autism Phenotypes

description: Metadata for the manuscript "Tryptophan-related Gut Microbes are Linked with Neural and Behavioral Autism Phenotypes".
DOI: 10.22008/fk2/iw73uu/k4xgtc
title: HUM_month.nc

description: Uploaded with pyDataverse 2024-01-03 19:08
DOI: 10.22008/fk2/iw73uu/lzst7f
title: HUM_month.csv

description: Uploaded with pyDataverse 2024-01-03 19:08
DOI: 10.15468/dl.6n373d
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Spartocera dentiventris",
 "HasCoordinate is True"
 ]
}

 The dataset includes 11 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009795-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/w38224zk6x.1
title: Multivariate Dataset For Base Oil Forecasting

description: This Multivariate dataset is composed of 386 variables for base oil forecasting and it was developed using financial market data from Yahoo Finance website. The variables are composed of global stock indexes, currency, metals, oil derivates, and companies from the following sectors: refineries, energy, oil, gas, lubricants, oil derivates (gasoline, diesel, etc.), pipelines, oil tankers, exploration and production (E&P), gas station, EPCM (wich operates in the oil & gas sector).

Many variables are traded in other currencies besides US Dollar. Therefore, it was necessary to capture the relationship of all these currencies to the US Dollar. Each currency ticker reflects this exchange relationship. This was necessary to standardize all prices in US Dollar.

The metals tickets are related to Oil as they can be used as a financial hedge against Oil volatility. So, these tickers are variables related to Oil.

US Treasury tickers were used as they are also used as financial hedges by portfolio managers to counterbalance the Oil and markets volatility.

The period considered is between 2010-01-01 and 2025-10-31.

The spreadsheet contains two tabs. The first is the Multivariate dataset and the second is a set of tickers. There were no captured because the prices captured had less than 80% of the period covered or because the ticker was not found.

The values captured were the Adjusted Close Prices that represent a stock's closing price modified to account for all applicable corporate actions, including dividend distributions, stock splits, and rights offeringsadjusted for stock splits.
DOI: 10.17632/w498b85v8w
title: Dataset for:Divergent controls on particulate and mineral-associated organic carbon in tropical forests of southern China
DOI: 10.17632/w498b85v8w.1
title: Dataset for:Divergent controls on particulate and mineral-associated organic carbon in tropical forests of southern China
DOI: 10.17632/4c7tj3nx32
title: Daily Root Zone Soil Moisture and Meteorological Dataset for Time Series Prediction (2020–2025)

description: This dataset contains daily meteorological variables and root zone soil moisture observations collected from 1 January 2020 to 31 December 2025. The dataset was constructed to support time series prediction and comparative modeling using machine learning and deep learning approaches. Meteorological data were obtained from BMKG (Badan Meteorologi, Klimatologi, dan Geofisika), Trunojoyo Meteorological Station. The observed variables include air temperature (Tavg, °C), relative humidity (RH_avg, %), rainfall (RR, mm), and sunshine duration (ss, hours/day). Root zone soil moisture data were retrieved from NASA POWER, derived from the MERRA-2 reanalysis system. The parameter used is GWETROOT (Root Zone Soil Wetness), representing volumetric soil moisture content (m3/m3) within the 0–100 cm soil depth layer. The soil moisture data correspond to the same geographic coordinates as the meteorological station (latitude -7.0398, longitude 113.914). All variables were aligned on a daily temporal scale. Special codes for missing or unavailable values were identified and treated appropriately during preprocessing. Zero rainfall or zero sunshine duration represent valid observations rather than missing data. The dataset is structured for supervised learning, where meteorological variables serve as input features and root zone soil moisture serves as the prediction target. The dataset is suitable for time series forecasting, environmental modeling, irrigation recommendation systems, and agricultural decision support applications.
DOI: 10.17632/4c7tj3nx32.1
title: Daily Root Zone Soil Moisture and Meteorological Dataset for Time Series Prediction (2020–2025)

description: This dataset contains daily meteorological variables and root zone soil moisture observations collected from 1 January 2020 to 31 December 2025. The dataset was constructed to support time series prediction and comparative modeling using machine learning and deep learning approaches. Meteorological data were obtained from BMKG (Badan Meteorologi, Klimatologi, dan Geofisika), Trunojoyo Meteorological Station. The observed variables include air temperature (Tavg, °C), relative humidity (RH_avg, %), rainfall (RR, mm), and sunshine duration (ss, hours/day). Root zone soil moisture data were retrieved from NASA POWER, derived from the MERRA-2 reanalysis system. The parameter used is GWETROOT (Root Zone Soil Wetness), representing volumetric soil moisture content (m3/m3) within the 0–100 cm soil depth layer. The soil moisture data correspond to the same geographic coordinates as the meteorological station (latitude -7.0398, longitude 113.914). All variables were aligned on a daily temporal scale. Special codes for missing or unavailable values were identified and treated appropriately during preprocessing. Zero rainfall or zero sunshine duration represent valid observations rather than missing data. The dataset is structured for supervised learning, where meteorological variables serve as input features and root zone soil moisture serves as the prediction target. The dataset is suitable for time series forecasting, environmental modeling, irrigation recommendation systems, and agricultural decision support applications.
DOI: 10.17632/9nvf8v5989
title: A Comprehensive Oceanographic, Meteorological and Hydrographic Dataset for the San Andres, Providencia, and Santa Catalina Archipelago in the Colombian Caribbean, 2018–2025

description: This dataset contains multi-sensor oceanographic, hydrographic, wave, and meteorological observations collected across the San Andrés, Providencia, and Santa Catalina Islands (Colombian Caribbean) between May 2018 and July 2025.
Sea surface variation was measured using AQUAlogger and RBR pressure sensors (SV, ASV), and additional surface-variation products and vertical current profiles were obtained from Nortek AWAC Acoustic Doppler Current Profilers (600 and 1000 kHz) (SVC). Fixed-depth time series of seawater temperature and temperature–conductivity were recorded with HOBO loggers (TCL), while CTD casts provided vertical profiles of temperature, conductivity, salinity, density, specific conductance, and sound velocity (CTD). Offshore wave parameters were measured using a Spotter wave buoy (WB).

Atmospheric variables—including air temperature, humidity, barometric pressure, precipitation, solar radiation, and wind speed and direction—were recorded by Davis Vantage Pro, Rainwise, and WeatherSens stations installed on San Andrés Island. All instruments were deployed following standard coastal-monitoring procedures, ensuring quality-controlled observations suitable for studies of coastal hydrodynamics, hydro-climatic variability, and environmental change in tropical island systems.
DOI: 10.17632/9nvf8v5989.1
title: A Comprehensive Oceanographic, Meteorological and Hydrographic Dataset for the San Andres, Providencia, and Santa Catalina Archipelago in the Colombian Caribbean, 2018–2025

description: This dataset contains multi-sensor oceanographic, hydrographic, wave, and meteorological observations collected across the San Andrés, Providencia, and Santa Catalina Islands (Colombian Caribbean) between May 2018 and July 2025.
Sea surface variation was measured using AQUAlogger and RBR pressure sensors (SV, ASV), and additional surface-variation products and vertical current profiles were obtained from Nortek AWAC Acoustic Doppler Current Profilers (600 and 1000 kHz) (SVC). Fixed-depth time series of seawater temperature and temperature–conductivity were recorded with HOBO loggers (TCL), while CTD casts provided vertical profiles of temperature, conductivity, salinity, density, specific conductance, and sound velocity (CTD). Offshore wave parameters were measured using a Spotter wave buoy (WB).

Atmospheric variables—including air temperature, humidity, barometric pressure, precipitation, solar radiation, and wind speed and direction—were recorded by Davis Vantage Pro, Rainwise, and WeatherSens stations installed on San Andrés Island. All instruments were deployed following standard coastal-monitoring procedures, ensuring quality-controlled observations suitable for studies of coastal hydrodynamics, hydro-climatic variability, and environmental change in tropical island systems.
DOI: 10.17632/8jwfmfp2cy
title: Fantini et al., 2026

description: Description of the dataset

The dataset contains the original and processed data supporting the manuscript “Relative sea-level fluctuations of the last millennium recorded by intertidal algal rims (NW Sardinia, Mediterranean Sea)” (Fantini et al., 2026). It includes:

Geochronological data reports: official laboratory radiocarbon analysis reports.

Radiocarbon ages of algal rims: compiled in Table SM1.

Supplementary material: macroscopic sample photographs, thin-section positions and microphotographs, and SEM images.

All files are provided in CSV, XLSX, and PDF formats to ensure accessibility and reproducibility.
DOI: 10.17632/8jwfmfp2cy.2
title: Fantini et al., 2026

description: Description of the dataset

The dataset contains the original and processed data supporting the manuscript “Relative sea-level fluctuations of the last millennium recorded by intertidal algal rims (NW Sardinia, Mediterranean Sea)” (Fantini et al., 2026). It includes:

Geochronological data reports: official laboratory radiocarbon analysis reports.

Radiocarbon ages of algal rims: compiled in Table SM1.

Supplementary material: macroscopic sample photographs, thin-section positions and microphotographs, and SEM images.

All files are provided in CSV, XLSX, and PDF formats to ensure accessibility and reproducibility.
DOI: 10.17632/6s8r8fwy8v
title: Instrumento y codificaciones de proyecto para análisis jurídico ambiental de los países del triángulo norte

description: El estudio emplea una metodología cualitativa basada en entrevistas semiestructuradas, guiadas por un instrumento que aborda tres ejes: marcos jurídicos, gobernanza ambiental y acciones de mejora. 

La recolección de datos se realizó a partir de un listado de especialistas ambientales nacionales y territoriales; en esta fase, la docente Ada Dueñas de la UNAB colaboró en la ejecución de algunas entrevistas.

Para el procesamiento, los audios se transcribieron mediante Whisper y los datos se depuraron para su análisis en el software MAXQDA. Como resultado, se identificaron 8 categorías y 29 subcategorías, representadas en un esquema detallado y una nube de palabras. Finalmente, el registro de la información incluye la institución y la fecha, garantizando el anonimato bajo estrictos principios éticos
DOI: 10.17632/6s8r8fwy8v.1
title: Instrumento y codificaciones de proyecto para análisis jurídico ambiental de los países del triángulo norte

description: El estudio emplea una metodología cualitativa basada en entrevistas semiestructuradas, guiadas por un instrumento que aborda tres ejes: marcos jurídicos, gobernanza ambiental y acciones de mejora. 

La recolección de datos se realizó a partir de un listado de especialistas ambientales nacionales y territoriales; en esta fase, la docente Ada Dueñas de la UNAB colaboró en la ejecución de algunas entrevistas.

Para el procesamiento, los audios se transcribieron mediante Whisper y los datos se depuraron para su análisis en el software MAXQDA. Como resultado, se identificaron 8 categorías y 29 subcategorías, representadas en un esquema detallado y una nube de palabras. Finalmente, el registro de la información incluye la institución y la fecha, garantizando el anonimato bajo estrictos principios éticos
DOI: 10.17632/8xp4hry8n9
title: Seniors

description: This repository contains anonymised pre- and post-course data from an AI literacy course for older adults (University of the Third Age). The dataset includes participants’ responses to a short AI-knowledge quiz and Likert-scale items on attitudes, trust, and self-efficacy related to AI use. All direct identifiers were removed and variables are documented in an accompanying codebook. The repository also provides analysis scripts and outputs to reproduce the statistical results reported in the manuscript.
DOI: 10.17632/8xp4hry8n9.1
title: Seniors

description: This repository contains anonymised pre- and post-course data from an AI literacy course for older adults (University of the Third Age). The dataset includes participants’ responses to a short AI-knowledge quiz and Likert-scale items on attitudes, trust, and self-efficacy related to AI use. All direct identifiers were removed and variables are documented in an accompanying codebook. The repository also provides analysis scripts and outputs to reproduce the statistical results reported in the manuscript.
DOI: 10.5281/zenodo.18720314
title: Electronic payment data and financial inclusion

description: The data includes demographic characteristics such as: gender, age, educational level, and employment status.

The number of respondents to the questionnaire is (100) customers.

The independent variable is electronic payment systems, and the dependent variable is financial inclusion.

The mediating variables consist of customer trust, ease of use, and digital awareness.

For each item in the questionnaire, you will find five options ranging from "strongly agree" to "strongly disagree," numbered from 1 (strongly disagree) to 5 (strongly agree).
DOI: 10.17632/xkdmdt56r4
title: Impact of digital economy on innovation and entrepreneurship: Evidence from China

description: This folder contains the replication materials for the empirical analyses presented in the paper. It includes the dataset and Stata code used to reproduce the main results.
DOI: 10.5281/zenodo.17940583
title: Electronic payment data and financial inclusion

description: The data includes demographic characteristics such as: gender, age, educational level, and employment status.

The number of respondents to the questionnaire is (100) customers.

The independent variable is electronic payment systems, and the dependent variable is financial inclusion.

The mediating variables consist of customer trust, ease of use, and digital awareness.

For each item in the questionnaire, you will find five options ranging from "strongly agree" to "strongly disagree," numbered from 1 (strongly disagree) to 5 (strongly agree).
DOI: 10.17632/xkdmdt56r4.1
title: Impact of digital economy on innovation and entrepreneurship: Evidence from China

description: This folder contains the replication materials for the empirical analyses presented in the paper. It includes the dataset and Stata code used to reproduce the main results.
DOI: 10.17632/hfw6vv2t9b
title: Ministromatolite modular framework reef, ~1.5 Ga, North China

description: A small lensoid mound, with cavernous framework formed by microbial carbonate, occurs in the ~1500-million-year-old (Myr) Wumishan Formation at Yesanpo, northern China. It consists of column and cones composed of innumerable conjoined ministromatolites, each ≤2 cm wide. The irregular, decimetric, framework cavities contain carbonate mud, pisoids, and marine cement. Geochemical signatures, together with traces of organic filaments in the ministromatolites, are consistent with slight oxygenation. The role of ministromatolites in creating this modular framework can broadly be compared with that of polyps in present-day scleractinian coral colonies. Cavernous habitats create extraordinary biodiversity in present-day tropical coral reefs. Yesanpo, currently the oldest known framework reef, predates earliest reported reef-dwelling animals by ~600 Myr. As oxygenation increased in the Late Proterozoic, microbial reef frameworks - similar in structure to Yesanpo - may have been occupied by cryptic biota. These habitats provide prime targets in the continued search for early marine animal life.