cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.2jgvm7
title: Occurrence Download

description: A dataset containing 784 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Actinotus helianthi",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 784 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007430-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j6by32
title: Occurrence Download

description: A dataset containing 5369 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pontederia vaginalis"
 ]
}

 The dataset includes 5369 records from 188 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007428-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18351864
title: ZAMONAVIY XORAZM ADABIY JARAYONI: AN'ANA VA YANGILANISH UYG'UNLIGI (1991–2025)

description: Ushbu maqolada mustaqillik yillarida Xorazm adabiy muhitida kechgan transformatsion jarayonlar, an’anaviy mumtoz maktab va zamonaviy g‘arbiy modernizm yo‘nalishlarining o‘zaro uyg‘unligi tadqiq etiladi. Tadqiqot davomida Xorazm adabiyotining o‘ziga xosligi, xususan, dostonchilik an’analari saqlangan holda lirikada kechayotgan yangilanishlar, nasrdagi psixologizm va dramaturgiyadagi tarixiy mavzular tahlil qilingan. Maqola 1991–2025 yillar oralig‘idagi ijodiy izlanishlarni ilmiy jihatdan baholashni maqsad qiladi.
DOI: 10.5281/zenodo.18351865
title: ZAMONAVIY XORAZM ADABIY JARAYONI: AN'ANA VA YANGILANISH UYG'UNLIGI (1991–2025)

description: Ushbu maqolada mustaqillik yillarida Xorazm adabiy muhitida kechgan transformatsion jarayonlar, an’anaviy mumtoz maktab va zamonaviy g‘arbiy modernizm yo‘nalishlarining o‘zaro uyg‘unligi tadqiq etiladi. Tadqiqot davomida Xorazm adabiyotining o‘ziga xosligi, xususan, dostonchilik an’analari saqlangan holda lirikada kechayotgan yangilanishlar, nasrdagi psixologizm va dramaturgiyadagi tarixiy mavzular tahlil qilingan. Maqola 1991–2025 yillar oralig‘idagi ijodiy izlanishlarni ilmiy jihatdan baholashni maqsad qiladi.
DOI: 10.5281/zenodo.18351874
title: OTA-ONALARNING YOSH AVLODNI  TARBIYALASH BO'YICHA MA' NAVIY-" AXLOQIY  BILIMLARINI OSHIRISH

description: Rivoyat qiladilarki, bir ona donishmand oldiga kelibdi va bolasining tarbiyasiga qachon kirishish kerakligi haqida so’rabdi.
DOI: 10.5281/zenodo.18351875
title: OTA-ONALARNING YOSH AVLODNI  TARBIYALASH BO'YICHA MA' NAVIY-" AXLOQIY  BILIMLARINI OSHIRISH

description: Rivoyat qiladilarki, bir ona donishmand oldiga kelibdi va bolasining tarbiyasiga qachon kirishish kerakligi haqida so’rabdi.
DOI: 10.15468/dl.necqh4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((4.316297217393159 47.89141617168815, 4.3159094228295 47.89404536650449, 4.314766319472549 47.896573156111245, 4.312911736362932 47.898902375811645, 4.310416877484589 47.90094348037841, 4.307377595591132 47.90261799049701, 4.303910712195266 47.903861514896185, 4.3001495245958825 47.904626231080584, 4.296238673148966 47.90488272838542, 4.292328567581861 47.90462114172346, 4.2885695888677455 47.90385153191981, 4.285106292218864 47.90260349783107, 4.282071836712117 47.90092503534618, 4.279582857930501 47.89888068765467, 4.277734982204644 47.89654905867133, 4.276599155372705 47.89401978612206, 4.276218926585701 47.8913900915594, 4.2766087899798215 47.88876104068935, 4.277753645619871 47.886233658255, 4.279609397696039 47.88390504696482, 4.282104664259796 47.88186465942117, 4.285143530491064 47.88019086577835, 4.288609238157876 47.87894794823061, 4.292368668955403 47.87818363688567, 4.2962774499848475 47.87792728077523, 4.300185486721213 47.878188723490844, 4.303942713152114 47.87895792612207, 4.307404840834562 47.88020535180054, 4.310438888656174 47.88188309726229, 4.3129282831002556 47.88392672847808, 4.314777334555285 47.886257750610035, 4.3159149181889624 47.88878661831988, 4.316297217393159 47.89141617168815))",
 "KingdomKey is one of (Animalia, Fungi, Plantae)",
 "Year is one of (2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026)",
 "Modified is greater than or equal to 2026-01-19"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007432-260120142942310/datasets/export for details.
DOI: 10.5281/zenodo.18344942
title: TSSC comet-centered data products from TESS 3I/ATLAS observations

description: NASA's TESS performed dedicated observations of the comet 3I/ATLAS during January 15 and 22, 2026. This repository contains data products created by the TESS Science Support Center which are background corrected image time series and photometric time series. For more details on these observations visit the TSSC webpage. For details on this data set, how was created, and how to work with this data visit our notebook tutorials here.
DOI: 10.6084/m9.figshare.31136523
title: Analyzing cross-trait genetic architecture with the BIGA cloud computing platform*

description: As large-scale biobanks provide increasing access to deep phenotyping and genomic data, genome-wide association studies (GWAS) are rapidly uncovering the genetic architecture behind various complex traits and diseases. GWAS publications typically make their summary-level data (GWAS summary statistics) publicly available, enabling further exploration of genetic overlaps between phenotypes gathered from different studies and cohorts. However, systematically analyzing high-dimensional GWAS summary statistics for thousands of phenotypes can be both logistically challenging and computationally demanding. In this paper, we introduce BIGA (https://bigagwas.org/), a website that aims to offer unified data analysis pipelines and processed data resources for cross-trait genetic architecture analyses. We have curated over 15,000 phenotypes and integrated four statistical genetics tools to support cloud-based batch-running for various cross-trait data analyses. Additionally, we developed a novel online query function for GWAS summary statistics, linking to over 30,000 harmonized datasets in the GWAS Catalog. Through BIGA, users can upload their own data, query data online without local downloads, submit jobs, and share results, providing the research community with a convenient tool for consolidating GWAS data and generating new insights.
DOI: 10.6084/m9.figshare.31136523.v1
title: Analyzing cross-trait genetic architecture with the BIGA cloud computing platform*

description: As large-scale biobanks provide increasing access to deep phenotyping and genomic data, genome-wide association studies (GWAS) are rapidly uncovering the genetic architecture behind various complex traits and diseases. GWAS publications typically make their summary-level data (GWAS summary statistics) publicly available, enabling further exploration of genetic overlaps between phenotypes gathered from different studies and cohorts. However, systematically analyzing high-dimensional GWAS summary statistics for thousands of phenotypes can be both logistically challenging and computationally demanding. In this paper, we introduce BIGA (https://bigagwas.org/), a website that aims to offer unified data analysis pipelines and processed data resources for cross-trait genetic architecture analyses. We have curated over 15,000 phenotypes and integrated four statistical genetics tools to support cloud-based batch-running for various cross-trait data analyses. Additionally, we developed a novel online query function for GWAS summary statistics, linking to over 30,000 harmonized datasets in the GWAS Catalog. Through BIGA, users can upload their own data, query data online without local downloads, submit jobs, and share results, providing the research community with a convenient tool for consolidating GWAS data and generating new insights.
DOI: 10.57761/bf0j-nb70
title: Item Response Warehouse

description: itemresponsewarehouse@stanford.edu
description: The Item Response Warehouse (IRW) is a collection of open, harmonized item response datasets.

- Open: The data are licensed for reformatting and public reuse. Their provenance is documented and code used to transform original data to meet the IRW data standard is available.
  
- Harmonized: The data are formatted to a common standard. The goal of the IRW is to make large quantities of data available for standardized analysis given the common formatting. 
  
 - Item Response: The IRW is comprised of cross-classified item responses. The key element required of data for inclusion in the IRW is that the data need to report individual responses that are cross-classified by the focus of measurement (typically a person) and the measurement tool (typically an item).
  
These datasets in IRW span a wide range of measures; examples include measures of ability in education settings, measures of partisanship based on voting records, and personality measures based on survey questions.  Responses can be scored in a variety of ways (dichotomous, polytomous, continuous) and may contain additional data (e.g., response time).
description: Tables have been harmonized as per details given [here](<https://datapages.github.io/irw/standard.html>).


description: Please find information about data licenses and citation info [here](<https://datapages.github.io/irw/docs.html>).
DOI: 10.17882/95035
title: COSTOF2, technical data from SeaMoN East, node of the EMSO-Azores observatory, 2020-2021

description: This dataset contains technical parameters (Voltage in V, current in mA, energy in Ah, internal pressure in mbar, water leak detection). This log is done by the COSTOF2 (COmmunication and STOrage Front-end). It is the Electronic core of SeaMoN East, the bottom station of EMSO-Azores dedicated to biological observations.
DOI: 10.17882/95037
title: COSTOF2, technical data from SeaMoN West, node of the EMSO-Azores observatory, 2020-2021

description: This dataset contains technical parameters (Voltage in V, current in mA, energy in Ah, internal pressure in mbar, water leak detection). This log is done by the COSTOF2 (COmmunication and STOrage Front-end,  the Electronic core of SeaMoN West, the bottom station of EMSO-Azores dedicated to geological observations.
DOI: 10.17882/95045
title: COSTOF2, technical data from SeaMoN East, node of the EMSO-Azores observatory, 2021-2022

description: This dataset contains technical parameters (Voltage in V, current in mA, energy in Ah, internal pressure in mbar, water leak detection). This log is done by the COSTOF2 (COmmunication and STOrage Front-end). It is the Electronic core of SeaMoN East, the bottom station of EMSO-Azores dedicated to biological observations.
DOI: 10.17882/95046
title: COSTOF2, technical data from SeaMoN West, node of the EMSO-Azores observatory, 2021-2022

description: This dataset contains technical parameters (Voltage in V, current in mA, energy in Ah, internal pressure in mbar, water leak detection). This log is done by the COSTOF2 (COmmunication and STOrage Front-end,  the Electronic core of SeaMoN West, the bottom station of EMSO-Azores dedicated to geological observations.
DOI: 10.17882/96738
title: COSTOF2, technical data from SeaMoN East, node of the EMSO-Azores observatory, 2022-2023

description: This dataset contains technical parameters (Voltage in V, current in mA, energy in Ah, internal pressure in mbar, water leak detection). This log is done by the COSTOF2 (COmmunication and STOrage Front-end). It is the Electronic core of SeaMoN East, the bottom station of EMSO-Azores dedicated to biological observations.
DOI: 10.17882/101826
title: COSTOF2, technical data from SeaMoN East, node of the EMSO-Azores observatory, 2023-2024

description: This dataset contains technical parameters (Voltage in V, current in mA, energy in Ah, internal pressure in mbar, water leak detection). This log is done by the COSTOF2 (COmmunication and STOrage Front-end). It is the Electronic core of SeaMoN East, the bottom station of EMSO-Azores dedicated to biological observations.
DOI: 10.17882/96739
title: COSTOF2, technical data from SeaMoN West, node of the EMSO-Azores observatory, 2022-2023

description: This dataset contains technical parameters (Voltage in V, current in mA, energy in Ah, internal pressure in mbar, water leak detection). This log is done by the COSTOF2 (COmmunication and STOrage Front-end,  the Electronic core of SeaMoN West, the bottom station of EMSO-Azores dedicated to geological observations.
DOI: 10.17882/101827
title: COSTOF2, technical data from SeaMoN West, node of the EMSO-Azores observatory, 2023-2024

description: This dataset contains technical parameters (Voltage in V, current in mA, energy in Ah, internal pressure in mbar, water leak detection). This log is done by the COSTOF2 (COmmunication and STOrage Front-end,  the Electronic core of SeaMoN West, the bottom station of EMSO-Azores dedicated to geological observations.
DOI: 10.17882/111192
title: Experimental Database of Loads and Wake of a Single Horizontal Axis Tidal Turbine (HATT) Immersed in Two Different Wave and Current Conditions

description: The present database is derived from experiments conducted on a single three-bladed horizontal axis tidal turbine (HATT) immersed at half the water depth of the IFREMER wave and current flume tank at Boulogne-sur-mer. The turbine model is subjected to wave and current conditions. The two studied wave cases are defined by their propagation direction either following (FO) or opposing (OP) the current direction.
Wave-generation induces upstream flow modifications. To evaluate the inflow conditions a pre-campaign of flow characterisation is performed without the turbine. The experimental database with the immersed turbine comprises both flow and loads measurements. Flow is monitored using a three-component Laser Doppler Velocimeter (3C-LDV). Numerous LDV acquisitions are performed to cover the fluid domain upstream and downstream of the turbine enabling the reconstruction of maps of diverse velocity-based quantities. Three wave probes aligned with the turbine rotation axis monitor the free surface elevation. Loads on the turbine rotor are acquired using a shaft transducer to measure global torque and thrust. In addition, each blade root is equipped with a five-component load cell to record local forces and moments.
These experiments continue work initiated at IFREMER wave and current flume tank over a decade ago. Furthermore, the present database fills a gap in the study of HATT wakes in wave and current conditions by delivering time-resolved data in the fluid domain. A study based on the present database (Dufour et al. 2026) is currently under review.
DOI: 10.17882/111620
title: Tidal characteristics from tide gauge data

description: Three datasets of tidal characteristics and datums from GESLA-4 tide gauges, including tidal trends, tidal duration, Highest Astronomical Tide (HAT), and Mean High Water (MHW). Tidal trends (tidal_trends.csv) were calculated solely from the University of Hawaii Sea Level Center (UHSLC) research-quality GESLA-4 dataset of gauges with more than 30 years of observations. The tidal duration (tidal_duration.csv) is created based on the full GESLA-4 dataset and is provided for locations in which spring tides are greater than approximately 0.15m and river influence is minor or negligible (see Talke (2025) for more information). The remaining tidal datums (in tidal_datums.csv) are based on 200-year tidal predictions on all tide gauges within TICON-4 (Hart-Davis et al., 2025). For all files, the ‘name’ variable is included, which is the tide gauge name as provided by GESLA-4 (https://www.gesla.org/). More information about particular tide gauge data can be found at GESLA-4.
The methods and descriptions of this dataset are expanded in Hart-Davis et al (submitted to Ocean Science). The available DOI will be made available when submitted and available. For users who are here before this, please contact the contributors to this dataset for more information. 
 
References:
Hart-Davis M.G., Sulzbach R., Haigh I., Marcos I., Talke S., Ray R., Woodworth P., Dettmering D., Thomas M., Seitz F. Global characteristics of tides from in-situ gauges. In preparation. EGUSPHERE: EGUSPHERE-2026-346
Talke, S.A., 2025. How tidal properties influence the future duration of coastal flooding. npj Natural Hazards, 2(1), p.36. https://doi.org/10.1038/s44304-025-00086-3
DOI: 10.17882/111630
title: DYBAGA CTD dataset for the Galician continental shelf (May 2001–April 2002)

description: The Dynamics and Biogeochemistry on the Galician Shelf: Short-Scale Variability project (DYBAGA, Dinámica Y Biogeoquímica annual en la plataforma GAllega: variación de corta escala, CICYT. MAR1999-1039-C02-01) was conducted between May 2001 and April 2002 and focused on the integrated observation, analysis, and modeling of the annual oceanographic cycle on the Galician continental shelf. Data were collected during 47 cruises of the research vessel Mytilus (29MY) using three different CTD systems, including a rosette-mounted CTD, resulting in more than 750 hydrographic profiles. These observations allowed the identification of distinct hydrographic regimes associated with seasonal stratification, upwelling and downwelling events, poleward current influence, winter mixing, and the subsequent restoration of spring conditions. DYBAGA constitutes a comprehensive observational and modeling framework that significantly improved the understanding of physical processes governing the Galician continental shelf.
In 2025, these hydrographic profiles were carefully reviewed within the framework of CSIC MOV-TEC-2025 grants, with the aim of recovering and preserving them for climate assessments and other scientific applications. The data were formatted following the MEDAR/MEDATLAS standard and subjected to quality-control procedures. These actions ensure compliance with FAIR data principles and facilitate their inclusion in international repositories, thereby promoting data reuse and open science.
DOI: 10.6084/m9.figshare.30141529.v1
title: Schematic 2D representation of acoustic scattering by an obstacle

description: The scattered field u<sub>sct</sub> is generated by an incident wave u_inc in a domain Ω<sub>P</sub>, bounded internally by a circular interface Γ<sub>I</sub> of radius r<sub>i</sub>, and externally by a square boundary Γ<sub>E</sub> of semi-length l<sub>e</sub>. The incident plane wave propagates towards the obstacle, interacts with the circular interface, and produces the scattered field, which is evaluated within the computational domain Ω<sub>P</sub>.
DOI: 10.15468/dl.9sskzu
title: Occurrence Download

description: A dataset containing 258 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((3.64569 39.72363,4.52369 39.72363,4.52369 40.07519,3.64569 40.07519,3.64569 39.72363))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pinus halepensis"
 ]
}

 The dataset includes 258 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007433-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h7gbf3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.79533499999999 23.833744, 88.71856699999999 23.828167, 88.643708 23.811575, 88.572619 23.78438, 88.507064 23.747259, 88.448666 23.701133, 88.398865 23.647146, 88.358885 23.586638, 88.3297 23.521104, 88.312016 23.452165, 88.306251 23.381522, 88.312528 23.310916, 88.330674 23.242084, 88.360225 23.176717, 88.400441 23.116417, 88.450323 23.062663, 88.50864 23.01677, 88.573959 22.979858, 88.644682 22.95283, 88.71907899999999 22.936344, 88.79533499999999 22.930804, 88.871591 22.936344, 88.945988 22.95283, 89.016711 22.979858, 89.08203 23.01677, 89.14034700000001 23.062663, 89.190229 23.116417, 89.230445 23.176717, 89.259996 23.242084, 89.278142 23.310916, 89.284419 23.381522, 89.278654 23.452165, 89.26097 23.521104, 89.231785 23.586638, 89.191805 23.647146, 89.142004 23.701133, 89.083606 23.747259, 89.018051 23.78438, 88.946962 23.811575, 88.872103 23.828167, 88.79533499999999 23.833744))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007434-260120142942310/datasets/export for details.
DOI: 10.15468/dl.3wd9m8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.833538 24.094689, 88.756615 24.089112, 88.681606 24.07252, 88.61037399999999 24.045326, 88.54468900000001 24.008204, 88.486175 23.962078, 88.43627600000001 23.908092, 88.396218 23.847584, 88.366979 23.782052, 88.34926299999999 23.713114, 88.34348900000001 23.642474, 88.349782 23.57187, 88.36796699999999 23.503041, 88.397578 23.437677, 88.43787500000001 23.377381, 88.48785599999999 23.32363, 88.54628700000001 23.277739, 88.611734 23.24083, 88.68259399999999 23.213804, 88.75713500000001 23.19732, 88.833538 23.19178, 88.909941 23.19732, 88.984482 23.213804, 89.055342 23.24083, 89.120789 23.277739, 89.17922 23.32363, 89.229201 23.377381, 89.269498 23.437677, 89.299109 23.503041, 89.317294 23.57187, 89.323587 23.642474, 89.317813 23.713114, 89.30009699999999 23.782052, 89.270858 23.847584, 89.2308 23.908092, 89.18090100000001 23.962078, 89.122387 24.008204, 89.056702 24.045326, 88.98547000000001 24.07252, 88.910461 24.089112, 88.833538 24.094689))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007435-260120142942310/datasets/export for details.