cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28887896.v1
title: MDPI remote sensing - publication data - Improving the Regional Precipitation Simulation Corrected by Satellite Observation Using Quantile Mapping

description: <b>Abstract</b>: <br>This study investigates how to use the gridded satellite datasets of observational precipitation to improve the performance of the climatological simulation by using the method of non-parametric quantile mapping (QM). The precipitation in Southeast Asia is simulated in 2001–2005 using the climate model of Weather Research and Forecasting (WRF). Two satellite datasets of observational precipitation, GSMaP and CHIRPS, are used for model training, simulation evaluation, and cross-validation. The evaluations of simulation and bias correction suggest that QM is able to perfectly correct the overall quantile distributions of the simulated precipitation, which has overestimation at most quantiles, especially for light and extreme precipitation. After the QM correction based on GSMaP (CHIRPS), the relative bias of the monthly average for all months is reduced from 39.3% to 4.1% (from 57.2% to 4.2%). The biases of spatial patterns are largely narrowed from 43.5% (59.4%) to 4.0% (2.5%) for annual-mean precipitation and from 43.5% (59.4%) to 4.0% (2.5%) for extreme precipitation. The results indicate that the QM correction based on the gridded satellite datasets outperforms the raw model output and greatly improves the estimates of the simulated precipitation.<br><b>Dataset description:</b>Name regulation: XXX05: 5km; XXX10: 10km; 01-12: 12 months; OBS: observation; WRF: WRF simulation; QMC: quantile mapping correction.<br>Folder "grid_data_OBS": daily grid data of observation;<br>Folder "grid_data_WRF": daily grid data of WRF simulation;<br>Folder "grid_data_QMC": daily grid data of QM correction;Folder "Figure 2 - cdf_OBS_WRF_QMC": data for results in Figure 2;<br>Folder "Figure 3 - statistics_mon_QMC": data for results in Figure 3;Folder "Figure 4 - annual precipitation": data for results in Figure 4;<br>Folder "Figure 5 - extreme precipitation": data for results in Figure 5.
DOI: 10.15468/dl.td2qfc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-04-03",
 "EventDate is less than or equal to 2025-05-03",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004182-250426092105405/datasets/export for details.
DOI: 10.15468/dl.zt33a2
title: Occurrence Download

description: A dataset containing 326 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Petrocodon Hance"
 ]
}

 The dataset includes 326 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004256-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15213031
title: Dataset for: Determinants of IPO Underpricing in the UK: An Empirical Analysis from 2014 to 2024

description: Description

This repository contains 2 files related to the construction and cleaning of a comprehensive dataset on UK IPOs from Jan 2014 to Nov 2024. The dataset has been used in regression analyses for my bachelor’s research, and all steps, from initial data collection to final adjustments, are documented and provided for transparency and reproducibility.

The repository includes the following files:

1. Excel Dataset FileThis single Excel file comprises multiple sheets, each detailing a different aspect of the data preparation and analysis. Important sheets include:



Regression_Final: Contains all 616 IPOs after cleaning and adjustments, with the variables (highlighted in yellow) that were used in the final regression analyses.

Rough: Provides the initial matching of 616 IPOs sourced from the London Stock Exchange (LSE), Bloomberg (BB), and Refinitiv (RF). In this sheet, rows with dates and issuer names marked in red indicate deletions (e.g., SPACs, funds, duplicates), while blue-highlighted cells denote manual overrides such as stock splits, currency adjustments, or listing date corrections.

Variable Breakdown, Backing Data, and Originals: Additional sheets break down the key variables, include supporting data (e.g., FTSE price and volatility, currency data), and provide the original downloaded tables for reference and verification.


2. Data Collection Documentation:This supplementary document details the methodology used for data collection, cleaning, and manual adjustments. It explains the procedures, criteria, and any assumptions made during the process, ensuring that the dataset is reproducible and transparent for future research.
DOI: 10.15468/dl.vz75y5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-04-03",
 "EventDate is less than or equal to 2025-05-03",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003305-250426092105405/datasets/export for details.
DOI: 10.15468/dl.cjxmdq
title: Occurrence Download

description: A dataset containing 84 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-10.52169 28.27902,44.72557 28.27902,44.72557 52.02473,-10.52169 52.02473,-10.52169 28.27902))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Tetronarce nobiliana (Bonaparte, 1835)"
 ]
}

 The dataset includes 84 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004255-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10480821
title: Rodzaj gramatyczny nazw wybranych krzewów w polszczyźnie ludowej. Dane badawcze (leksykograficzne, folklorystyczne i etnograficzne)

description: Dane badawcze związane z realizacją grantu Narodowego Centrum Nauki pt. Polskie ludowe relacje między człowiekiem i rośliną (na przykładzie krzewów). Badania z pogranicza etnolingwistyki i etnobotaniki (nr projektu: 2021/43/D/HS2/01019; kierownik projektu: dr Olga Kielak)

Dokument zawiera trzy rodzaje danych badawczych, które zostały wykorzystane w analizach w artykule poświęconym rodzajowi gramatycznemu wybranych krzewów w polszczyźnie ludowej (Olga Kielak, Czy krzewy mają „płeć”? O rodzaju gramatycznym nazw wybranych krzewów w polszczyźnie ludowej, „Język Polski” 2023, R. CIII, z. 4, s. 77–90). Są to: (a) dane leksykograficzne – pozyskane ze słowników ogólnopolskich i gwarowych języka polskiego; (b) dane folklorystyczne – pieśni (weselne, zalotne/miłosne, rodzinne, dożynkowe), formuły magiczne oraz legendy ajtiologiczne; (c) dane etnograficzne – zapisy wierzeń i opisy praktyk. Zgromadzone dane przynależną do różnych stadiów czasowych – od przełomu XVIII i XIX wieku, aż po czasy współczesne, z przewagą materiałów starszych. W dokumencie zostały one opatrzone metrykami (skrótami), których rozwinięcia zamieszczone są w bibliografii.

Wszelkie analizy prowadzone w oparciu o zebrane dane źródłowe przeprowadzane były z wykorzystaniem metodologii językoznawczej (definicja kognitywna).
DOI: 10.5281/zenodo.10480822
title: Rodzaj gramatyczny nazw wybranych krzewów w polszczyźnie ludowej. Dane badawcze (leksykograficzne, folklorystyczne i etnograficzne)

description: Dane badawcze związane z realizacją grantu Narodowego Centrum Nauki pt. Polskie ludowe relacje między człowiekiem i rośliną (na przykładzie krzewów). Badania z pogranicza etnolingwistyki i etnobotaniki (nr projektu: 2021/43/D/HS2/01019; kierownik projektu: dr Olga Kielak)

Dokument zawiera trzy rodzaje danych badawczych, które zostały wykorzystane w analizach w artykule poświęconym rodzajowi gramatycznemu wybranych krzewów w polszczyźnie ludowej (Olga Kielak, Czy krzewy mają „płeć”? O rodzaju gramatycznym nazw wybranych krzewów w polszczyźnie ludowej, „Język Polski” 2023, R. CIII, z. 4, s. 77–90). Są to: (a) dane leksykograficzne – pozyskane ze słowników ogólnopolskich i gwarowych języka polskiego; (b) dane folklorystyczne – pieśni (weselne, zalotne/miłosne, rodzinne, dożynkowe), formuły magiczne oraz legendy ajtiologiczne; (c) dane etnograficzne – zapisy wierzeń i opisy praktyk. Zgromadzone dane przynależną do różnych stadiów czasowych – od przełomu XVIII i XIX wieku, aż po czasy współczesne, z przewagą materiałów starszych. W dokumencie zostały one opatrzone metrykami (skrótami), których rozwinięcia zamieszczone są w bibliografii.

Wszelkie analizy prowadzone w oparciu o zebrane dane źródłowe przeprowadzane były z wykorzystaniem metodologii językoznawczej (definicja kognitywna).
DOI: 10.5281/zenodo.10553181
title: Lexicographic, ethnographic, and folkloric material utilized in the analysis of popular names for the black elder (Sambucus nigra)

description: Research data related to the implementation of the National Science Centre grant entitled "The relationships between man and plant in Polish folklore (on the example of shrubs). Studies on the border between ethnolinguistics and ethnobotany" (project number: 2021/43/D/HS2/01019; project manager: Dr. Olga Kielak).

The document contains three types of research data utilized in the analyses presented in the article on Polish names for black elder (Sambucus nigra) [Olga Kielak, From the name to the popular image of the plant: the Polish names for the black elder (Sambucus nigra), "Journal of Ethnobiology and Ethnomedicine" 2024, 20, 12]. These include: (a) lexicographic data – nationwide and dialectal names for black elder (Sambucus nigra) extracted from general and dialectal dictionaries of the Polish language, obtained during on-site queries in two card catalogs: the Krakow Dictionary of Polish Dialects by the Polish Academy of Sciences and the Lublin Ethnolinguistic Workshop named after Jerzy Bartmiński, as well as noted from 19th- and 20th-century ethnographic sources; (b) ethnographic data – contexts containing folk beliefs, convictions, and practices, extracted from ethnographic sources published at the turn of the 19th and 20th centuries (monographs and articles published in ethnographic journals, including "Zbiór Wiadomości do Anthropologii Krajowej" "Wisła," and "Lud"), as well as from material publications gathering field-recorded informal accounts; and (c) folkloric data (etiological legend). The collected research data span various time periods—from the late 18th and 19th centuries to contemporary times, with a prevalence of older materials. The document includes metrics (abbreviations), the resolution of which is provided in the bibliography.

All analyses conducted based on the collected source data were carried out using a linguistic methodology (cognitive definition).
DOI: 10.5281/zenodo.10553182
title: Lexicographic, ethnographic, and folkloric material utilized in the analysis of popular names for the black elder (Sambucus nigra)

description: Research data related to the implementation of the National Science Centre grant entitled "The relationships between man and plant in Polish folklore (on the example of shrubs). Studies on the border between ethnolinguistics and ethnobotany" (project number: 2021/43/D/HS2/01019; project manager: Dr. Olga Kielak).

The document contains three types of research data utilized in the analyses presented in the article on Polish names for black elder (Sambucus nigra) [Olga Kielak, From the name to the popular image of the plant: the Polish names for the black elder (Sambucus nigra), "Journal of Ethnobiology and Ethnomedicine" 2024, 20, 12]. These include: (a) lexicographic data – nationwide and dialectal names for black elder (Sambucus nigra) extracted from general and dialectal dictionaries of the Polish language, obtained during on-site queries in two card catalogs: the Krakow Dictionary of Polish Dialects by the Polish Academy of Sciences and the Lublin Ethnolinguistic Workshop named after Jerzy Bartmiński, as well as noted from 19th- and 20th-century ethnographic sources; (b) ethnographic data – contexts containing folk beliefs, convictions, and practices, extracted from ethnographic sources published at the turn of the 19th and 20th centuries (monographs and articles published in ethnographic journals, including "Zbiór Wiadomości do Anthropologii Krajowej" "Wisła," and "Lud"), as well as from material publications gathering field-recorded informal accounts; and (c) folkloric data (etiological legend). The collected research data span various time periods—from the late 18th and 19th centuries to contemporary times, with a prevalence of older materials. The document includes metrics (abbreviations), the resolution of which is provided in the bibliography.

All analyses conducted based on the collected source data were carried out using a linguistic methodology (cognitive definition).
DOI: 10.15468/dl.fmueve
title: Occurrence Download

description: A dataset containing 486515 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Reynoutria Houtt."
 ]
}

 The dataset includes 486515 records from 2031 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004252-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/y2weav
title: Conservación y preservación de tortugas marinas (aggregated per 1-degree cell)

description: Original provider:
CRAM-UPV

Dataset credits:
Data provider
Seguimiento de juveniles de Tortuga boba
Originating data center
&lt;a href='http://www.seaturtle.org/tracking/' target='_blank'&gt;Satellite Tracking and Analysis Tool (STAT)&lt;/a&gt;
Project partner
Universitat Politècnica de València
Project sponsor or sponsor description
Financiación Fundación Banco Santander, Fundación CRAM, Universitat Politècnica de València
 This dataset is a summarized representation of the telemetry locations aggregated per species per 1-degree cell.
DOI: 10.15468/dl.rndyp2
title: Occurrence Download

description: A dataset containing 1682084193 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 1682084193 records from 19240 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024234-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0172690.10fu
title: SH0172690.10FU

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/sh0172691.10fu
title: SH0172691.10FU

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/sh0172692.10fu
title: SH0172692.10FU

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/sh0172693.10fu
title: SH0172693.10FU

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/sh0172694.10fu
title: SH0172694.10FU

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/sh0172695.10fu
title: SH0172695.10FU

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/sh0172696.10fu
title: SH0172696.10FU

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.