cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.8sy6wp
title: Occurrence Download

description: A dataset containing 622767 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Croatia",
 "Geometry POLYGON((13.1 42.1,19.9 42.1,19.9 46.8,13.1 46.8,13.1 42.1))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 622767 records from 546 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0213557-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hnrhfa
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tinamiformes)",
 "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((-70 -90,-60 -90,-60 -80,-70 -80,-70 -90))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018425-251009101135966/datasets/export for details.
DOI: 10.15468/dl.nqadum
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lantanophaga pusillidactylus",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018422-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7st922
title: Occurrence Download

description: A dataset containing 664 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Netherlands",
 "Geometry POLYGON((5.82021 52.76459,6.08703 52.76459,6.08703 52.94862,5.82021 52.94862,5.82021 52.76459))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Boloria selene",
 "Year 2000-2025"
 ]
}

 The dataset includes 664 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018424-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29710910
title: Naskah Ringkas

description: Cities have a significant influence in determining human experience through sensations and perceptions experienced when carrying out physical activities.
DOI: 10.6084/m9.figshare.29710910.v1
title: Naskah Ringkas

description: Cities have a significant influence in determining human experience through sensations and perceptions experienced when carrying out physical activities.
DOI: 10.15156/bio/sh1404681.10fu
title: SH1404681.10FU

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/sh1404683.10fu
title: SH1404683.10FU

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/sh1404686.10fu
title: SH1404686.10FU

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/sh1404689.10fu
title: SH1404689.10FU

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/sh1404693.10fu
title: SH1404693.10FU

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/sh1404695.10fu
title: SH1404695.10FU

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/sh1404697.10fu
title: SH1404697.10FU

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/sh1404698.10fu
title: SH1404698.10FU

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/sh1404699.10fu
title: SH1404699.10FU

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: 10.7910/dvn/akikkc
title: Survey Data on Generic Skills and Labour Market Prospects among University Graduates in Chile (2024)

description: Este conjunto de datos contiene información anonimizada proveniente de una encuesta aplicada en 2024 a 2.792 titulados universitarios en Chile. La encuesta fue desarrollada en el marco del proyecto Fondecyt 1230080 financiado por la Agencia Nacional de Investigación y Desarrollo (ANID) y examina la adquisición percibida de competencias genéricas, la percepción de ajuste entre formación y empleo, y las perspectivas laborales durante la transición desde la universidad al mercado de trabajo. Se han eliminado todos los identificadores directos. El acceso al conjunto de datos se encuentra restringido debido a la presencia de variables institucionales y sociodemográficas que podrían permitir una identificación indirecta.
DOI: 10.5281/zenodo.18760119
title: Systematic Literature Review Dataset – Customer Experience in the Hotel Industry

description: 1. Description

This dataset contains the full extraction matrix used in the systematic literature review (SLR) published in:

Veloso, M., & Gómez-Suárez, M. (2023). Customer experience in the hotel industry: a systematic literature review and research agenda. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/IJCHM-04-2022-0517

The dataset includes all articles identified and selected through a PRISMA-based procedure from Scopus and Web of Science databases.

The final sample includes 46 peer-reviewed journal articles (2006–2021) focused exclusively on customer experience (CX) in the hotel industry.

 

2. Search strategy

Databases:



Scopus

Web of Science


Keywords used:



“Customer experience” AND hotel

“Consumer experience” AND hotel

“Brand experience” AND hotel

“Hotel experience”

“Guest experience”


Selection procedure:



Identification

Screening

Eligibility

Inclusion (PRISMA adapted protocol)


Initial records: 1,236After screening: 281After eligibility assessment: 142Final included articles: 46

 

3. Variables included in dataset

The dataset contains the following variables (adaptar a lo que efectivamente esté en tu Excel):



Author(s)

Year

Journal

Country/context

Methodology (quantitative, qualitative, mixed)

Data collection method

Theoretical framework used

Definition of CX

CX dimensions

Antecedents

Consequences

Mediators

Moderators

Research gaps identified


 

4. Inclusion criteria



Peer-reviewed journal articles

English language

Focus exclusively on customer experience in hotels

Title or abstract includes selected keywords


Exclusion criteria:



Studies focused on Airbnb or peer-to-peer accommodations

Studies addressing hospitality in general without specific hotel focus


 

5. File format



XLSX format

No personal or confidential data included

All data extracted from published academic sources
DOI: 10.5281/zenodo.18760118
title: Systematic Literature Review Dataset – Customer Experience in the Hotel Industry

description: 1. Description

This dataset contains the full extraction matrix used in the systematic literature review (SLR) published in:

Veloso, M., & Gómez-Suárez, M. (2023). Customer experience in the hotel industry: a systematic literature review and research agenda. International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/IJCHM-04-2022-0517

The dataset includes all articles identified and selected through a PRISMA-based procedure from Scopus and Web of Science databases.

The final sample includes 46 peer-reviewed journal articles (2006–2021) focused exclusively on customer experience (CX) in the hotel industry.

 

2. Search strategy

Databases:



Scopus

Web of Science


Keywords used:



“Customer experience” AND hotel

“Consumer experience” AND hotel

“Brand experience” AND hotel

“Hotel experience”

“Guest experience”


Selection procedure:



Identification

Screening

Eligibility

Inclusion (PRISMA adapted protocol)


Initial records: 1,236After screening: 281After eligibility assessment: 142Final included articles: 46

 

3. Variables included in dataset

The dataset contains the following variables (adaptar a lo que efectivamente esté en tu Excel):



Author(s)

Year

Journal

Country/context

Methodology (quantitative, qualitative, mixed)

Data collection method

Theoretical framework used

Definition of CX

CX dimensions

Antecedents

Consequences

Mediators

Moderators

Research gaps identified


 

4. Inclusion criteria



Peer-reviewed journal articles

English language

Focus exclusively on customer experience in hotels

Title or abstract includes selected keywords


Exclusion criteria:



Studies focused on Airbnb or peer-to-peer accommodations

Studies addressing hospitality in general without specific hotel focus


 

5. File format



XLSX format

No personal or confidential data included

All data extracted from published academic sources
DOI: 10.17026/ls/s9awrz
title: Materials underlying the research article “Mitigating terrain shadows in very high-resolution satellite imagery for accurate evergreen conifer detection using bi-temporal image fusion”

description: &lt;p&gt;Dataset for: "Mitigating terrain shadows in very high-resolution satellite imagery for accurate evergreen conifer detection using bi-temporal image fusion". The manuscript was published in International Journal of Applied Earth Observation and Geoinformation in October 2024.&lt;/p&gt;

&lt;p&gt;Very high-resolution (VHR) optical satellite imagery offers significant potential for detailed land cover mapping. However, terrain shadows, which appear dark and lack texture and detail, are especially acute at low solar elevations. These shadows hinder the creation of spatially complete and accurate land cover maps, particularly in rugged mountainous environments. While many methods have been proposed to mitigate terrain shadows in remote sensing, they either perform insufficient shadow reduction or rely on high-resolution digital elevation models which are often unavailable for VHR image shadow mitigation. In this paper, we propose a bi-temporal image fusion approach to mitigate terrain shadows in VHR satellite imagery. Our approach fuses a WorldView-2 multispectral image, which contains significant terrain shadows, with a corresponding geometrically registered WorldView-1 panchromatic image, which has minimal shadows. This fusion is applied to improve the mapping of evergreen conifers in temperate mixed mountain forests. To evaluate the effectiveness of our approach, we first improve an existing shadow detection method by Silva et al. (2018) to more accurately detect shadows in mountainous, forested landscapes. Next, we propose a quantitative algorithm that differentiates dark and light terrain shadows in VHR satellite imagery based on object visibility in shadowed areas. Finally, we apply a state-of-the-art 3D U-Net deep learning method to detect evergreen conifers. Our study shows that the proposed approach significantly reduces terrain shadows and enhances the detection of evergreen conifers in shaded areas. This is the first time a bi-temporal image fusion approach has been used to mitigate terrain shadow effects for land cover mapping at a very high spatial resolution. This approach can also be applied to other VHR satellite sensors. However, careful image co-registration will be necessary when applying this technique to multi-sensor systems beyond the WorldView constellation, such as Pléiades or SkySat.&lt;/p&gt;
DOI: 10.7910/dvn/kvz3od
title: Media References - Constructing female terrorism - ISBN 978-1-78821-896-2

description: Media references to accompany Constructing female terrorism - ISBN 978-1-78821-896-2
DOI: 10.15468/dl.zhmcc5
title: Occurrence Download

description: A dataset containing 1168 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hesperocyparis arizonica"
 ]
}

 The dataset includes 1168 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007524-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eap86e
title: Occurrence Download

description: A dataset containing 99882 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Crocodylus porosus"
 ]
}

 The dataset includes 99882 records from 100 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007471-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hu3yp4
title: Occurrence Download

description: A dataset containing 1760003 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vulpes vulpes"
 ]
}

 The dataset includes 1760003 records from 4013 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007448-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tv7nwr
title: Occurrence Download

description: A dataset containing 392 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Celosia argentea",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 392 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011648-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bsws8s
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Hemiergis decresiensis)",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011651-250717081556266/datasets/export for details.