cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13020/bagf-h278
title: Creating a patient-centered report card for solid organ transplant candidates

description: Choosing a transplant center that will accept a particular candidate can be difficult and challenging for patients with end-stage organ failure. As transplant centers have varying levels of expertise, interests, and outcomes of solid organ transplant, patient health-related characteristics influence the variation in candidates centers will accept. Most transplant candidates undergo waitlist work-ups as outpatients and many undergo transplant at centers not closest to their homes. Some are listed at more than one center. Several studies suggest that patients have a choice of centers. The PI, as Deputy Director of the Scientific Registry of Transplant Recipients (SRTR), provides comparative information to the public about each solid organ transplant center in the United States. The risk adjusted outcomes, in the report cards, account for the transplant recipient's health-related characteristics, donor characteristics and transplant related factors. Many transplant centers provide a print-out of this SRTR report card to their candidates to comply with Centers for Medicare Medicaid rules. Unfortunately, in their current format, the report cards are not designed for transplant candidates, many of whom may have low health literacy and numeracy. The proposed work aims to develop and evaluate a patient-centered website and printouts of the SRTR report cards that will effectively communicate comparative information to transplant candidates about their alternatives when choosing transplant centers. We will develop a novel tool to allow candidates to tailor the report cards to their clinical profiles based on their health-related characteristics and to communicate information on alternative transplant centers that perform transplants in patients like them. The website will also allow patients to self-refer to centers.

Here, we provide copies of the interview / focus group guide as well as examples of the demographic / clinical questionnaires completed by study participants. We are releasing these materials to allow for greater insight into the study and to enhance reproducibility.
description: A. Filename: AHRQ Discussion Guide 
 Short description: The file includes an example of the discussion guide used for interviews and focus groups. 

 B. Filename: AHRQ Kidney Candidate-Recipient Questionnaire 
 Short description: The file includes the demographic/clinical questionnaire used for kidney patients. 
 
 C. Filename: AHRQ Kidney Family Questionnaire 
 Short description: The file includes the demographic/clinical questionnaire used for the family members of kidney patients.
DOI: 10.15468/dl.m2phfr
title: Occurrence Download

description: A dataset containing 410 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((146.557142 -36.083784, 146.563879 -36.083784, 146.563879 -36.079293, 146.559388 -36.079293, 146.559388 -36.077047, 146.557142 -36.077047, 146.557142 -36.083784)), ((146.557142 -36.083784, 146.548159 -36.083784, 146.548159 -36.079293, 146.543667 -36.079293, 146.543667 -36.081539, 146.545913 -36.081539, 146.545913 -36.08603, 146.539176 -36.08603, 146.539176 -36.083784, 146.53693 -36.083784, 146.53693 -36.081539, 146.532438 -36.081539, 146.532438 -36.083784, 146.534684 -36.083784, 146.534684 -36.088276, 146.527947 -36.088276, 146.527947 -36.081539, 146.530192 -36.081539, 146.530192 -36.074801, 146.527947 -36.074801, 146.527947 -36.077047, 146.523455 -36.077047, 146.523455 -36.079293, 146.521209 -36.079293, 146.521209 -36.077047, 146.512226 -36.077047, 146.512226 -36.090522, 146.514472 -36.090522, 146.514472 -36.079293, 146.518963 -36.079293, 146.518963 -36.092768, 146.521209 -36.092768, 146.521209 -36.095013, 146.518963 -36.095013, 146.518963 -36.097259, 146.525701 -36.097259, 146.525701 -36.095013, 146.534684 -36.095013, 146.534684 -36.092768, 146.53693 -36.092768, 146.53693 -36.097259, 146.541421 -36.097259, 146.541421 -36.099505, 146.543667 -36.099505, 146.543667 -36.101751, 146.548159 -36.101751, 146.548159 -36.099505, 146.550405 -36.099505, 146.550405 -36.097259, 146.55265 -36.097259, 146.55265 -36.095013, 146.557142 -36.095013, 146.557142 -36.092768, 146.559388 -36.092768, 146.559388 -36.088276, 146.557142 -36.088276, 146.557142 -36.083784)), ((146.557142 -36.077047, 146.557142 -36.072555, 146.566125 -36.072555, 146.566125 -36.068064, 146.568371 -36.068064, 146.568371 -36.063572, 146.566125 -36.063572, 146.566125 -36.065818, 146.559388 -36.065818, 146.559388 -36.068064, 146.557142 -36.068064, 146.557142 -36.07031, 146.554896 -36.07031, 146.554896 -36.068064, 146.548159 -36.068064, 146.548159 -36.072555, 146.55265 -36.072555, 146.55265 -36.077047, 146.557142 -36.077047)), ((146.566125 -36.072555, 146.566125 -36.077047, 146.568371 -36.077047, 146.568371 -36.072555, 146.566125 -36.072555)))"
 ]
}

 The dataset includes 410 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074605-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3azwad
title: Occurrence Download

description: A dataset containing 64572 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aedes aegypti (Linnaeus, 1762)"
 ]
}

 The dataset includes 64572 records from 92 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074603-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x9xxwa
title: Occurrence Download

description: A dataset containing 120996 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Penelope purpurascens Wagler, 1830"
 ]
}

 The dataset includes 120996 records from 147 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074593-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13344937
title: Investigando o Uso da Inteligência Artificial em Projetos Python Hospedados no GitHub

description: This dataset was utilized in the research paper titled "Investigando o Uso da Inteligência Artificial em Projetos Python Hospedados no GitHub," accepted for publication in the 12th Workshop on Software Visualization, Evolution, and Maintenance. This study aims to explore the presence and usage of artificial intelligence libraries in Python projects hosted on GitHub.

To achieve this, we developed a Python script that analyzes repositories listed in a CSV file, checking for dependencies related to AI. The script utilizes GitHub’s API to access repository data and inspect `requirements.txt` files for mentions of AI libraries. The dataset includes information on repositories that use specific AI libraries, such as TensorFlow, PyTorch, and scikit-learn. By examining these dependencies, the study provides insights into how frequently and in what contexts these libraries are used in real-world Python projects. This research contributes to understanding the adoption of AI technologies in software development and supports practitioners in identifying relevant AI tools in the Python ecosystem.
DOI: 10.5281/zenodo.13344938
title: Investigando o Uso da Inteligência Artificial em Projetos Python Hospedados no GitHub

description: This dataset was utilized in the research paper titled "Investigando o Uso da Inteligência Artificial em Projetos Python Hospedados no GitHub," accepted for publication in the 12th Workshop on Software Visualization, Evolution, and Maintenance. This study aims to explore the presence and usage of artificial intelligence libraries in Python projects hosted on GitHub.

To achieve this, we developed a Python script that analyzes repositories listed in a CSV file, checking for dependencies related to AI. The script utilizes GitHub’s API to access repository data and inspect `requirements.txt` files for mentions of AI libraries. The dataset includes information on repositories that use specific AI libraries, such as TensorFlow, PyTorch, and scikit-learn. By examining these dependencies, the study provides insights into how frequently and in what contexts these libraries are used in real-world Python projects. This research contributes to understanding the adoption of AI technologies in software development and supports practitioners in identifying relevant AI tools in the Python ecosystem.
DOI: 10.15468/dl.gmx9h8
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Holocentropus glacialis Ross, 1938"
 ]
}

 The dataset includes 60 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074606-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.32fcba
title: Occurrence Download

description: A dataset containing 156 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((146.581846 -36.101751, 146.599812 -36.101751, 146.599812 -36.099505, 146.581846 -36.099505, 146.581846 -36.101751)), ((146.581846 -36.101751, 146.5796 -36.101751, 146.5796 -36.103997, 146.581846 -36.103997, 146.581846 -36.101751)))"
 ]
}

 The dataset includes 156 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074607-240626123714530/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.25057808
title: <b>Zebrafish Model of Okur-Chung Neurodevelopmental Syndrome (OCNDS) </b>

description: Okur-Chung Neurodevelopmental Syndrome (OCNDS) is a rare autosomal dominant disorder caused by heterozygous pathogenic variants of the CSNK2A1 gene. CSNK2A1 encodes the α-subunit of the CK2 (Casein Kinase 2) and is involved in diverse biological processes. In this study, we collected data by employing a CK2 inhibitor and overexpression of mutant and wild-type csnk2a1 mRNA in a zebrafish model to investigate the functional consequences of selected CSNK2A1 variants implicated in Okur-Chung Neurodevelopmental Syndrome (OCNDS). The dataset provides comprehensive dose-response data for a CK2 inhibitor, demonstrating how varying doses influence zebrafish morphology and phenotypic outcomes. In addition, the dataset includes analyses of specific morphological and phenotypic changes resulting from the expression of both wild-type and mutant csnk2a1 mRNA in zebrafish. It also covers rescue experiments aimed at mitigating these mutant phenotypes, highlighting the utility of zebrafish as an adaptable model system for examining the functional impact of CSNK2A1 mutations.
DOI: 10.6084/m9.figshare.25057808.v3
title: <b>Zebrafish Model of Okur-Chung Neurodevelopmental Syndrome (OCNDS) </b>

description: Okur-Chung Neurodevelopmental Syndrome (OCNDS) is a rare autosomal dominant disorder caused by heterozygous pathogenic variants of the CSNK2A1 gene. CSNK2A1 encodes the α-subunit of the CK2 (Casein Kinase 2) and is involved in diverse biological processes. In this study, we collected data by employing a CK2 inhibitor and overexpression of mutant and wild-type csnk2a1 mRNA in a zebrafish model to investigate the functional consequences of selected CSNK2A1 variants implicated in Okur-Chung Neurodevelopmental Syndrome (OCNDS). The dataset provides comprehensive dose-response data for a CK2 inhibitor, demonstrating how varying doses influence zebrafish morphology and phenotypic outcomes. In addition, the dataset includes analyses of specific morphological and phenotypic changes resulting from the expression of both wild-type and mutant csnk2a1 mRNA in zebrafish. It also covers rescue experiments aimed at mitigating these mutant phenotypes, highlighting the utility of zebrafish as an adaptable model system for examining the functional impact of CSNK2A1 mutations.
DOI: 10.6084/m9.figshare.25057808.v2
title: Metadata on <i>csnk2a1</i> Mutant-Induced Morphological Phenotypes in Zebrafish

description: Okur-Chung Neurodevelopmental Syndrome (OCNDS) is a rare autosomal dominant disorder caused by heterozygous pathogenic variants of the CSNK2A1 gene. CSNK2A1 encodes the α-subunit of the CK2 (Casein Kinase 2) and is involved in diverse biological processes. In this study, we collected data by employing a CK2 inhibitor and overexpression of mutant and wild-type csnk2a1 mRNA in a zebrafish model to investigate the functional consequences of selected CSNK2A1 variants implicated in Okur-Chung Neurodevelopmental Syndrome (OCNDS). The dataset provides comprehensive dose-response data for a CK2 inhibitor, demonstrating how varying doses influence zebrafish morphology and phenotypic outcomes. In addition, the dataset includes analyses of specific morphological and phenotypic changes resulting from the expression of both wild-type and mutant csnk2a1 mRNA in zebrafish. It also covers rescue experiments aimed at mitigating these mutant phenotypes, highlighting the utility of zebrafish as an adaptable model system for examining the functional impact of CSNK2A1 mutations.
DOI: 10.15468/dl.v4tkyw
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Holocentropus glacialis Ross, 1938"
 ]
}

 The dataset includes 60 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074608-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5ve8tk
title: Occurrence Download

description: A dataset containing 979 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((146.604304 -36.083784, 146.604304 -36.08603, 146.60655 -36.08603, 146.60655 -36.083784, 146.604304 -36.083784)), ((146.60655 -36.08603, 146.60655 -36.088276, 146.608795 -36.088276, 146.608795 -36.090522, 146.60655 -36.090522, 146.60655 -36.092768, 146.604304 -36.092768, 146.604304 -36.097259, 146.60655 -36.097259, 146.60655 -36.095013, 146.611041 -36.095013, 146.611041 -36.099505, 146.613287 -36.099505, 146.613287 -36.092768, 146.611041 -36.092768, 146.611041 -36.08603, 146.60655 -36.08603)), ((146.611041 -36.099505, 146.60655 -36.099505, 146.60655 -36.101751, 146.611041 -36.101751, 146.611041 -36.099505)), ((146.611041 -36.08603, 146.613287 -36.08603, 146.613287 -36.083784, 146.611041 -36.083784, 146.611041 -36.08603)))"
 ]
}

 The dataset includes 979 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074609-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2yx768
title: Occurrence Download

description: A dataset containing 2304 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Colombia",
 "Geometry POLYGON((-75.00513 4.92297,-74.95066 4.92297,-74.95066 4.96634,-75.00513 4.96634,-75.00513 4.92297))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2304 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074610-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xjq5jq
title: Occurrence Download

description: A dataset containing 899 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Specimen, Material citation)",
 "TaxonKey is Sceloporus bicanthalis Smith, 1937"
 ]
}

 The dataset includes 899 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074611-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fr2feh
title: Occurrence Download

description: A dataset listing the 647815 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 647815 records were derived from 10592 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074594-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/5y74zx
title: Calliphoridae (Blowflies) of Ireland

description: Distributional data of the Calliphoridae in Ireland.
DOI: 10.34740/kaggle/dsv/14343107
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.cn24ny
title: Occurrence Download

description: A dataset containing 155005 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Korea, Republic of",
 "OccurrenceStatus is Present",
 "TaxonKey is Insecta",
 "Year 2019-2023"
 ]
}

 The dataset includes 155005 records from 157 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069181-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jtysap
title: Occurrence Download

description: A dataset containing 410 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Leucas aspera"
 ]
}

 The dataset includes 410 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069198-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nnpmzb
title: Occurrence Download

description: A dataset containing 264 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Oenanthe javanica",
 "Year 1970-2000"
 ]
}

 The dataset includes 264 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069199-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18094357
title: UAV-derived multitemporal orthomosaics and DTMs of the Basento River across varying flow regimes

description: This dataset provides multitemporal high-resolution, georeferenced UAV-derived orthomosaics and Digital Terrain Models (DTMs) of a ~3 km reach of the Basento River (southern Italy), located in the middle section of the basin. The surveyed reach is an area frequently affected by flooding, characterized by accelerated erosion processes and intense sediment transport, resulting in a high hydro-geomorphological hazard.

The dataset is based on six UAV surveys conducted between 2019 and 2024, designed to capture river morphology conditions under different flow regimes following the pluvial hydrological regime of the Basento River, which typically exhibits peak discharges in autumn–winter and lower flows during summer. UAV flights were carried out at 50-75 m above ground level (AGL), allowing the generation of very high spatial resolution products suitable for detailed hydro-geomorphological analyses.

Surveys were carried out during medium–high flow conditions (2019, 2021, 2022), low flow (2020), high flow (2023), and medium–low flow (2024).

The resulting orthomosaics and DTMs are georeferenced in the spatial reference system EPSG:32633 - WGS 84 / UTM zone 33N, projected and exhibit variable spatial resolutions: approximately 1 cm and 6 cm (2019, 2020, 2021), 3 cm and 9 cm (2022), 5 cm and 6 cm (2023), and 6 cm and 9 cm (2024), respectively.

The dataset is organised into six directories, each named according to the survey year (e.g., Basento2019, Basento2020). Each directory provides the corresponding .tif, .tfw, .prj files for orthomosaics and DTMs. 

 

CitationsDataset users are kindly invited to cite as follows:



La Salandra, M., & Colacicco, R. (2025). UAV-derived multitemporal orthomosaics and DTMs of the Basento River across varying flow regimes (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18094358
DOI: 10.5281/zenodo.18094358
title: UAV-derived multitemporal orthomosaics and DTMs of the Basento River across varying flow regimes

description: This dataset provides multitemporal high-resolution, georeferenced UAV-derived orthomosaics and Digital Terrain Models (DTMs) of a ~3 km reach of the Basento River (southern Italy), located in the middle section of the basin. The surveyed reach is an area frequently affected by flooding, characterized by accelerated erosion processes and intense sediment transport, resulting in a high hydro-geomorphological hazard.

The dataset is based on six UAV surveys conducted between 2019 and 2024, designed to capture river morphology conditions under different flow regimes following the pluvial hydrological regime of the Basento River, which typically exhibits peak discharges in autumn–winter and lower flows during summer. UAV flights were carried out at 50-75 m above ground level (AGL), allowing the generation of very high spatial resolution products suitable for detailed hydro-geomorphological analyses.

Surveys were carried out during medium–high flow conditions (2019, 2021, 2022), low flow (2020), high flow (2023), and medium–low flow (2024).

The resulting orthomosaics and DTMs are georeferenced in the spatial reference system EPSG:32633 - WGS 84 / UTM zone 33N, projected and exhibit variable spatial resolutions: approximately 1 cm and 6 cm (2019, 2020, 2021), 3 cm and 9 cm (2022), 5 cm and 6 cm (2023), and 6 cm and 9 cm (2024), respectively.

The dataset is organised into six directories, each named according to the survey year (e.g., Basento2019, Basento2020). Each directory provides the corresponding .tif, .tfw, .prj files for orthomosaics and DTMs. 

 

CitationsDataset users are kindly invited to cite as follows:



La Salandra, M., & Colacicco, R. (2025). UAV-derived multitemporal orthomosaics and DTMs of the Basento River across varying flow regimes (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18094358
DOI: 10.5281/zenodo.17265889
title: Piezoelectrically actuated silicon-nitride-based high-speed spatial light modulator

description: Data for [Vanackere, T., Hermans, A., Christen, I. et al. Piezoelectrically actuated silicon-nitride-based high-speed spatial light modulator. Nat Commun 16, 11637 (2025). https://doi.org/10.1038/s41467-025-66718-4]
DOI: 10.5281/zenodo.17265890
title: Piezoelectrically actuated silicon-nitride-based high-speed spatial light modulator

description: Data for [Vanackere, T., Hermans, A., Christen, I. et al. Piezoelectrically actuated silicon-nitride-based high-speed spatial light modulator. Nat Commun 16, 11637 (2025). https://doi.org/10.1038/s41467-025-66718-4]
DOI: 10.5281/zenodo.18095213
title: Weather observations from Fyli weather station (Greece)

description: Hourly meteorological time series recorded at the Fyli weather station (Greece), including timestamp, precipitation, solar radiation, air temperature, wind direction and speed, and relative humidity for August–September 2025.
DOI: 10.5281/zenodo.18095214
title: Weather observations from Fyli weather station (Greece)

description: Hourly meteorological time series recorded at the Fyli weather station (Greece), including timestamp, precipitation, solar radiation, air temperature, wind direction and speed, and relative humidity for August–September 2025.