cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15007306
title: Sustainable Rural Housing in Cold Climates; A Model for   Rumicruz-Ecuador

description: Background: The loss of cultural identity in the rural architecture of Rumicruz, Chimborazo, is a consequence of the adoption of generic models and unsustainable modern materials, which has affected thermal comfort and the connection with local traditions. This research proposes sustainable housing that combines vernacular and modern techniques, respecting both the environment and the community's needs.

Method: Based on a mixed approach (qualitative and quantitative), the architectural, social, and environmental context was analyzed through a field diagnosis, literature review and critical observation. During this process, problems related to thermal comfort, housing deterioration, and the use of inadequate materials were identified. The proposal includes the use of mudbrick, stone, and concrete blocks, complemented with solar heating systems and energy efficiency, significantly improving thermal comfort compared to traditional housing.

Conclusions: It is concluded that the proposal integrates cultural identity and sustainability, adapting traditional techniques to current demands. The bioclimatic analysis and design support the thermal comfort values, highlighting the relevance of designs adapted to the local context.
DOI: 10.5281/zenodo.2580261
title: 2009\London\SWT Weather data

description: 2009\ London\ SWT Weather data


Data Type: Weather station
Site information:
Latitude: 51.487760                              
Longitude: -0.091069
Anemometer height: 60 m
Owner: Bill Legassick, Southwark Council. Contact: Tel: 020 7525 4253 | Fax: 020 7525 5705
Email: Bill.Legassick@southwark.gov.uk
Sensor information      
Sensor type                 Model                                               Date installed
Anemometer                CDL  Windset (EC8)                        1999
Rain gauge                  Campbell Scientific ARG-100           1999
Temperature probe      T107_C                                             1999
Humidity probe            HMP45A                                            1999
Files: Are Zipped
Filenames: Weather_Data_2008.CSV
Filetype: comma delimited
Header Row:Date and Time,Battery Voltage,CR10 Temperature,Wind Direction 10 Minutes,Wind Speed 10 Minutes,Wind Gust 10 Minutes,Hourly Average Direction,Hourly Average Speed,Hourly Maximum Gust,Hourly Gust Time,Hourly Gust Direction,Last Minute Average Temperature,Total Hourly Rain,Average RH over previous minute,Maximum Hourly Air Temperature,Minimum Hourly Air Temperature,Maximum Hourly Rainfall Rate,Time of Rainfall
Data: hourly averages
DOI: 10.5281/zenodo.2580262
title: 2009\London\SWT Weather data

description: 2009\ London\ SWT Weather data


Data Type: Weather station
Site information:
Latitude: 51.487760                              
Longitude: -0.091069
Anemometer height: 60 m
Owner: Bill Legassick, Southwark Council. Contact: Tel: 020 7525 4253 | Fax: 020 7525 5705
Email: Bill.Legassick@southwark.gov.uk
Sensor information      
Sensor type                 Model                                               Date installed
Anemometer                CDL  Windset (EC8)                        1999
Rain gauge                  Campbell Scientific ARG-100           1999
Temperature probe      T107_C                                             1999
Humidity probe            HMP45A                                            1999
Files: Are Zipped
Filenames: Weather_Data_2008.CSV
Filetype: comma delimited
Header Row:Date and Time,Battery Voltage,CR10 Temperature,Wind Direction 10 Minutes,Wind Speed 10 Minutes,Wind Gust 10 Minutes,Hourly Average Direction,Hourly Average Speed,Hourly Maximum Gust,Hourly Gust Time,Hourly Gust Direction,Last Minute Average Temperature,Total Hourly Rain,Average RH over previous minute,Maximum Hourly Air Temperature,Minimum Hourly Air Temperature,Maximum Hourly Rainfall Rate,Time of Rainfall
Data: hourly averages
DOI: 10.57745/nlofin
title: NutriKG-Ontology.ttl

description: :unav
DOI: 10.15454/gaxtx6/uwwizy
title: DOI-Scorff-1.tab

description: :unav
DOI: 10.57745/qh2g8z
title: DOI-Scorff.tab

description: :unav
DOI: 10.15454/gaxtx6/fezqrc
title: ORE-ScorffData.tab

description: :unav
DOI: 10.15454/gaxtx6/mbid1y
title: DOI-Scorff-1.txt

description: :unav
DOI: 10.15454/gaxtx6/uii7mr
title: DOI-Scorff-Parametres-SANDRE-1.tab

description: Parameters description (Excel file)
DOI: 10.57745/xy5ycj
title: DOI-Scorff 2.csv

description: :unav
DOI: 10.15454/gaxtx6/0f3whl
title: DOI-Scorff.txt

description: Data (text file)
DOI: 10.15454/gaxtx6/70c2yy
title: DOI-Scorff.tab

description: Data (Excel file)
DOI: 10.15454/gaxtx6/bjhxu4
title: DOI-Scorff-1.csv

description: :unav
DOI: 10.15454/gaxtx6/zmhe6s
title: DOI-Scorff-SecteurDegrade.tab

description: Sectors description (Excel file)
DOI: 10.57745/ch88ve
title: DOI-Scorff-1.csv

description: :unav
DOI: 10.57745/cv4smg
title: DOI-Scorff-SecteurDegrade.tab

description: :unav
DOI: 10.6084/m9.figshare.28575092
title: bdd_malaria_ecu

description: Malaria case database at the provincial level.
DOI: 10.6084/m9.figshare.28575092.v1
title: bdd_malaria_ecu

description: Malaria case database at the provincial level.
DOI: 10.48597/27bu-qjm2
title: Measurement of Meteorology at Capo Granitola

description: Measurement of Meteorology at Capo Granitola
DOI: 10.15468/dl.5ns8ew
title: Occurrence Download

description: A dataset containing 208 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is French Guiana",
 "TaxonKey is Handroanthus Mattos"
 ]
}

 The dataset includes 208 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003026-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10891602
title: Food Recall Incidents

description: The Food Recall Incidents dataset consists of 7,546 short texts (from 5 to 360 characters each), which are the titles of food recall announcements (therefore referred to as title), crawled from 24 public food safety authority websites by Agroknow. The texts are written in 6 languages, with English (6,644) and German (888) being the most common, followed by French (8), Greek (4), Italian (1) and Danish (1). Most of the texts have been authored after 2010 and they describe recalls of specific food products due to specific hazards. Experts manually classified each text to four groups of classes describing hazards and products on two levels of granularity:







hazard: fine-grained description of the hazards mentioned in the texts comprising 261 classes;

hazard-category: categorized version of the hazard classification task comprising 10 classes;

product: fine-grained description of the products mentioned in the texts comprising 1,256 classes;

product-category: categorized version of the product classification task comprising 22 classes.


The columns hazard-title and product-title comprise character spans, generated based on feature importance of a Logistic Regression (LR) classifier. These signify parts of the title that are important for hazard and product classification. Due to their very low support for many classes, the fine-grained tasks of hazard and product classification may require further pre-processing (e.g. label clustering or filtering), dependent on the application. The dataset comprises also metadata, such as the release date of the text (year, month, day), the language of the text (language), and the country of issue (country).

DISCLAIMER: A random sample of 1,562 instances is kept hidden for the purposes of an academic challenge and will be released soon.
DOI: 10.15468/dl.n7mxnz
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ornithogalum reverchonii Lange ex Willk.)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 7 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003027-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10820657
title: Food Recall Incidents

description: The Food Recall Incidents dataset consists of 7,546 short texts (from 5 to 360 characters each), which are the titles of food recall announcements (therefore referred to as title), and their full-length texts (from 56 to 48,318 characters). The data are crawled from 24 public food safety authority websites by Agroknow. All texts are written in 6 languages, with English (6,644) and German (888) being the most common, followed by French (8), Greek (4), Italian (1) and Danish (1). Most of the texts have been authored after 2010 and they describe recalls of specific food products due to specific hazards. Experts manually classified each text to four groups of classes describing hazards and products on two levels of granularity:







hazard: fine-grained description of the hazards mentioned in the texts comprising 261 classes;

hazard-category: categorized version of the hazard classification task comprising 10 classes;

product: fine-grained description of the products mentioned in the texts comprising 1,256 classes;

product-category: categorized version of the product classification task comprising 22 classes.


The columns hazard-title and product-title comprise character spans, generated based on feature importance of a Logistic Regression (LR) classifier. These signify parts of the title that are important for hazard and product classification. Due to their very low support for many classes, the fine-grained tasks of hazard and product classification may require further pre-processing (e.g. label clustering or filtering), dependent on the application. The dataset comprises also metadata, such as the release date of the text (year, month, day), the language of the text (language), and the country of issue (country).



DISCLAIMER: A random sample of 1,562 instances was used for validation and testing for the purposes of the SemEval 2025 Task 9: The Food Hazard Detection Challenge, labelled respectively in the semeval-split column.
DOI: 10.5281/zenodo.15007331
title: Food Recall Incidents

description: The Food Recall Incidents dataset consists of 7,546 short texts (from 5 to 360 characters each), which are the titles of food recall announcements (therefore referred to as title), and their full-length texts (from 56 to 48,318 characters). The data are crawled from 24 public food safety authority websites by Agroknow. All texts are written in 6 languages, with English (6,644) and German (888) being the most common, followed by French (8), Greek (4), Italian (1) and Danish (1). Most of the texts have been authored after 2010 and they describe recalls of specific food products due to specific hazards. Experts manually classified each text to four groups of classes describing hazards and products on two levels of granularity:







hazard: fine-grained description of the hazards mentioned in the texts comprising 261 classes;

hazard-category: categorized version of the hazard classification task comprising 10 classes;

product: fine-grained description of the products mentioned in the texts comprising 1,256 classes;

product-category: categorized version of the product classification task comprising 22 classes.


The columns hazard-title and product-title comprise character spans, generated based on feature importance of a Logistic Regression (LR) classifier. These signify parts of the title that are important for hazard and product classification. Due to their very low support for many classes, the fine-grained tasks of hazard and product classification may require further pre-processing (e.g. label clustering or filtering), dependent on the application. The dataset comprises also metadata, such as the release date of the text (year, month, day), the language of the text (language), and the country of issue (country).



DISCLAIMER: A random sample of 1,562 instances was used for validation and testing for the purposes of the SemEval 2025 Task 9: The Food Hazard Detection Challenge, labelled respectively in the semeval-split column.
DOI: 10.6073/pasta/cc3b25b63b97fc06eddefdce8e4cd51c
title: Average glacier stake height and snow depth measurements, McMurdo Dry Valleys, Antarctica (1993-2023, ongoing)

description: As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor glacial mass balance and meltwater flow. This data package includes stake height and snow depth measurements to the surface of six glaciers (Canada, Commonwealth, Hughes, Suess, Howard, and Taylor) in Taylor Valley and one glacier (Adams) in Miers Valley, all of which are located in the McMurdo Dry Valleys of Antarctica. Most measurements began during the 93-94 field season. Adams measurements were established during the 14-15 field season. Measurements are ongoing except at Hughes and Suess Glaciers where monitoring ceased following the 08-09 field season. Monitoring the changes in these measurements over time provides a record of mass balance, and aids in determining the role of glaciers in the polar hydrologic cycle.
DOI: 10.15468/dl.dbe3ff
title: Occurrence Download

description: A dataset containing 81388 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is one of (United States of America, Mexico)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Achillea millefolium L."
 ]
}

 The dataset includes 81388 records from 295 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003008-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.5706100
title: A consensus molecular environment of schizophrenia risk genes in shifting co-expression networks across brain development, ageing and brain regions

description: Extended data files:<br> <strong>1)</strong> wide_form_WGCNA(v3.6.2)_final.xlsx: An excel file with detail of geneinfo and WGCNA outputs: module-assignment, kWithin, kTotal etc for all Age-parsed, non-parsed and published networks. <strong>2)</strong> wide_form_test_slidingwindow_NC_SchizoNew(v1.3)_final.xlsx: An excel file with detail of WGCNA outputs: module-assignment, kWithin, kTotal etc for all networks in sliding window network. <strong>3)</strong> CN all.genes.html, <strong>4)</strong> DLPFC all.genes.html, <strong>5)</strong> HP all.genes.html: Interactive Sankey plots for all genes <strong>6)</strong> CN hit.genes_kb_200__new.html, <strong>7)</strong> DLPFC hit.genes_kb_200__new.html, <strong>8)</strong> HP hit.genes_kb_200__new.html: Interactive Sankey plots with only <em>SCZ risk genes</em> at 200kbp
description: Change log: 1) Added additional sankey plots
DOI: 10.5281/zenodo.11220432
title: Investigating effect chains from cognitive and noise-induced short-term stress build-up to restoration in an urban or nature setting using 360° VR

description: Dataset for demographic, psychological and physiological data obtained for RESTORE (Experiment 1 WP1). Study results are published in the article titled "Investigating effect chains from cognitive and noise-induced short-term stress build-up to restoration in an urban or nature setting using 360° VR" in the Journal of Environmental Psychology. Explanations on all variables (column names) in the datasets are given either in the second spreadsheet in each Excel file or in the csv files appended with _legend.csv (see latest version of the dataset). File 'Psychophysiological_participant_data_aggregated' is aggregated per participant (single or mean values), and the file 'Restoration_EDA_baseline-corrected_aggregated' contains EDA data aggregated per time point per restoration setting (Nature vs Urban) and prior cognitive demand condition. Methodological details on how the data was obtained and processed are given in the Open Access article.
DOI: 10.5281/zenodo.11220433
title: Investigating effect chains from cognitive and noise-induced short-term stress build-up to restoration in an urban or nature setting using 360° VR

description: Dataset for demographic, psychological and physiological data obtained for RESTORE (Experiment 1 WP1). Study results are published in the article titled "Investigating effect chains from cognitive and noise-induced short-term stress build-up to restoration in an urban or nature setting using 360° VR" in the Journal of Environmental Psychology. Explanations on all variables (column names) in the datasets are given either in the second spreadsheet in each Excel file or in the csv files appended with _legend.csv (see latest version of the dataset). File 'Psychophysiological_participant_data_aggregated' is aggregated per participant (single or mean values), and the file 'Restoration_EDA_baseline-corrected_aggregated' contains EDA data aggregated per time point per restoration setting (Nature vs Urban) and prior cognitive demand condition. Methodological details on how the data was obtained and processed are given in the Open Access article.
DOI: 10.5281/zenodo.14714469
title: ICST 2025 UAV Testing Competition: Evaluation Artifacts

description: The UAV Testing Competition organized by the International Conference on Software Testing, Verification and Validation (ICST) 2025 is an initiative designed to inspire and encourage the Software Testing Community to direct their attention toward UAVs as a rapidly emerging and crucial domain.Here we store the evaluation artifacts for the second edition held in 2025. We report the 3 case studies used in the evaluation, test suites generated by each tool for the case studies, and the scoring and ranking details.
DOI: 10.5281/zenodo.14714470
title: ICST 2025 UAV Testing Competition: Evaluation Artifacts

description: The UAV Testing Competition organized by the International Conference on Software Testing, Verification and Validation (ICST) 2025 is an initiative designed to inspire and encourage the Software Testing Community to direct their attention toward UAVs as a rapidly emerging and crucial domain.Here we store the evaluation artifacts for the second edition held in 2025. We report the 3 case studies used in the evaluation, test suites generated by each tool for the case studies, and the scoring and ranking details.
DOI: 10.5281/zenodo.15007504
title: ICST 2025 UAV Testing Competition: Evaluation Artifacts

description: The UAV Testing Competition organized by the International Conference on Software Testing, Verification and Validation (ICST) 2025 is an initiative designed to inspire and encourage the Software Testing Community to direct their attention toward UAVs as a rapidly emerging and crucial domain.Here we store the evaluation artifacts for the second edition held in 2025. We report the 3 case studies used in the evaluation, test suites generated by each tool for the case studies, and the scoring and ranking details.
DOI: 10.5281/zenodo.15007506
title: Investigating effect chains from cognitive and noise-induced short-term stress build-up to restoration in an urban or nature setting using 360° VR

description: Dataset for demographic, psychological and physiological data obtained for RESTORE (Experiment 1 WP1). Study results are published in the article titled "Investigating effect chains from cognitive and noise-induced short-term stress build-up to restoration in an urban or nature setting using 360° VR" in the Journal of Environmental Psychology. Explanations on all variables (column names) in the datasets are given either in the second spreadsheet in each Excel file or in the csv files appended with _legend.csv (see latest version of the dataset). File 'Psychophysiological_participant_data_aggregated' is aggregated per participant (single or mean values), and the file 'Restoration_EDA_baseline-corrected_aggregated' contains EDA data aggregated per time point per restoration setting (Nature vs Urban) and prior cognitive demand condition. Methodological details on how the data was obtained and processed are given in the Open Access article.
DOI: 10.5281/zenodo.13821320
title: SELPHI2.0: Data-driven extraction of human kinase-substrate relationships from omics datasets

description: In this study, we have created a machine learning-based model to derive a probabilistic kinase-substrate network from omics datasets.  Our methodology displays improved performance compared to other state-of-the-art kinase-substrate prediction methods, and provides predictions for more kinases. Importantly, it better captures new experimentally-identified kinase-substrate relationships. It can therefore allow the improved prioritisation of kinase-substrate pairs for illuminating the dark human cell signalling space. Our model is integrated into a web server, SELPHI2.0, to allow unbiased analysis of phosphoproteomics data, facilitating the design of downstream experiments to uncover mechanisms of signal transduction across conditions and cellular contexts.

The SELPHI2.0 web server is freely available under: https://selphi2.com  and all code for reproducing this project can be found at https://gitlab.ebi.ac.uk/petsalakilab/selphi_2.0 and https://github.com/alussana/selphi2.0-pssms. A Docker image of the web server can be found at: https://gitlab.ebi.ac.uk/petsalakilab/selphi_2.
DOI: 10.5281/zenodo.13821321
title: SELPHI2.0: Data-driven extraction of human kinase-substrate relationships from omics datasets

description: In this study, we have created a machine learning-based model to derive a probabilistic kinase-substrate network from omics datasets.  Our methodology displays improved performance compared to other state-of-the-art kinase-substrate prediction methods, and provides predictions for more kinases. Importantly, it better captures new experimentally-identified kinase-substrate relationships. It can therefore allow the improved prioritisation of kinase-substrate pairs for illuminating the dark human cell signalling space. Our model is integrated into a web server, SELPHI2.0, to allow unbiased analysis of phosphoproteomics data, facilitating the design of downstream experiments to uncover mechanisms of signal transduction across conditions and cellular contexts.

The SELPHI2.0 web server is freely available under: https://selphi2.com  and all code for reproducing this project can be found at https://gitlab.ebi.ac.uk/petsalakilab/selphi_2.0 and https://github.com/alussana/selphi2.0-pssms. A Docker image of the web server can be found at: https://gitlab.ebi.ac.uk/petsalakilab/selphi_2.
DOI: 10.5281/zenodo.5676481
title: Schizophrenia risk genes converge into shifting co-expression networks across brain development, ageing and brain regions

description: Extended data files:<br> 1) wide_form_WGCNA(v3.6.2)_final.xlsx: An excel file with detail of geneinfo and WGCNA outputs: module-assignment, kWithin, kTotal etc for all Age-parsed, non-parsed and published networks. 2) wide_form_test_slidingwindow_NC_SchizoNew(v1.3)_final.xlsx: An excel file with detail of WGCNA outputs: module-assignment, kWithin, kTotal etc for all networks in sliding window network.