cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2k56xw
title: CCDC 2358508: Experimental Crystal Structure Determination

description: Related Article: Sumera Zaib, Imtiaz Khan, Aliya Ibrar, Christopher John McAdam, Safaa N. Abdou, Mohamed M. Ibrahim, Salah M. El-Bahy, Antonio Frontera|2024|J.Mol.Struct.|1318|139232|doi:10.1016/j.molstruc.2024.139232
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2k56yx
title: CCDC 2358509: Experimental Crystal Structure Determination

description: Related Article: Sumera Zaib, Imtiaz Khan, Aliya Ibrar, Christopher John McAdam, Safaa N. Abdou, Mohamed M. Ibrahim, Salah M. El-Bahy, Antonio Frontera|2024|J.Mol.Struct.|1318|139232|doi:10.1016/j.molstruc.2024.139232
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jpf2r
title: CCDC 2344284: Experimental Crystal Structure Determination

description: Related Article: Krishna Chattopadhyay, Biswarup Dutta, Shyamali Dutta, Anupama Manna, Gavin A. Craig, Manas Mandal, Mark Murrie, Debashis Ray|2024|Inorg.Chim.Acta|572|122270|doi:10.1016/j.ica.2024.122270
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.64bn2d
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.643489 -32.971107, 148.643489 -32.975599, 148.645735 -32.975599, 148.645735 -32.971107, 148.643489 -32.971107))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056987-240626123714530/datasets/export for details.
DOI: 10.15468/dl.ekt9xg
title: Occurrence Download

description: A dataset containing 597 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Euterpe precatoria var. longevaginata (Mart.) A.J.Hend."
 ]
}

 The dataset includes 597 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056988-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25934/pr00010410
title: Vivli 2024 data challenge: Clinical decision support: Merging AI, surveillance and literature for optimal antibiotic selection.

description: The escalating challenge of antimicrobial resistance (AMR) necessitates innovative approaches to optimize antibiotic selection. We propose a research initiative focused on integrating artificial intelligence (AI), surveillance data, and comprehensive literature to develop a clinical decision support system (CDSS) tailored for use across all levels of healthcare. Our primary objective is to address the complexities of antibiotic treatment for WHO-designated critical and priority organisms by leveraging the vast, diverse data landscape.
This project is driven by the need to navigate multiple guidelines, literature and surveillance data from databases such as Paratek-Keystone, Pfizer-Atlas, and Venatorx-Gears to guide the treatment of these organisms. However, the sheer volume of information presents significant challenges for clinicians and policymakers in synthesizing and summarizing evidence-based decisions efficiently.
Our proposed CDSS aims to consolidate these data sources into a cohesive platform that leverages AI to analyze, summarize, and present actionable insights. By integrating real-time surveillance data with up-to-date literature, the system will provide users with a comprehensive overview of current evidence, facilitating informed decision-making at both the bedside and policy levels.
The envisioned system will support clinicians in selecting optimal antibiotic regimens by delivering tailored recommendations based on the latest research and surveillance trends. Furthermore, it will empower healthcare administrators and policymakers by offering strategic insights into AMR patterns and treatment efficacy, thus enhancing the overall healthcare response to this global threat.
By merging AI with existing surveillance and literature resources, our initiative seeks to transform the landscape of clinical decision-making, fostering a more responsive and effective approach to combating antimicrobial resistance.
DOI: 10.15468/dl.5qvpan
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.085912 -32.971107, 149.085912 -32.973353, 149.090403 -32.973353, 149.090403 -32.971107, 149.085912 -32.971107))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056989-240626123714530/datasets/export for details.
DOI: 10.15468/dl.d7ga9z
title: Occurrence Download

description: A dataset containing 416 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Euterpe precatoria var. precatoria"
 ]
}

 The dataset includes 416 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056990-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.67fw73
title: Occurrence Download

description: A dataset containing 308 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Bathynomus giganteus de la Colección de Crustáceos del Museo de Historia Natural Marina de Colombia - Makuriwa",
 "Geometry POLYGON((-92.64723 4.24421,-56.35277 4.24421,-56.35277 18.75579,-92.64723 18.75579,-92.64723 4.24421))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 308 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056991-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pvxahq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.779864 -32.971107, 149.779864 -32.977844, 149.786601 -32.977844, 149.786601 -32.975599, 149.784355 -32.975599, 149.784355 -32.971107, 149.779864 -32.971107))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056992-240626123714530/datasets/export for details.
DOI: 10.15468/dl.eju7m4
title: Occurrence Download

description: A dataset containing 387 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Iberolacerta aranica (Arribas, 1993)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 387 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056993-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/2jyx-9y22
title: Parkes observations for project P1328 semester 2024APRS_15

description: Fast radio bursts are peculiar micro-millisecond duration transients, which have been seen to be extragalactic in origin. Since their discovery, a dichotomy has emerged in their population. Some FRBs have been seen to be repeating, while others have not been seen to be repeating. The repeating FRBs, such as FRB 20180301A, provide an unparalleled window into their circumburst environment due to their repeating nature, which can be used to constrain possible progenitor models and test underlying emission mechanisms. Additionally, FRB 20180301A has been seen to have interesting polarisation properties, such as a switch in the sign of RM, indicating a reversal in the magnetic field and a marked reduction in the linear polarisation fraction towards lower frequencies (depolarisation). The previous Parkes/Murriyang source follow-up has also revealed a temporal evolution in the dispersion measure (DM) of the source and tentative evidence for correlation in the DM and rotation measure (RM). The ultra-wideband low (UWL) receiver on Parkes/Murriyang is ideally suited to explore the wideband spectro-temporal and polarimetric behaviour of the source. We propose regular monitoring of FRB 20180301A using UWL to model the magnetic field evolution, study its circumburst media using depolarisation behaviour, and constrain any correlation of DM and RM.
DOI: 10.25919/kp5c-g195
title: Parkes observations for project P1328 semester 2024APRS_14

description: Fast radio bursts are peculiar micro-millisecond duration transients, which have been seen to be extragalactic in origin. Since their discovery, a dichotomy has emerged in their population. Some FRBs have been seen to be repeating, while others have not been seen to be repeating. The repeating FRBs, such as FRB 20180301A, provide an unparalleled window into their circumburst environment due to their repeating nature, which can be used to constrain possible progenitor models and test underlying emission mechanisms. Additionally, FRB 20180301A has been seen to have interesting polarisation properties, such as a switch in the sign of RM, indicating a reversal in the magnetic field and a marked reduction in the linear polarisation fraction towards lower frequencies (depolarisation). The previous Parkes/Murriyang source follow-up has also revealed a temporal evolution in the dispersion measure (DM) of the source and tentative evidence for correlation in the DM and rotation measure (RM). The ultra-wideband low (UWL) receiver on Parkes/Murriyang is ideally suited to explore the wideband spectro-temporal and polarimetric behaviour of the source. We propose regular monitoring of FRB 20180301A using UWL to model the magnetic field evolution, study its circumburst media using depolarisation behaviour, and constrain any correlation of DM and RM.
DOI: 10.25919/f2xm-dy50
title: Parkes observations for project P1032 semester 2024APRS_04

description: With this proposal, we aim to continue P1032, the rapid measurements of relativistic parameters of southern binary pulsar systems using data from the Parkes Ultra Wideband Low (UWL) receiver. As the MeerTime project at the MeerKAT radio telescope ends in early 2024, observations with the UWL receiver will now form the backbone for extending the timing baselines of many pulsars that have been part of this project. Under these circumstances we have revamped the source selection in this proposal such that the UWL receiver is the most (versatile and) suited instrument to achieve the proposed scientific goals for the chosen pulsars. We will use the UWL data to obtain significant orbital coverage and timing baselines on these pulsars and obtain important constraints on orbital and temporal DM variations that will help in identifying the nature of the companion stars. Increasing the number of measured Neutron Star (NS) masses, as well as improving on current constraints has profound implications for NS internal structure and for stellar and binary evolution physics. We request pre-graded status for this project for the next semester.
DOI: 10.15468/dl.h75eez
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((149.822534 -32.971107, 149.82478 -32.971107, 149.82478 -32.966615, 149.827025 -32.966615, 149.827025 -32.959878, 149.82478 -32.959878, 149.82478 -32.96437, 149.822534 -32.96437, 149.822534 -32.971107)), ((149.822534 -32.971107, 149.818042 -32.971107, 149.818042 -32.973353, 149.822534 -32.973353, 149.822534 -32.971107)))"
 ]
}

 The dataset includes 43 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056994-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8rpgth
title: Occurrence Download

description: A dataset containing 235 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Iberolacerta aurelioi (Arribas, 1994)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 235 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056995-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yjapvz
title: Occurrence Download

description: A dataset containing 2024 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Iberolacerta bonnali (Lantz, 1927)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 2024 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056996-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12720767
title: Dependabot and Security Pull Requests

description: This deposit contains four (4) main datasets that were used in the study "Dependabot and Security Pull Requests: Large Empirical Study" (Link). Each dataset is described as follows :



Dataset (1) - Dependency Update : This dataset concerns issues related to pull requests (PRs) that were created by both users and bots to manage dependency updates in GitHub projects. The search was based on the keywords "Dependency, Update" in the title, body or comment of a PR created in the time period between 26/05/2017 and 15/06/2021 for the 1st partition, and between 01/01/2023 and 30/09/2023 for the 2nd partition. We obtained a total of 6,573,489 PR-related issues belonging to a total of 927,007 repositories for partition (1); and for partition (2), we obtained a total of 3,342,829 PR-related issues belonging to a total of 816,028 repositories.

Dataset (2) - Dependabot Security PRs : The second dataset is related to PRs created by Dependabot to handle security vulnerabilities in project dependencies. In our search, we look for PR-related issues created by "Dependabot-preview" or "Dependabot" and with the label "security", also created during the time period between 26/05/2017 and 30/09/2023. With these parameters, our results consist of 422,388 issues from 47,987 repositories.

Dataset (3) - Manual Security PRs : For this dataset, we were interested in PRs created only by users to handle security vulnerabilities. The search consists of finding the keywords "Dependency, Vulnerable" in the title, body or comment of a PR created in the time period between 26/05/2017 and 30/09/2023. We only consider pull requests created by authors with the type "user". The final results include a total of 186,186 issues for 60,758 repositories.

Dataset (4) - Bots' Security PRs : This dataset is related to PRs created by several bots to handle security vulnerabilities in project dependencies. In the search query, we look for PR-related issues where the keywords "Dependency", and "Security", and "Vulnerability" are mentioned in the title, body, or comment of the PR. These PRs are created by one of the following bots: "Snyk", "Renovate", "Greenkeeper", or "Depfu", also created during the time period between 26/05/2017 and 30/09/2023. The obtained results for the 4 bots consists of a collection of 628,495 PR-related issues in a total of 105,342 repositories.


We also included :



Derived Sample : This sample contains the data that was selected and extracted to conduct our manual qualitative analysis, and the manual feature extraction.
DOI: 10.5281/zenodo.7793971
title: Dependabot and Security Pull Requests

description: This deposit contains four (4) main datasets that were used in the study "Dependabot and Security Pull Requests: Large Empirical Study" (Link). Each dataset is described as follows :



Dataset (1) - Dependency Update : This dataset concerns issues related to pull requests (PRs) that were created by both users and bots to manage dependency updates in GitHub projects. The search was based on the keywords "Dependency, Update" in the title, body or comment of a PR created in the time period between 26/05/2017 and 15/06/2021 for the 1st partition, and between 01/01/2023 and 30/09/2023 for the 2nd partition. We obtained a total of 6,573,489 PR-related issues belonging to a total of 927,007 repositories for partition (1); and for partition (2), we obtained a total of 3,342,829 PR-related issues belonging to a total of 816,028 repositories.

Dataset (2) - Dependabot Security PRs : The second dataset is related to PRs created by Dependabot to handle security vulnerabilities in project dependencies. In our search, we look for PR-related issues created by "Dependabot-preview" or "Dependabot" and with the label "security", also created during the time period between 26/05/2017 and 30/09/2023. With these parameters, our results consist of 422,388 issues from 47,987 repositories.

Dataset (3) - Manual Security PRs : For this dataset, we were interested in PRs created only by users to handle security vulnerabilities. The search consists of finding the keywords "Dependency, Vulnerable" in the title, body or comment of a PR created in the time period between 26/05/2017 and 30/09/2023. We only consider pull requests created by authors with the type "user". The final results include a total of 186,186 issues for 60,758 repositories.

Dataset (4) - Bots' Security PRs : This dataset is related to PRs created by several bots to handle security vulnerabilities in project dependencies. In the search query, we look for PR-related issues where the keywords "Dependency", and "Security", and "Vulnerability" are mentioned in the title, body, or comment of the PR. These PRs are created by one of the following bots: "Snyk", "Renovate", "Greenkeeper", or "Depfu", also created during the time period between 26/05/2017 and 30/09/2023. The obtained results for the 4 bots consists of a collection of 628,495 PR-related issues in a total of 105,342 repositories.


We also included :



Derived Sample : This sample contains the data that was selected and extracted to conduct our manual qualitative analysis, and the manual feature extraction.
DOI: 10.5281/zenodo.7793972
title: Dependabot and Security Pull Requests

description: This deposit contains three (3) datasets that were used in the study "<em>Dependabot and Security Pull Requests: Large Empirical Study</em>" (Under review). Each dataset is described as follows : <strong>Dataset (1) - Dependency Update</strong> : This dataset concerns issues related to pull requests that were created by both users and bots to manage dependency updates in GitHub projects. The search query that we used consists of looking for the keywords "<em>Dependency, Update</em>" in the title, body or comment of a PR created in the time period between 26/05/2017 and 15/06/2021. Note that the first date corresponds to the launch date of Dependabot that we chose as reference for all our datasets to conserve homogeneity and uniformity of PRs creation dates, and the second date corresponds to the day that we executed our collection pipeline process. We obtained a total of 6,573,489 PR-related issues belonging to a total of 927,007 repositories. <strong>Dataset (2) - Dependabot Security PRs</strong> : The second dataset is related to PRs created by Dependabot to handle security vulnerabilities in project dependencies. In the search query, we look for PR-related issues created by "<em>Dependabot-preview</em>" and with the label "<em>security</em>", also created during the time period between 26/05/2017 and 15/06/2021. With these parameters, the GitHub API returned 384,764 issues from 36,911 repositories. <strong>Dataset (3) - Manual Security PRs</strong> : For this dataset, we were interested in PRs created only by users to handle security vulnerabilities. The used query consists of searching for the keywords "<em>Dependency, Vulnerable</em>" in the title, body or comment of a PR created in the time period between 26/05/2017 and 15/06/2021. After the pipeline execution, we excluded the issues that were created by bots by filtering the PR authors with the GitHub user type "<em>bot</em>" and only keeping those with the type "<em>user</em>". The final results include a total of 100,102 issues for 37,845 repositories. It is worth noting that we have explored several search keywords and considered using root-based search to make sure that we covered the maximum amount of cases without missing any PRs.
DOI: 10.5281/zenodo.7801356
title: Dependabot and Security Pull Requests

description: This deposit contains four (4) main datasets that were used in the study "Dependabot and Security Pull Requests: Large Empirical Study" (Link) . Each dataset is described as follows :



Dataset (1) - Dependency Update : This dataset concerns issues related to pull requests (PRs) that were created by both users and bots to manage dependency updates in GitHub projects. The search was based on the keywords "Dependency, Update" in the title, body or comment of a PR created in the time period between 26/05/2017 and 15/06/2021 for the 1st partition, and between 01/01/2023 and 30/09/2023 for the 2nd partition. We obtained a total of 6,573,489 PR-related issues belonging to a total of 927,007 repositories for partition (1); and for partition (2), we obtained a total of 3,342,829 PR-related issues belonging to a total of 816,028 repositories.

Dataset (2) - Dependabot Security PRs : The second dataset is related to PRs created by Dependabot to handle security vulnerabilities in project dependencies. In our search, we look for PR-related issues created by "Dependabot-preview" or "Dependabot" and with the label "security", also created during the time period between 26/05/2017 and 30/09/2023. With these parameters, our results consist of 422,388 issues from 47,987 repositories.

Dataset (3) - Manual Security PRs : For this dataset, we were interested in PRs created only by users to handle security vulnerabilities. The search consists of finding the keywords "Dependency, Vulnerable" in the title, body or comment of a PR created in the time period between 26/05/2017 and 30/09/2023. We only consider pull requests created by authors with the type "user". The final results include a total of 186,186 issues for 60,758 repositories.

Dataset (4) - Bots' Security PRs : This dataset is related to PRs created by several bots to handle security vulnerabilities in project dependencies. In the search query, we look for PR-related issues where the keywords "Dependency", and "Security", and "Vulnerability" are mentioned in the title, body, or comment of the PR. These PRs are created by one of the following bots: "Snyk", "Renovate", "Greenkeeper", or "Depfu", also created during the time period between 26/05/2017 and 30/09/2023. The obtained results for the 4 bots consists of a collection of 628,495 PR-related issues in a total of 105,342 repositories.


We also included :



Derived Sample : This sample contains the data that was selected and extracted to conduct our manual qualitative analysis, and the manual feature extraction.