cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23559849.v1
title: <strong>Investigating the Link between Frontal Sinus Morphology and Craniofacial Characteristics with Sex: A 3D CBCT study on </strong> <strong>the South Indian Population.</strong>

description: The data contains frontal sinus and craniofacial parameters in patients using cone beam computed tomography.
DOI: 10.34740/kaggle/dsv/5938436
title: Random Telecom Payments
DOI: 10.34740/kaggle/ds/3388697
title: Random Telecom Payments
DOI: 10.21227/tgfc-n793
title: Resource-Constrained Multi-Project Reactive Scheduling Problem with New Project Arrival

description: Reactive project scheduling is an important branch of project scheduling under uncertainty. This paper proposes a resource-constrained multi-project reactive scheduling problem (RCMPRSP) with new project arrival to minimize the adjustment cost of the baseline schedule while achieving the deterministic multi-project scheduling goal. Although the RCMPRSP aims to minimize the adjustment cost, it adds a constraint to ensure that the reactive schedule is one of the schedules with shortest possible make-span after new project arrival. Therefore, the make-span and cost can both be optimized during when the multi-project schedule must be reactive scheduled due to new project arrival. Therefore, this scheduling problem has two stages. In the fifirst stage, the shortest make-span is obtained by fully rescheduling the multi-project after new project arrival. If the new project has a higher priority, the new project will be prioritized for implementation. Otherwise, the new project will be delayed. In the second stage, the multi-project is rescheduled to minimize the adjustment cost of the baseline schedule after new project arrival. The exact solution is implemented on IBM ILOG CPLEX Optimization Studio. It is found in the experiments that the CPLEX execution effificiency is acceptable for activity numbers below 80. The results of computational experiments demonstrate that the proposed method has distinct advantages over existing methods.
DOI: 10.5281/zenodo.8060264
title: Curated GWAS summary statistics on African ancestry on 19 blood count traits and glycemic traits (hg38)

description: Genome wide curated summary statistics on 19 blood count traits and glycemic traits File format is the inittable format intended to be used with the Joint Analysis of Summary Statistics (JASS), which allows to perform multi-trait GWAS: https://gitlab.pasteur.fr/statistical-genetics/jass GWAS of hematological traits originate from Chen et al paper and were downloaded from the GWAS Catalog (https://www.ebi.ac.uk/gwas/publications/32888493#study_panel). GWAS of glycemic traits come from the (18) study downloadable from GWAS Catalog (https://www.ebi.ac.uk/gwas/publications/34059833).
DOI: 10.5281/zenodo.8060263
title: Curated GWAS summary statistics on African ancestry on 19 blood count traits and glycemic traits (hg38)

description: Genome wide curated summary statistics on 19 blood count traits and glycemic traits File format is the inittable format intended to be used with the Joint Analysis of Summary Statistics (JASS), which allows to perform multi-trait GWAS: https://gitlab.pasteur.fr/statistical-genetics/jass GWAS of hematological traits originate from Chen et al paper and were downloaded from the GWAS Catalog (https://www.ebi.ac.uk/gwas/publications/32888493#study_panel). GWAS of glycemic traits come from the (18) study downloadable from GWAS Catalog (https://www.ebi.ac.uk/gwas/publications/34059833).
DOI: 10.5281/zenodo.8069013
title: Testing Access Options

description: A random file for testing access options
DOI: 10.5281/zenodo.8069012
title: Testing Access Options

description: A random file for testing access options
DOI: 10.5281/zenodo.8069063
title: VULNER Interview

description: VULNER Interview
DOI: 10.5281/zenodo.8069062
title: VULNER Interview

description: VULNER Interview
DOI: 10.5281/zenodo.8056341
title: Magnetic-field-free

description: A
DOI: 10.5281/zenodo.8066045
title: Magnetic-field-free

description: A
DOI: 10.21942/uva.23552004
title: Dataset for: "Why are open ascending auctions popular? The role of information aggregation and behavioral biases"

description: The dataset
DOI: 10.21942/uva.23552004.v2
title: Dataset for: "Why are open ascending auctions popular? The role of information aggregation and behavioral biases"

description: The dataset
DOI: 10.21942/uva.23552004.v1
title: Data

description: The dataset
DOI: 10.21942/uva.23552013
title: Dataset for: "Morals in multi-unit markets"

description: Data <br>
DOI: 10.21942/uva.23552013.v2
title: Dataset for: "Morals in multi-unit markets"

description: Data <br>
DOI: 10.21942/uva.23552013.v1
title: Data

description: Data <br>
DOI: 10.21942/uva.23552031
title: Dataset for: "Persuading an audience: Testing information design in the laboratory"

description: Data
DOI: 10.21942/uva.23552031.v2
title: Dataset for: "Persuading an audience: Testing information design in the laboratory"

description: Data
DOI: 10.21942/uva.23552031.v1
title: Data

description: Data
DOI: 10.5281/zenodo.8069023
title: Reflection effect across decision domains and probabilities

description: Data from the vignette study.
DOI: 10.5281/zenodo.8069022
title: Reflection effect across decision domains and probabilities

description: Data from the vignette study.
DOI: 10.5281/zenodo.8020625
title: SeaLiT Ontology - An extension of CIDOC-CRM for the modelling of Maritime History information

description: The <strong>SeaLiT Ontology</strong> is a formal ontology intended to facilitate the integration, mediation and interchange of heterogeneous information related to <strong>maritime history</strong>. It aims at providing the semantic definitions needed to transform disparate, localised information sources of maritime history into a coherent global resource. It also serves as a common language for domain experts and IT developers to formulate requirements and to agree on system functionalities with respect to the correct handling of historical information. The ontology uses and extends the <strong>CIDOC Conceptual Reference Model</strong> (ISO 21127:2014), in particular version 7.2.1, as a general ontology of human activity, things and events happening in space and time. The ontology has been developed following a bottom-up process from primary data collected in the context of the <strong>SeaLiT Project</strong> (<em>Seafaring Lives in Transition, Mediterranean Maritime Labour and Shipping, 1850s-1920s</em>). SeaLiT is an international research project, funded by the ERC Starting Grant 2016, which explores the transition from sail to steam navigation and its effects on seafaring populations in the Mediterranean and the Black Sea between the 1850s and the 1920s. More information about the construction of the <strong>SeaLiT Ontology</strong>, the considered data sources, as well as their transformation to a knowledge graph using the SeaLiT Ontology, can be found in the following papers: P. Fafalios, A. Kritsotaki, and M. Doerr, "<em>The SeaLiT Ontology – An Extension of CIDOC-CRM for the Modeling and Integration of Maritime History Information"</em>. ACM Journal on Computing and Cultural Heritage, 2023. https://doi.org/10.1145/3586080 [pdf, bib] P. Fafalios, K. Petrakis, G. Samaritakis, K. Doerr, A. Kritsotaki, Y. Tzitzikas, and M. Doerr, "FAST CAT: Collaborative Data Entry and Curation for Semantic Interoperability in Digital Humanities", ACM Journal on Computing and Cultural Heritage, 2021. https://doi.org/10.1145/3461460 [pdf, bib] The (resolvable) <strong>namespace </strong>of the ontology is: http://www.sealitproject.eu/ontology/ An <strong>OWL implementation</strong> of the ontology is available at: https://sealitproject.eu/ontology/SeaLiT_Ontology_v1.2.owl <strong>Knowledge graphs </strong>that make use of the SeaLiT Ontology are available at: https://zenodo.org/record/6460841. These RDF datasets integrate information of 16 different types of archival sources related to maritime history, including crew lists, payrolls, registers of different types, censuses, and employment records.
DOI: 10.5281/zenodo.5964239
title: SeaLiT Ontology - An extension of CIDOC-CRM for the modelling of Maritime History information

description: The <strong>SeaLiT Ontology</strong> is a formal ontology intended to facilitate the integration, mediation and interchange of heterogeneous information related to <strong>maritime history</strong>. It aims at providing the semantic definitions needed to transform disparate, localised information sources of maritime history into a coherent global resource. It also serves as a common language for domain experts and IT developers to formulate requirements and to agree on system functionalities with respect to the correct handling of historical information. The ontology uses and extends the <strong>CIDOC Conceptual Reference Model</strong> (ISO 21127:2014), in particular version 7.2.1, as a general ontology of human activity, things and events happening in space and time. The ontology has been developed following a bottom-up process from primary data collected in the context of the <strong>SeaLiT Project</strong> (<em>Seafaring Lives in Transition, Mediterranean Maritime Labour and Shipping, 1850s-1920s</em>). SeaLiT is an international research project, funded by the ERC Starting Grant 2016, which explores the transition from sail to steam navigation and its effects on seafaring populations in the Mediterranean and the Black Sea between the 1850s and the 1920s. More information about the construction of the <strong>SeaLiT Ontology</strong>, the considered data sources, as well as their transformation to a knowledge graph using the SeaLiT Ontology, can be found in the following papers: P. Fafalios, A. Kritsotaki, and M. Doerr, "<em>The SeaLiT Ontology – An Extension of CIDOC-CRM for the Modeling and Integration of Maritime History Information"</em>. ACM Journal on Computing and Cultural Heritage, 2023. https://doi.org/10.1145/3586080 [pdf, bib] P. Fafalios, K. Petrakis, G. Samaritakis, K. Doerr, A. Kritsotaki, Y. Tzitzikas, and M. Doerr, "FAST CAT: Collaborative Data Entry and Curation for Semantic Interoperability in Digital Humanities", ACM Journal on Computing and Cultural Heritage, 2021. https://doi.org/10.1145/3461460 [pdf, bib] The (resolvable) <strong>namespace </strong>of the ontology is: http://www.sealitproject.eu/ontology/ An <strong>OWL implementation</strong> of the ontology is available at: https://sealitproject.eu/ontology/SeaLiT_Ontology_v1.2.owl <strong>Knowledge graphs </strong>that make use of the SeaLiT Ontology are available at: https://zenodo.org/record/6460841. These RDF datasets integrate information of 16 different types of archival sources related to maritime history, including crew lists, payrolls, registers of different types, censuses, and employment records.
DOI: 10.5281/zenodo.7908721
title: Dataset - What are the Machine Learning best practices reported by practitioners on Stack Exchange?

description: The data correspond to the posts (questions and answers) retrieved by querying for posts related to the tag 'machine learning' and the phrase 'best practice(s).' The data were used as the basis for a study currently under review on discussing machine learning best practices as discussed by practitioners in question-and-answer communities such as Stack Exchange. The information from each type of post (i.e., questions and answers) is presented in multiple formats (i.e., .txt, .csv, and .xlsx). <strong>Answers - Variables</strong> <strong>AID</strong>:<strong> </strong> Unique identification of the answer in the Q&A website. <strong>ParentId</strong>: Unique identification of the question associated with the answer in the Q&A website <strong>AcceptedAnswerId</strong> : In the case in which an answer is the most voted question associated with the <em>ParentId</em>, and it is different from the accepted answer, a different identifier from the <em>AID</em> is available. In the case in which the accepted question had a <em>score</em> lower than 1, a -1 is assigned. <strong>ABody:</strong> HTML text of the answer. <strong>Score:</strong> Upvotes - downvotes of the answer. <strong>url_Answer:</strong> URL of the answer. The question URL can be from different websites. <strong>type:</strong> best or accepted. Accepted in the case that the information belongs to the accepted answer of the <em>ParentId </em>question and best in the case in which it is the most voted question of the <em>ParentId </em>question. <strong>Date: </strong>Creation date of the answer. <strong>Questions - Variables</strong> <strong>QID</strong>: Unique identification of the question in the Q&A website. <strong>AcceptedAnswerId</strong>: Unique identification of the accepted answer for a specific question in the Q&A website. In the case in which a question had a most-voted answer different from the accepted one, and the accepted one had a negative score, a -1 was assigned to the <em>AcceptedAnswerId</em><strong>. </strong> <strong>BestAnswerId</strong>: Unique identification of the most voted answer for a specific question in the Q&A website. In the case in which the most voted and accepted questions were the same, then a -1 was assigned to the <em>BestAnswerId</em>. <strong>Qtitle</strong>: Title of the question. <strong>QBody</strong>: HTML text of the question. <strong>Score</strong>: Upvotes - downvotes of the questions. <strong>QTags</strong>: Tags that are associated with each question. <strong>url_question</strong>: URL of the question. The question URL can be from different websites. <strong>Date</strong>: Creation date of the question This dataset is a subset of the Stack Exchange dump of 03.2021 (https://archive.org/details/stackexchange_20210301) in which a series of filters were applied to obtain the data used in the study.
DOI: 10.5281/zenodo.7908722
title: Dataset - What are the Machine Learning best practices reported by practitioners on Stack Exchange?

description: The data correspond to the posts (questions and answers) retrieved by querying for posts related to the tag 'machine learning' and the phrase 'best practice(s).' The data were used as the basis for a study currently under review on discussing machine learning best practices as discussed by practitioners in question-and-answer communities such as Stack Exchange. The information from each type of post (i.e., questions and answers) is presented in multiple formats (i.e., .txt, .csv, and .xlsx).
DOI: 10.5281/zenodo.8058979
title: Dataset - What are the Machine Learning best practices reported by practitioners on Stack Exchange?

description: The data correspond to the posts (questions and answers) retrieved by querying for posts related to the tag 'machine learning' and the phrase 'best practice(s).' The data were used as the basis for a study currently under review on discussing machine learning best practices as discussed by practitioners in question-and-answer communities such as Stack Exchange. The information from each type of post (i.e., questions and answers) is presented in multiple formats (i.e., .txt, .csv, and .xlsx). <strong>Answers - Variables</strong> <strong>AID</strong>:<strong> </strong> Unique identification of the answer in the Q&A website. <strong>ParentId</strong>: Unique identification of the question associated with the answer in the Q&A website <strong>AcceptedAnswerId</strong> : In the case in which an answer is the most voted question associated with the <em>ParentId</em>, and it is different from the accepted answer, a different identifier from the <em>AID</em> is available. In the case in which the accepted question had a <em>score</em> lower than 1, a -1 is assigned. <strong>ABody:</strong> HTML text of the answer. <strong>Score:</strong> Upvotes - downvotes of the answer. <strong>url_Answer:</strong> URL of the answer. The question URL can be from different websites. <strong>type:</strong> best or accepted. Accepted in the case that the information belongs to the accepted answer of the <em>ParentId </em>question and best in the case in which it is the most voted question of the <em>ParentId </em>question. <strong>Date: </strong>Creation date of the answer. <strong>Questions - Variables</strong> <strong>QID</strong>: Unique identification of the question in the Q&A website. <strong>AcceptedAnswerId</strong>: Unique identification of the accepted answer for a specific question in the Q&A website. In the case in which a question had a most-voted answer different from the accepted one, and the accepted one had a negative score, a -1 was assigned to the <em>AcceptedAnswerId</em><strong>. </strong> <strong>BestAnswerId</strong>: Unique identification of the most voted answer for a specific question in the Q&A website. In the case in which the most voted and accepted questions were the same, then a -1 was assigned to the <em>BestAnswerId</em>. <strong>Qtitle</strong>: Title of the question. <strong>QBody</strong>: HTML text of the question. <strong>Score</strong>: Upvotes - downvotes of the questions. <strong>QTags</strong>: Tags that are associated with each question. <strong>url_question</strong>: URL of the question. The question URL can be from different websites. <strong>Date</strong>: Creation date of the question This dataset is a subset of the Stack Exchange dump of 03.2021 (https://archive.org/details/stackexchange_20210301) in which a series of filters were applied to obtain the data used in the study.
DOI: 10.4121/1c8546e4-ecfd-4c60-986e-42198d5e0d5b
title: Dataset of Software Testing Massive Open Online Courses (MOOCs)

description: Software testing is a necessary aspect of software development. With high expectations placed on software testers and a shortage of qualified professionals, Massive Open Online Courses (MOOCs) have emerged as a potential solution to improve software testing education. MOOCs provide accessible education and can offer a comprehensive review of software testing principles and procedures, bridging the gap between formal education and industry expectations. A study of software testing MOOCs was conducted to examine key aspects. This dataset includes information about the MOOC providers used for the research, metadata about courses selected and the information gathered about course descriptions, teaching techniques and topics discussed.
DOI: 10.4121/1c8546e4-ecfd-4c60-986e-42198d5e0d5b.v1
title: Dataset of Software Testing Massive Open Online Courses (MOOCs)

description: Software testing is a necessary aspect of software development. With high expectations placed on software testers and a shortage of qualified professionals, Massive Open Online Courses (MOOCs) have emerged as a potential solution to improve software testing education. MOOCs provide accessible education and can offer a comprehensive review of software testing principles and procedures, bridging the gap between formal education and industry expectations. A study of software testing MOOCs was conducted to examine key aspects. This dataset includes information about the MOOC providers used for the research, metadata about courses selected and the information gathered about course descriptions, teaching techniques and topics discussed.
DOI: 10.5281/zenodo.8069288
title: Early meteorological observations in Almada (Portugal) for the period 1788-1813

description: Daily and monthly meteorological observations recorded in Almada (Portugal) during the period 1788-1813.
DOI: 10.5281/zenodo.8069287
title: Early meteorological observations in Almada (Portugal) for the period 1788-1813

description: Daily and monthly meteorological observations recorded in Almada (Portugal) during the period 1788-1813.
DOI: 10.5517/ccdc.csd.cc2dc8tw
title: CCDC 2215378: Experimental Crystal Structure Determination

description: Related Article: Takahiro Suzuki, Wataru Ikeda, Ayaka Kanno, Kazutada Ikeuchi, Keiji Tanino|2023|Chem.-Eur.J.|29|e202203511|doi:10.1002/chem.202203511
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: 10.6084/m9.figshare.23559956
title: Older than you think: Using U-Pb calcite geochronology to better constrain basin-bounding fault reactivation, Inner Moray Firth Basin, W North Sea

description: Appendix C. Geochronology data.
DOI: 10.6084/m9.figshare.23559956.v1
title: Older than you think: Using U-Pb calcite geochronology to better constrain basin-bounding fault reactivation, Inner Moray Firth Basin, W North Sea

description: Appendix C. Geochronology data.
DOI: 10.6084/m9.figshare.21620814
title: Serum troponin is elevated in acute decompensation and acute-on-chronic liver failure and is associated with severity of liver disease and short-term mortality

description: The role of high sensitive cardiac Troponin (hs-cTn) in patients with liver cirrhosis (LC) and liver-related acute events is not well established. To assess the prognostic performance of hs-cTn I in acute decompensation (AD) and acute-on-chronic liver failure (ACLF). Two cohorts of consecutive patients, a derivation (retrospective) and a validation (prospective), were evaluated and 30-day-mortality was recorded. Hs-cTnI values were measured. Very low hs-cTnΙ (4 ng/L) was considered the cutoff-level. A total of 296 patients with LC [69.3% male, median age 57 (IQR 51–68) years, MELD score 19 (13–25), ACLF (29.4%), AD (48.3%), and without liver-related acute events (22.3%)] were included in the derivation cohort. The 66.2% of total patients had hs-cTnI ≥4 ng/L. Patients with hs-cTnI ≥4 ng/L were older and had more severe LC compared to those with &lt;4ng/L. The multivariate analysis demonstrated that age (<i>p</i> &lt; 0.001) and MELD (<i>p</i> = 0.001) were independent variables associated with elevated hs-cTnI after adjustment for age, sex and hepatic encephalopathy in total patients. When ACLF and AD were analyzed separately, the mortality was higher in patients with hs-cTnI ≥ 4 ng/L compared to lower values (log-rank <i>p</i> = 0.036 and <i>p</i> = 0.019, respectively). In multivariate analysis, MELD (<i>p</i> &lt; 0.001) and hs-cTnI ≥4 ng/L (<i>p</i> = 0.032) were independent prognostic factors of mortality in ACLF/AD groups, after adjustment for age and sex. Similar results were obtained from the validation cohort (<i>N</i> = 148). hs-cTnI levels were higher in patients with severe liver disease. The low cutoff-point of 4 ng/L is accurate in ruling out non-survivors mainly in AD group.