cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6795855
title: Dataset: The availability and completeness of open funder metadata - Case study for publications funded by the Dutch Research Council

description: Data and code belonging to the manuscript: <strong>The availability and completeness of open funder metadata - Case study for publications funded by the Dutch Research Council </strong> <strong>Abstract:</strong><br> Research funders spend considerable efforts collecting information on outcomes of the research they fund. To help funders track publication output associated with their funding, Crossref initiated FundRef in 2013, enabling publishers to register funding information using persistent identifiers. However, it is hard to assess the coverage of funder metadata because it is unknown how many articles are the result of funded research and therefore should include funder metadata. In this paper we looked at 5,004 publications reported by researchers to be the result of funding by a specific funding agency: the Dutch Research Council NWO. Only 67% of these articles contain funding information in Crossref, with a subset acknowledging NWO as funder name and/or Funder IDs linked to NWO (53% and 45%, respectively). Web of Science (WoS), Scopus and Dimensions are all able to infer additional funding information from funding statements in the full text of the articles. Funding information in Lens largely corresponds to that in Crossref, with some additional funding information likely taken from PubMed. We observe interesting differences between publishers in the coverage and completeness of funding metadata in Crossref compared to proprietary databases, highlighting potential to increase the quality of open metadata on funding. <strong>This dataset contains the following files:</strong> <strong>DOIs_unique_CR_Lens_Wos_Scopus_Dim.csv</strong><em> - </em>Dataset of unique DOIs (n= 5,004) with collected information from Crossref and presence/absence of funder information in Lens, Web of Science, Scopus and Dimensions <strong>NWO_funder_names_Crossref.txt</strong><em> </em>- List of funder name variants for NWO found in Crossref <strong>Google_Apps_Script.js</strong> - Google Apps Script for retrieving information from Crossref and processing Dimensions results <strong>DOI_cleaning.R</strong><em> - </em>R script for cleaning DOIs
description: We are able to share the majority of the raw data underpinning our paper, except for part of the proprietary bibliometric data we used from Web of Science, Scopus and Dimensions. Data from Lens is available as collection here: https://www.lens.org/lens/search/scholar/list?collectionId=200429
DOI: 10.5281/zenodo.852652
title: Data For: Am I Who I Say I Am?

description: Across social media platforms users (sub)consciously represent themselves in a way which is appropriate for their intended audience. This has unknown impacts on studies with unobtrusive designs based on digital (social) platforms, and studies of contemporary social phenomena in online settings. A lack of appropriate methods to identify, control for, and mitigate the effects of self-representation, the propensity to express socially responding characteristics or self-censorship in digital settings, hinders the ability of researchers to confidently interpret and generalize their findings. This article proposes applying boosted regression modelling to fill this research gap. A case study of paid Amazon Mechanical Turk workers (n=509) is presented where workers completed psychometric surveys and provided anonymized access to their Facebook timelines. Our research finds indicators of self-representation on Facebook, facilitating suggestions for its mitigation. We validate the use of LIWC for Facebook personality studies, as well as find discrepancies with extant literature about the use of LIWC-only approaches in unobtrusive designs. Using survey data and LIWC sentiment categories as predictors, the boosted regression model classified the Five Factor personality model with an average accuracy of 74.6%. The contribution of this work is an accurate prediction of psychometric information based on short, informal text.
description: SPSS format
DOI: 10.6084/m9.figshare.6741422.v14
title: COCI CSV dataset of all the citation data

description: This dataset contains all the citation data (in CSV format) included in COCI, released on 26 March 2022. In particular, each line of the CSV file defines a citation, and includes the following information:<b>[field "oci"]</b> the Open Citation Identifier (OCI) for the citation;<b>[field "citing"]</b> the DOI of the citing entity;<b>[field "cited"]</b> the DOI of the cited entity;<b>[field "creation"]</b> the creation date of the citation (i.e. the publication date of the citing entity);<b>[field "timespan"]</b> the time span of the citation (i.e. the interval between the publication date of the cited entity and the publication date of the citing entity);<b>[field "journal_sc"]</b> it records whether the citation is a journal self-citations (i.e. the citing and the cited entities are published in the same journal);<b>[field "author_sc"]</b> it records whether the citation is an author self-citation (i.e. the citing and the cited entities have at least one author in common).<br>This version of the dataset contains:<br>1,294,283,603 citations;72,268,850 bibliographic resources.The size of the zipped archive is 32.81 GB, while the size of the unzipped CSV file is 210.4 GB.<br>Additional information about COCI can be retrieved in the official webpage.<br>
DOI: 10.5281/zenodo.5562842
title: Crossref Funder Registry - Mapping to top-level funding organizations

description: The Crossref Funder Registry is an open registry of names and identifiers of research funding organizations. The registry has a hierarchical structure. Each organization may have relations with parent and child organizations.<br> <br> We provide a mapping of organizations in the Crossref Funder Registry to the corresponding top-level organizations. The mapping is based on version 1.34 of the Crossref Funder Registry, made available in an RDF file in the Crossref Funder Registry GitLab repository.<br> <br> To create the mapping to top-level organizations, we first extracted the hierarchical structure of the Crossref Funder Registry based on all ‘narrower’ and ‘broader’ assignments. Using this hierarchical structure, we then identified for each of the 27,681 active organizations in the registry the corresponding top-level organizations. For most organizations, we identified a single top-level organization. However, organizations may have multiple parent organizations, and for some organizations we therefore identified multiple top-level organizations.<br> <br> Example: ‘H2020 Societal Challenges’ has ‘Horizon 2020 Framework Programme’ as its only parent organization, ‘Horizon 2020 Framework Programme’ has ‘European Commission’ as its only parent organization, and ‘European Commission’ does not have a parent organization. The top-level organization corresponding to ‘H2020 Societal Challenges’ therefore is ‘European Commission’.<br> <br> We ignored the following parent-child relations in order to avoid having cycles in the network of parent-child relations: Child organization: Ministry of Science and Technology of the People's Republic of China (CHN) [DOI: 10.13039/501100002855]<br> Parent organization: National Science and Technology Major Project (CHN) [DOI: 10.13039/501100018537] Child organization: University of Georgia (USA) [DOI: 10.13039/100007699]<br> Parent organization: College of William and Mary (USA) [DOI: 10.13039/100008277] We ignored the following parent-child relations because they seem to be mistakes: Child organization: College of William and Mary (USA) [DOI: 10.13039/100008277]<br> Parent organization: University of Georgia (USA) [DOI: 10.13039/100007699] Child organization: Fakulti Pertanian, Universiti Putra Malaysia (MYS) [DOI: 10.13039/501100006018]<br> Parent organization: Department of Child Health, University of Manchester (GBR) [DOI: 10.13039/100007546] Child organization: Pusat Penyelidikan dan Inovasi, Universiti Malaysia Sabah (MYS) [DOI: 10.13039/501100006243]<br> Parent organization: Workplace Health, Safety and Compensation Commission (CAN) [DOI: 10.13039/501100000183] Child organization: Workplace Health, Safety and Compensation Commission (CAN) [DOI: 10.13039/501100000183]<br> Parent organization: Shahid Beheshti University of Medical Sciences (IRN) [DOI: 10.13039/501100005851]
DOI: 10.6073/pasta/ec507ac70846b17d0633d95aa3c680c6
title: Pond data: physical, chemical, and biological characteristics with scientific and United States of America state definitions from literature and legislative surveys

description: Ponds are often identified by their small size and shallow depths, but the lack of a universal definition hampers science and weakens legal protection. In order to determine a working definition of ‘pond’, we conducted a literature search for scientific definitions, a U.S. state survey for management definitions, and looked at pond ecosystem function using data from the literature search. Our dataset includes physical, chemical, and biological data for 1327 waterbodies ≤ 20 ha in surface area and ≤ 9 m in maximum or mean depth from our literature review. These data have a global distribution, we include a table of latitudes and longitudes, and span many years (1946-2019). We have also included a table of 54 pond definitions from the literature review and a table of U.S. state definitions of ponds, wetlands, and lakes resulting from our survey.
DOI: 10.5281/zenodo.7322688
title: World Atlas of Classifier Languages

description: Cite the source of the dataset as: Her, One-Soon, Harald Hammarström and Marc Allassonnière-Tang. 2022. Defining numeral classifiers and identifying classifier languages of the world. Linguistics Vanguard. https://doi.org/10.1515/lingvan-2022-0006
DOI: 10.5281/zenodo.7322687
title: World Atlas of Classifier Languages

description: Cite the source of the dataset as: Her, One-Soon, Harald Hammarström and Marc Allassonnière-Tang. 2022. Defining numeral classifiers and identifying classifier languages of the world. Linguistics Vanguard. https://doi.org/10.1515/lingvan-2022-0006
DOI: 10.17632/5btcx9fdjv.1
title: Developed Computer Scripts for "Static and Seismic Responses of Pile-Supported Marine Structures under Scoured Conditions"

description: 1. The developed computer scripts (in MATLAB and/or OpenSees platforms) for implementation of the proposed methods proposed in the doctoral disseration "Static and seismic responses of pile-supported marine structures under scoured conditions" (author: Wenyu Jiang, University of Victoria).
2. For more details, please contact the authours via email: wenyujiang@uvic.ca; uvicwenyujiang@gmail.com.
DOI: 10.6084/m9.figshare.21557268
title: Supplementary-Electron microprobe analysis Data

description: Electron microprobe analysis Data.
DOI: 10.6084/m9.figshare.21557466
title: depressive symptoms of chronic heart failure.sav

description: There are some demographic characteristics and medical-related characteristics of chronic heart failure, as well as PHQ-9 score.
DOI: 10.6084/m9.figshare.21557466.v1
title: depressive symptoms of chronic heart failure.sav

description: There are some demographic characteristics and medical-related characteristics of chronic heart failure, as well as PHQ-9 score.
DOI: 10.14279/depositonce-10638.3
title: Supporting Information and Data for Machine Learning Algorithms Applied to Identify Microbial Species by their Motility

description: Future missions to potentially habitable places in the Solar System require biochemistry-independent methods for detecting potentially alien life forms, for which ‘motility’ is an excellent candidate. Here we present a semi-automated experimental setup, capable of distinguishing the movement of abiotic particles due to Brownian motion from the motility behavior of the bacteria Pseudoalteromonas haloplanktis, Planococcus halocryophilus, Bacillus subtilis, and Escherichia coli. Supervised machine learning algorithms were also used to specifically identify these species based on their characteristic motility behavior. While we were able to distinguish microbial motility from the abiotic movements due to Brownian motion with an accuracy exceeding 99%, the accuracy of the automated identification rates of the selected species does not exceed 82%. This study serves as the basis for the further development of a microscopic life recognition system for upcoming missions to Mars or the ocean worlds of the outer Solar System.
DOI: 10.6084/m9.figshare.21557554
title: Additional file 2 of Knowledge, attitude, and practice of evidence-based medicine among resident physicians in hospitals of Syria: a cross-sectional study

description: Additional file 2. EBM Syrian residents Quantitative dataset.
DOI: 10.6084/m9.figshare.21557554.v1
title: Additional file 2 of Knowledge, attitude, and practice of evidence-based medicine among resident physicians in hospitals of Syria: a cross-sectional study

description: Additional file 2. EBM Syrian residents Quantitative dataset.
DOI: 10.6084/m9.figshare.21557597
title: Additional file 2 of Vault differences in eyes implanted with spherical and toric implantable collamer lenses: an inter-eye analysis

description: Additional file 2: Raw Data. Table S2a. Demographics (Variables: Gender and Age); Table S2b. Preoperative refraction (Variables: Sphere, Cylinder and axis, Distance Corrected Visual Acuity (DCVA) for the Right (OD) and Left eye (OS); Table S2c. Postoperative refraction (Variables: Sphere, Cylinder and axis, Uncorrected Visual Acuity (UCVA) for the Right (OD) and Left eye (OS); Table S2d. ICL Characteristics for the OD and OS (Variables: Type of ICL implanted per eye, Diameter, Sphere, Cylinder and axis); Table S2e. Preoperative Pentacam measurements (Variables: Corneal Diameter, Central Corneal Thickness (CCT), Central Keratometry (Kc), Corneal Astigmatism) for the OD and OS; Table S2f. Preoperative Visante measurements (Variables: Anterior Chamber Depth (ACD); Anterior Chamber Width (A2A); Central Corneal Thickness (CCT); Crystalline Lens Rise (CLR); Anterior Chamber Angle Nasal and Temporal (ACA Nasal and Temporal) and Pupil diameter) for the OD and OS; Table S2g. Postoperative Visante measurements (Variables: ICL Thickness; Vault and Pupil Diameter) for the OD and OS.
DOI: 10.6084/m9.figshare.21557597.v1
title: Additional file 2 of Vault differences in eyes implanted with spherical and toric implantable collamer lenses: an inter-eye analysis

description: Additional file 2: Raw Data. Table S2a. Demographics (Variables: Gender and Age); Table S2b. Preoperative refraction (Variables: Sphere, Cylinder and axis, Distance Corrected Visual Acuity (DCVA) for the Right (OD) and Left eye (OS); Table S2c. Postoperative refraction (Variables: Sphere, Cylinder and axis, Uncorrected Visual Acuity (UCVA) for the Right (OD) and Left eye (OS); Table S2d. ICL Characteristics for the OD and OS (Variables: Type of ICL implanted per eye, Diameter, Sphere, Cylinder and axis); Table S2e. Preoperative Pentacam measurements (Variables: Corneal Diameter, Central Corneal Thickness (CCT), Central Keratometry (Kc), Corneal Astigmatism) for the OD and OS; Table S2f. Preoperative Visante measurements (Variables: Anterior Chamber Depth (ACD); Anterior Chamber Width (A2A); Central Corneal Thickness (CCT); Crystalline Lens Rise (CLR); Anterior Chamber Angle Nasal and Temporal (ACA Nasal and Temporal) and Pupil diameter) for the OD and OS; Table S2g. Postoperative Visante measurements (Variables: ICL Thickness; Vault and Pupil Diameter) for the OD and OS.
DOI: 10.6084/m9.figshare.21557608
title: Additional file 2 of metaMIC: reference-free misassembly identification and correction of de novo metagenomic assemblies

description: Additional file 2: Table S1-S13.
DOI: 10.6084/m9.figshare.21557608.v1
title: Additional file 2 of metaMIC: reference-free misassembly identification and correction of de novo metagenomic assemblies

description: Additional file 2: Table S1-S13.
DOI: 10.6084/m9.figshare.21557639
title: Additional file 2 of A cross-sectional study: exploring knowledge and attitude of medical and nursing students to Care for Elders in the future

description: Additional file 2.
DOI: 10.6084/m9.figshare.21557639.v1
title: Additional file 2 of A cross-sectional study: exploring knowledge and attitude of medical and nursing students to Care for Elders in the future

description: Additional file 2.
DOI: 10.6084/m9.figshare.21557654
title: Additional file 2 of Association of body mass index and inflammatory dietary pattern with breast cancer pathologic and genomic immunophenotype in the nurses’ health study

description: Additional file 2: Supplementary Table S2. Immune Gene Expression Scores. Gene expression scores for all samples used in analyses.
DOI: 10.6084/m9.figshare.21557654.v1
title: Additional file 2 of Association of body mass index and inflammatory dietary pattern with breast cancer pathologic and genomic immunophenotype in the nurses’ health study

description: Additional file 2: Supplementary Table S2. Immune Gene Expression Scores. Gene expression scores for all samples used in analyses.
DOI: 10.6084/m9.figshare.21557657
title: Additional file 3 of Association of body mass index and inflammatory dietary pattern with breast cancer pathologic and genomic immunophenotype in the nurses’ health study

description: Additional file 3: Supplementary Table S3. Spearman's correlation of individual signature score with immune marker immunohistochemistry (IHC).
DOI: 10.6084/m9.figshare.21557657.v1
title: Additional file 3 of Association of body mass index and inflammatory dietary pattern with breast cancer pathologic and genomic immunophenotype in the nurses’ health study

description: Additional file 3: Supplementary Table S3. Spearman's correlation of individual signature score with immune marker immunohistochemistry (IHC).
DOI: 10.6084/m9.figshare.21557665
title: Additional file 1 of Under contract and in good health: a multigroup cross-lagged panel model of time use and health-related quality of life in working-age men and women

description: Additional file 1. R sample code.
DOI: 10.6084/m9.figshare.21557665.v1
title: Additional file 1 of Under contract and in good health: a multigroup cross-lagged panel model of time use and health-related quality of life in working-age men and women

description: Additional file 1. R sample code.
DOI: 10.6084/m9.figshare.21557668
title: Additional file 2 of Under contract and in good health: a multigroup cross-lagged panel model of time use and health-related quality of life in working-age men and women

description: Additional file 2. Descriptive statistics and correlations of time-use categories and HRQoL.
DOI: 10.6084/m9.figshare.21557671
title: Additional file 3 of Under contract and in good health: a multigroup cross-lagged panel model of time use and health-related quality of life in working-age men and women

description: Additional file 3. Full results of the multigroup cross-lagged panel model without controls.
DOI: 10.6084/m9.figshare.21557671.v1
title: Additional file 3 of Under contract and in good health: a multigroup cross-lagged panel model of time use and health-related quality of life in working-age men and women

description: Additional file 3. Full results of the multigroup cross-lagged panel model without controls.
DOI: 10.6084/m9.figshare.21557674
title: Additional file 4 of Under contract and in good health: a multigroup cross-lagged panel model of time use and health-related quality of life in working-age men and women

description: Additional file 4. Full results of the multigroup cross-lagged panel model with controls.
DOI: 10.6084/m9.figshare.21557674.v1
title: Additional file 4 of Under contract and in good health: a multigroup cross-lagged panel model of time use and health-related quality of life in working-age men and women

description: Additional file 4. Full results of the multigroup cross-lagged panel model with controls.
DOI: 10.5523/bris.3f9j9z626s7f32a3r5j1wd7zt7
title: 40 interviews with healthcare professionals to explore implementation of hip fracture services

description: 40 interviews carried out at 4 hospitals across England that aim to understand the implementation of hip fracture services, including barriers and facilitators to delivery. Interviews have been carried out with a range of healthcare professionals across the care pathway. This dataset is under embargo until 1st April 2029.
DOI: 10.5281/zenodo.7248870
title: TableS1_Dataset - Rhyme Structure for 25 versions of Sadhukarn main melody collected in Thailand, Cambodia, and Laos: CC0 license

description: The dataset of rhyme music structure obtained 25 different versions of Sadhukarn main melody collected from Thailand, Laos, Cambodia, and their border areas. Specifically, the material outcomes synthesized by Thai music measure and solfege syllables in Western music notation are applied for setting the rhyme structure format. To define Thai rhyme music structure, a pillar tone or “Look-Tok” in Thai musical terms is a necessary material used for the process. This dataset can be used for a wide spectrum of music analysis.
DOI: 10.5281/zenodo.7248869
title: TableS1_Dataset - Rhyme Structure for 25 versions of Sadhukarn main melody collected in Thailand, Cambodia, and Laos: CC0 license

description: The dataset of rhyme music structure obtained 25 different versions of Sadhukarn main melody collected from Thailand, Laos, Cambodia, and their border areas. Specifically, the material outcomes synthesized by Thai music measure and solfege syllables in Western music notation are applied for setting the rhyme structure format. To define Thai rhyme music structure, a pillar tone or “Look-Tok” in Thai musical terms is a necessary material used for the process. This dataset can be used for a wide spectrum of music analysis.
DOI: 10.5281/zenodo.7322757
title: Proto-gene supplemental datas

description: Supplemental data
DOI: 10.5281/zenodo.7322756
title: Proto-gene supplemental datas

description: Supplemental data
DOI: 10.5281/zenodo.7251547
title: DNA origami book biosensor for multiplex detection of cancer-associated nucleic acids

description: This dataset contains the raw data that were used for the publication entitled, "DNA origami book biosensor for multiplex detection of cancer-associated nucleic acids" published in Nanoscale. Abstract DNA nanotechnology provides a promising approach for the development of biomedical point-of-care diagnostic nanoscale devices that are easy to use and cost-effective, highly sensitive and thus constitute an alternative to expensive, complex diagnostic devices. Moreover, DNA nanotechnology-based devices are particularly advantageous for applications in oncology, owing to being ideally suited for the detection of cancer-associated nucleic acids, including circulating tumor-derived DNA fragments (ctDNAs), circulating microRNAs (miRNAs) and other RNA species. Here, we present a dynamic DNA origami book biosensor that is precisely decorated with arrays of fluorophores acting as donors and acceptors and also fluorescence quenchers that produce a strong optical readout upon exposure to external stimuli for the single or dual detection of target oligonucleotides and miRNAs. This biosensor allowed the detection of target molecules either through the decrease of Förster resonance energy transfer (FRET) or an increase in the fluorescence intensity profile owing to a rotation of the constituent top layer of the structure. Single-DNA origami experiments showed that detection of two targets can be achieved simultaneously within 10 min with a limit of detection in the range of 1–10 pM. Overall, our DNA origami book biosensor design showed sensitive and specific detection of synthetic target oligonucleotides and natural miRNAs extracted from cancer cells. Based on these results, we foresee that our DNA origami biosensor may be developed into a cost-effective point-of-care diagnostic strategy for the specific and sensitive detection of a variety of DNAs and RNAs, such as ctDNAs, miRNAs, mRNAs, and viral DNA/RNAs in human samples.