Find research datasets worth reusing

opencc-by-4.0Aug 2021View details →

Data used for publication on 'Analysis of blue corona discharges at the top of tropical thunderstorm clouds in different phases of convection'

This data was used from implementing Figures 1-4 in the main manuscript and all the Figures in the Supportive Information of the submitted publication 'Analysis of blue corona discharges at the top of tropical thunderstorm clouds in different phases of convection'.

opennotspecifiedJul 2012View details →

FIGURE 1 in The dates of publication of L.A.G. Bosc's Histoire naturelle des Crustacés

FIGURE 1. The title-pages of the first (left) and second (right) volumes of the Histoire naturelle des Crustacés (Bosc 1801a, b). Note the uncertainty in the date of the publication in the anonymous annotation on the title-page of the first volume. From a work no longer in copyright held by the Smithsonian Institution and digitised under the Biodiversity Heritage Library initiative (http://dx.doi.org/10.5962/bhl.title.39831).

dryad32/100

Safe traveling in public transport amid COVID-19

Several intense policies, such as mandatorily wearing masks and practicing social distancing, have been implemented in South Korea to prevent the spread of the novel coronavirus disease (COVID-19). In this study, we analyzed and measured the impact of the aforementioned policies by calculating the degree of infection exposure in public transportation. Specifically, we simulated how passengers encounter and infect each other during their journeys in public transportation by tracking movements of passengers. The probabilities of exposure to infections in public transportation were compared via a combination of the aforementioned policies by using the SEIR model, a respiratory infectious disease diffusion model. We determined that the mandatorily wearing of masks exhibits similar effects to maintaining social distancing 2 m in preventing COVID-19. During peak hours, in the cases of mandatorily wearing and practicing social distancing with masks, the reduction in infection rates corresponded to 93.5% and 98.1%, respectively.

opencc-zeroAug 2021View details →

opennotspecifiedApr 2013View details →

FIGURE 1 in The leucosiid crabs described by Thomas Bell in 1855: original description and dates of publication (Crustacea: Decapoda: Brachyura)

FIGURE 1. Two of Bell's (1855) publications on the Leucosiidae Samouelle, 1819. A, title-page of Bell's (1855d) Catalogue of Crustacea in the Collection of the British Museum; B, plate 34 from Bell (1855c) published in the Transactions of the Linnean Society. From publications no longer in copyright (A, Google Books, www.books.google.com; B, the Biodiversity Heritage Library, www.biodiversitylibrary.org).

FIGURE 5 in Nomenclatural and taxonomic problems related to the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany

FIGURE 5. Accompanying letters of four documents received by the Paris Museum library: facsimiles of PDFs of (a–c) three works published by Parasites & Vectors (Andrade Filho et al. 2009, Freeman & Sommerville 2010, Poinar 2009) and (d) a work published by BMC evolutionary Biology (Tan et al. 2012), letter received on 14 January 2013.

FIGURE 2 in Nomenclatural and taxonomic problems related to the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany

FIGURE 2. First page of Yamaguchi et al. (2012) under two different versions: (a) PDF dated 8 March 2012, downloaded from the BMC website on 6 November 2012; (b) paper facsimile dated 8 March 2012, received by the Paris Museum library before 5 November 2012 (two pages on one, successive pages printed upside down).

FIGURE 4 in Nomenclatural and taxonomic problems related to the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany

FIGURE 4. Four pages of Bargues et al. (2011) under two different versions: (a) page 11 of PDF dated 12 July 2011, downloaded from the BMC website on 11 November 2012, showing its fig. 8 with its correct legend; (b–d) pages 6, 9 and 15 of paper facsimile dated 12 July 2011, received by the Paris Museum library before 5 November 2012, showing its fig. 2 (legend of fig. 2 in PDF, tree of fig. 8 in PDF), its fig. 4 (legend of fig. 4 in PDF, photograph of fig. 10 in PDF) and its fig. 10 (legend and photograph of fig. 10 in PDF).

FIGURE 3. Page 9 in Nomenclatural and taxonomic problems related to the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany

FIGURE 3. Page 9 of Malm & Johanson (2011) under two different versions: (a) PDF dated 12 January 2011, downloaded from the BMC website on 11 November 2012; (b) paper facsimile dated 12 January 2011, received by the Paris Museum library before 5 November 2012 (compared to the PDF, throughout the printed document blue was replaced by violet and red by orange).

FIGURE 6 in Nomenclatural and taxonomic problems related to the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany

FIGURE 6. First page of PDFs of Tan et al. (2012) under two different versions, both dated 9 July 2012, as downloaded from the BMC website on: (a) 6 November 2012 (prepublication); (b) 16 December 2012 (final publication). In (b), the small boxes surrounded with green are taken from pages 18 (dates) and 19 (DOI and reference).

FIGURE 7 in Nomenclatural and taxonomic problems related to the electronic publication of new nomina and nomenclatural acts in zoology, with brief comments on optical discs and on the situation in botany

FIGURE 7. Four figures of prepublication of Tan et al. (2012), as downloaded from the BMC website on 6 November 2012. Note than fig. 3 and 4 are identical but with different legends.

opennotspecifiedAug 2021View details →

FIGURE 1. A–C in The valid publication and identity of Aristolochia compressicaulis (Aristolochiaceae)

FIGURE 1. A–C: Isotrema compressicaule. A. Flowering branch, B. Flower in frontal view, C. Longitudinal-section of flower. D–F: I. versicolor. D. Flowering branch, E. Flower in frontal view, F. Longitudinal-section of flower. G–I: I. liangshanense. G. Flowering branch, H. Flower in frontal view, I. Longitudinal-section of flower.—A–F: photographed by Xin-Xin Zhu; G–I: photographed by Hai-Ning Li.

opencc-by-4.0Aug 2021View details →

Large eddy simulation input data for publication "Pressure fields in the airflow over wind-generated surface waves" by Funke et al.

Input files allow for the simulation of a turbulent flow over a sinusoidal surface using the PALM LES model, version 6.0, revision 4901.

opencc-by-4.0Jul 2021View details →

Data set for publication.

Sequencing data.

opennotspecifiedMay 2021View details →

FIGURE 2 in How Kalanchoe marmorata (Crassulaceae subfam. Kalanchooideae), a distinctive central and east African species, received its name, and the later, valid publication of K. macrantha by Maire

FIGURE 2. The bright white flowers of Kalanchoe marmorata, produced during the winter months, are some of the longest in the genus. Photograph: Gideon F. Smith.

opennotspecifiedMay 2021View details →

FIGURE 1 in How Kalanchoe marmorata (Crassulaceae subfam. Kalanchooideae), a distinctive central and east African species, received its name, and the later, valid publication of K. macrantha by Maire

FIGURE 1. In most forms of Kalanchoe marmorata the leaves are highly mottled with purple blotches on a light dull green background. Photograph: Gideon F. Smith.

Source Data for the publication "From crystallographic data to solution structure of photoreceptors: the case of AppA BLUF domain"

This dataset contains the raw data for the results shown in the paper, all in excel format, one sheet per file: <ul> <li> chemical_shifts.xlsx - Chemical shifts of FMN and residues (on optimized frames) </li> <li> excitation_energies.xlsx - Excitation energies of FMN (on optimized frames) </li> <li> Distance_H3.xlsx - Distance between ASN-OD1 and FMN-H3 (on optimized frames) </li> <li> CO_freq_QMMM_MD.xlsx - Average C=O frequencies and relevant distances for each QM/MM MD.   </li> </ul>

Re-identification of Individuals in Genomic Datasets Using Public Face Images

Image-genome pairs in these synthetic datasets were created by combining a subset of the publicly available face image dataset, CelebA, and genotypes from OpenSNP. The genome in a given pair does not correspond to the individual in the image (taken from CelebA), but comes instead from an individual with the same set of phenotypes (taken from OpenSNP). Artificial genotypes were created for each image (genotype refers only to the small subset of SNPs we are interested in) using all available data from OpenSNP where self-reported phenotypes are present. In the Synthetic-Ideal dataset, to each image, we assigned a genotype from OpenSNP that corresponds to an individual with the same phenotypes, such that the probability of the selected phenotypes is maximized, given the genotype. In other words, we picked the genotype from the OpenSNP data that is most representative of an individual with a given set of phenotypes. In the Synthetic-Realistic dataset, to each image, we assigned a genotype from OpenSNP that corresponds to an individual with the same phenotypes, but at random according to the empirical distribution of phenotypes for particular SNPs in our data. Since CelebA does not have labels for all considered phenotypes, 1000 images from this dataset were manually labeled by one of the authors. After cleaning and removing ambiguous cases, the resulting datasets consist of 456 records.

FoldIt Public Dataset

This is the public dataset that is used for training FoldIt, a deep learning model for haustral fold detection and segmentation. TrainA contains the optical colonoscopy images (OC). TrainB contains the haustral fold annotations overlayed on the virtual colonoscopy (VC) images. Lastly, TrainC contains the VC images. The model trained on this dataset is also included here. Abstract: Haustral folds are colon wall protrusions implicated for high polyp miss rate during optical colonoscopy procedures. If segmented accurately, haustral folds can allow for better estimation of missed surface and can also serve as valuable landmarks for registering pre-treatment virtual (CT) and optical colonoscopies, to guide navigation towards the anomalies found in pre-treatment scans. We present a novel generative adversarial network, FoldIt, for feature-consistent image translation of optical colonoscopy videos to virtual colonoscopy renderings with haustral fold overlays. A new transitive loss is introduced in order to leverage ground truth information between haustral fold annotations and virtual colonoscopy renderings. We demonstrate the effectiveness of our model on real challenging optical colonoscopy videos as well as on textured virtual colonoscopy videos with clinician-verified haustral fold annotations. In essence, the FoldIt model is a method for translating between domains when a shared common domain is available. We use the FoldIt model to learn a translation from optical colonoscopy to haustral fold annotation via a common virtual colonoscopy domain. You can find the code and additional detail about Foldit via our Computation Endoscopy Platform at <a href="https://github.com/nadeemlab/CEP">https://github.com/nadeemlab/CEP</a>   Please cite the following papers when using this dataset. The OC data came from the Hyper Kvasir datset: <blockquote> Borgli, Hanna, et al. "HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy." Scientific data 7.1 (2020): 1-14. </blockquote> The VC and fold annotation data came from the following TCIA dataset: <blockquote> Smith K, Clark K, Bennett W, Nolan T, Kirby J, Wolfsberger M, Moulton J, Vendt B, Freymann J. (2015). Data From CT_COLONOGRAPHY. The Cancer Imaging Archive. <a href="https://doi.org/10.7937/K9/TCIA.2015.NWTESAY1">https://doi.org/10.7937/K9/TCIA.2015.NWTESAY1</a> </blockquote>

Graphical integrity issues in open access publications: detection and patterns of proportional ink violations

Here are all the bar charts we annotated manually and used to train the graphical integrity detector. For more detail about our method, please visit our GitHub repository. (https://github.com/sciosci/Graphical_Integrity_Issues)

Data Set of Publication on Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams

This data set contains the evaluation data of our publication on "<a href="https://doi.org/10.1016/j.jss.2021.111138">Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams</a>". The data set contains an overview on our implementation, description of the evaluation cases, and the evaluation results. The application to produce this data is available in another data set, which is linked to this data set.