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zenodo36/100

A formative usability study of workflow management systems in label-free digital pathology - Questionnaires

<p>This repository holds the necessary questionnaires, participant data, interview questions and data, as well as a descriptive Readme file that was used for our publication &quot;A formative usability study of workflow management systems in label-free digital pathology&quot; by Markus Jelonek et al. (2022), submitted to F1000Research.</p> <p>&nbsp;</p> <p>Abstract:</p> <p>We present a formative usability study that investigates the usability of different<br> workflow management systems in the field of biomedical data analysis. Specifically, we study a task in the field of so-called label-free digital pathology and investigate one graphical user interface based workflow and one script-based workflow to solve the task. Our main intention is to gain first insights into the systematic study of usability in the context of biomedical image analysis, and formulate experiences and guidelines for future usability studies dealing with workflow management systems. Embedded in a specific setup dealing with label-free digital pathology, the core question behind our contribution is how usability studies for scientific workflow management can be conducted, and how they can be used systematically to improve such tools. Further, we address specific questions about the resource utilisation and management of usability studies, including the recruitment of participants as well as the design of specific workflows to be investigated.</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Dataset: digital photographs of specimens in manuscript entitled Taxonomic revision of the mydas-fly genera Eremohaplomydas Bequaert, 1959, Haplomydas Bezzi, 1924, and Lachnocorynus Hesse, 1969 (Insecta: Diptera: Mydidae)

<p>This is the original files containing the information published in digital specimens and photo records here in Zenodo.</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Supplementary Material of the paper entitled "Governing Digital Twin technology on smart and sustainable tourism"

<p>In this document, we provide some supplementary material of the paper entitled &ldquo;Governing Digital Twin technology on smart and sustainable tourism&rsquo;&rsquo;.</p> <p>Rahmadian, E., Feitosa, D., Zwitter, A. (2022). Governing Digital Twin technology on smart and sustainable tourism.</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Data Augmentation for learning mechanical digital twins of voids in welding joints

<p>In Source-2_Data_Augmentation:</p> <p>Exercice1_augmentation.ipynb Jupyter Notebook for data warpping of defect images.</p> <p>Exercice2_augmentation_multimodale.ipynb Jupyter Notebook for multimodal data augmentaion (defect images and mechanical fields) via oversampling</p> <p>Exercice3_clustering.ipynb Data clustering using the k-medoids algorithm applied to mechanical dissimilarity of the defects.</p> <p>k_medoids.py is a python code of a kmedoids algorithm.</p> <p>in Data:</p> <p>All_images.npy (numpy file) contains the defect images.</p> <p>All_Stresses.npy (numpy) contains mechanical fields, All_Stresses[k,i,j,ic,it] is the instance number k of the component ic of the Cauchy stress tensor at time it. The mechanical problem is decribed in <a href="https://dx.doi.org/10.5802/crmeca.51">&lang;10.5802/crmeca.51&rang;</a>. <a href="https://hal.archives-ouvertes.fr/hal-03113503">&lang;hal-03113503&rang;.</a></p> <p>New_images_1.npy and New_Stresses_1.npy are augmented data for k=1.</p> <p>New_images_87.npy and New_Stresses_87.npy are augmented data for k=87.</p> <p>Dissimilarity_Stress.npy is the Frobenius norm of the distances between stress tensors (All_Stresses.npy).</p> <p>&nbsp;</p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

African Red Slip Ware Digital (ARS3D) - Comparison-Data

<p>Characteristic of the North African bowls, plates, and jugs are their pictorial decorations applied mainly by appliqu&eacute;s and stamps. As mass-produced image carriers and everyday objects, the ARS spread throughout the empire.</p> <p>The range of motifs includes mythological scenes as well as scenes from the Old and New Testament, circus, arena and hunting scenes as well as fish and plant motifs. The appliqu&eacute;s-decorated pottery thus provides insights into Late Antique imagination and its changes, as well as into the economic history of the period between the 3rd and 5th centuries AD in North Africa.</p> <p>Previous documentation methods were not able to capture the objects and their decoration in an adequate way. The digital recording of the RGZM&#39;s collections by 3D scans allows to compare potentially identical appliqu&eacute;s and to assign them to their negative forms and the corresponding stamps.</p> <p>Whereas vessel curvature previously falsified the assignment of appliqu&eacute;s and models, 3D analysis and visualisation tools now allow a comparison . Metadata created for each object increases the effectiveness and accuracy of determining image context and content. Issues related to the production of the ARS and the process flows within the workshops can be investigated through the analysis of the 3D data.</p> <p>The developed ontology uses CIDOC CRM and various extensions. The data mainly consists of objects (E24), on which e.g. applications (features, E25) can be found. These objects can be described semantically, e.g. by the shape or time epoch. Features are described with observations, e.g. a human type man standing and wearing a beard. These observations lead to interpretations whose arguments can be observations.</p>

opencc-by-4.0Nov 2021View details →
zenodo36/100

Repository for "Standardized classification of cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography"

<p>Repositories&nbsp;for&nbsp;&quot;Standardized classification of&nbsp;cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography&quot;</p> <p>Repository&nbsp;1: Digital subtraction angiographies of CVS patients for grading with pM1 values</p> <p>Repository&nbsp;2: Vessel values</p> <p>Repository 3: Clinical data of CVS patients</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

(PDF-like) An Ontology for Supporting Digital Forensics Controlled Experiments: Early Stages of Development - Figures

<p>Figures from An Ontology for Supporting Digital Forensics Controlled Experiments: Early Stages of Development</p>

opencc-by-4.0Mar 2022View details →
zenodo36/100

The phenotypic plasticity of an evolving digital organism

<p>Data set and R code used in the analysis reported in the manuscript entitled &quot;<em>The phenotypic plasticity of an evolving digital organism</em>&quot;, which has been accepted in Proc. R. Open. Sci.&nbsp;for publication.</p>

openmit-licenseJul 2021View details →
zenodo36/100

Figure 2 from: Keller D., Radivojević N., Lazzarini V. (2022). Issues in ubimus archaeology: Beyond pure computing and precision during the analogue-digital transition

<p><strong>Figure2_W20_003_2_P92</strong></p> <p><strong>Fonds Jean-Claude Risset, Laboratoire PRISM (UMR 7061 &ndash; France). The copyright applies to documents digitized by the PRISM laboratory.</strong></p>

opencc-by-4.0Apr 2022View details →
zenodo36/100

Figure 3 from: Keller D., Radivojević N., Lazzarini V. (2022). Issues in ubimus archaeology: Beyond pure computing and precision during the analogue-digital transition

<p><strong>Figure3. W20_003_3_P10</strong><br> <strong>Fonds Jean-Claude Risset, Laboratoire PRISM (UMR 7061 &ndash; France). The copyright applies to documents digitized by the PRISM laboratory</strong></p>

opencc-by-4.0Apr 2022View details →
zenodo36/100

Figure 1 from: Keller D., Radivojević N., Lazzarini V. (2022). Issues in ubimus archaeology: Beyond pure computing and precision during the analogue-digital transition

<p><strong>Figure 1. W20_003_2_P20</strong><br> <strong>Fonds Jean-Claude Risset, Laboratoire PRISM (UMR 7061 &ndash; France). The copyright applies to documents digitized by the PRISM laboratory</strong></p>

opencc-by-4.0Apr 2022View details →
dryad36/100

Data from: a physics-based digital twin for model predictive control of autonomous unmanned aerial vehicle landing

<p>This paper proposes a two-level, data-driven, digital twin concept for the autonomous landing of aircraft, under some assumptions. It features a digital twin instance for model predictive control; and an innovative, real-time, digital twin prototype for fluid-structure interaction and flight dynamics to inform it. The latter digital twin is based on the linearization about a pre-designed glideslope trajectory of a high-fidelity, viscous, nonlinear computational model for flight dynamics; and its projection onto a low-dimensional approximation subspace to achieve real-time performance, while maintaining accuracy. Its main purpose is to predict in real-time, during flight, the state of an aircraft and the aerodynamic forces and moments acting on it. Unlike static lookup tables or regression-based surrogate models based on steady-state wind tunnel data, the aforementioned real-time digital twin prototype allows the digital twin instance for model predictive control to be informed by a truly dynamic flight model, rather than a less accurate set of steady-state aerodynamic force and moment data points. The paper describes in detail the construction of the proposed two-level digital twin concept and its verification by numerical simulation. It also reports on its preliminary flight validation in autonomous mode for an off-the-shelf unmanned aerial vehicle instrumented at Stanford University.</p>

opencc-zeroMay 2022View details →
zenodo36/100

Synthesis of results in Digital Competence in before-after measures

<p>Synthesis of results in Digital Competence in before-after measures</p>

opencc-by-4.0May 2022View details →
zenodo36/100

Full-field displacements and strains obtained by digital image correlation during fatigue crack growth experiments

<p>This data publication contains&nbsp;full-field displacements and strains&nbsp;obtained by 3D digital image correlation (DIC)&nbsp;using a GOM Aramis 12M system including&nbsp;three fatigue crack propagation (fcp)&nbsp;experiments of AA2024-T3 aluminium sheet material.</p> <p>The repository consists of three datasets of different experiments named&nbsp;</p> <ul> <li>S<sub>950,1.6&nbsp;</sub>- MT950 specimen, 1.6 mm sheet thickness, load ratios R=0.3, 1.0</li> <li>S<sub>160,2.0&nbsp;</sub>-&nbsp;MT160 specimen, 2.0 mm sheet thickness, load ratios R=0.1, 0.25, 0.5, 0.75, 1.0</li> <li>S<sub>160,4.7&nbsp;</sub>- MT160 specimen, 4.7&nbsp;mm sheet thickness, load ratios R=0.1, 0.25, 0.5, 0.75, 1.0</li> </ul> <p>where S<sub>w,t</sub>&nbsp;denotes a middle tension (MT) specimen with width w and thickness t. The&nbsp;nodal DIC measurements at different times during the experiments are provided&nbsp;as&nbsp;.txt files we call <em>&quot;nodemaps&quot;&nbsp;</em>and stored in&nbsp;subfolders &quot;<strong>Nodemaps</strong>&quot;. Each <em>nodemap</em> consists of a header containing meta data information like a running number (current stage index)&nbsp;or the&nbsp;applied force, followed by the nodal displacements and strains in tabular form.&nbsp;Additionally, the dataset S<sub>160,4.7</sub>&nbsp;contains crack path and crack tip labels for each nodemap in the subfolder &quot;<strong>GroundTruth</strong>&quot;. The ground truth is provided as arrays of size 256x256. Each pixel of the array contains the label &quot;2&quot; for the class &quot;crack tip&quot;, &quot;1&quot; for the class &quot;crack path&quot;, or &quot;0&quot; for the class &quot;background&quot;.&nbsp;These labels were created in a semi-manual fashion and can be&nbsp;used for machine learned crack detection using supervised training.</p> <p>These datasets were recently&nbsp;used to evaluate neural attention of convolutional neural networks&nbsp;trained on fatigue crack tip detection&nbsp;in&nbsp;<a href="https://www.nature.com/articles/s41598-022-13275-1">Melching et al. (Sci Rep,&nbsp;2022)</a>. Additional guidance on data loading and usage can also be found at&nbsp;<a href="https://github.com/dlr-wf/explainable-crack-tip-detection">https://github.com/dlr-wf/explainable-crack-tip-detection</a>.</p> <p>The experiments S<sub>160,2.0</sub>&nbsp;and&nbsp;S<sub>160,4.7&nbsp;</sub>were conducted and analysed by <a href="https://doi.org/10.1111/ffe.13433">Strohmann et al. (FFEMS, 2021)</a>.</p> <p>The experiment&nbsp;S<sub>950,1.6</sub>&nbsp;was conducted and analysed by&nbsp;<a href="https://doi.org/10.1111/ffe.13335">Breitbarth et al. (FFEMS, 2020)</a>.</p>

opencc-by-nc-4.0May 2022View details →
zenodo36/100

Atividade de Restauração Digital

<p>Trabalho realizado para a disciplina de Tecnologia da Informa&ccedil;&atilde;o I, v&aacute;lido para o per&iacute;odo 2021.2, na Universidade Federal da Para&iacute;ba. Com o objetivo de realizar restaura&ccedil;&atilde;o de documentos.</p>

opencc-by-4.0May 2022View details →
zenodo36/100

Data set from "Absolute Treatment Effects for the Primary Outcome and All-cause Mortality in the Cardiovascular Outcome Trials of New Antidiabetic Drugs – A Meta-Analysis of Digitalized Individual Patient Data"

<p>This data set contains the complete digitalized individual patient data that are used in the manuscript &quot;Absolute Treatment Effects for the Primary Outcome and All-cause Mortality in the Cardiovascular Outcome Trials of New Antidiabetic Drugs &ndash; A Meta-Analysis of Digitalized Individual Patient Data&quot;, which is accepted from &quot;Acta Diabetologica&quot;.<br> The data file is in CSV format and contains the five variables &quot;OutcomeType&quot; (with values &quot;AllcauseMortality&quot; or &quot;PrimaryOutcome&quot;), &quot;Study&quot; (denoting the respective cardiovascular outcome trial), &quot;Treatment&quot; (denoting the respective study treatment or placebo), &quot;Event&quot; (denoting if the respective has been observed (Event=1) or not (Event=0)), and &quot;SurvivalTimeMonths&quot; (denoting the respective time to the event or censoring in months).</p>

opencc-by-4.0Jun 2022View details →
zenodo36/100

Digital elevation model of differences of two debris flow event in Chutou gully

<p>We release two datasets that reflected the height alteration of channel deposits during the debris flow events, which occurred on&nbsp;20 August 2019 and&nbsp;17 August 2020 in Chutou gully,&nbsp;Miansi Town, Wenchuan County, Sichuan Province, Southwestern China.&nbsp;The first dataset&nbsp;indicates the height alteration during the 2019 debris flow, whereas the second indicates the 2020 debris flow.&nbsp;The datasets&nbsp;can be used to analyse the deposit evolution during the debris flow events. The datasets can be viewed or edited through the ArcGIS software</p>

opencc-by-4.0Jun 2022View details →
zenodo36/100

African Red Slip Ware Digital (ARS3D) - Comparison Videos

<p>Characteristic of the North African bowls, plates, and jugs are their pictorial decorations applied mainly by appliqu&eacute;s and stamps. As mass-produced image carriers and everyday objects, the ARS spread throughout the empire.</p> <p>The range of motifs includes mythological scenes as well as scenes from the Old and New Testament, circus, arena and hunting scenes as well as fish and plant motifs. The appliqu&eacute;s-decorated pottery thus provides insights into Late Antique imagination and its changes, as well as into the economic history of the period between the 3rd and 5th centuries AD in North Africa.</p> <p>Previous documentation methods were not able to capture the objects and their decoration in an adequate way. The digital recording of the RGZM&#39;s collections by 3D scans allows to compare potentially identical appliqu&eacute;s and to assign them to their negative forms and the corresponding stamps.</p> <p>Whereas vessel curvature previously falsified the assignment of appliqu&eacute;s and models, 3D analysis and visualisation tools now allow a comparison . Metadata created for each object increases the effectiveness and accuracy of determining image context and content. Issues related to the production of the ARS and the process flows within the workshops can be investigated through the analysis of the 3D data.</p> <p>The developed ontology uses CIDOC CRM and various extensions. The data mainly consists of objects (E24), on which e.g. applications (features, E25) can be found. These objects can be described semantically, e.g. by the shape or time epoch. Features are described with observations, e.g. a human type man standing and wearing a beard. These observations lead to interpretations whose arguments can be observations.</p> <blockquote> <p>This repo contains exemplary cross-fade videos</p> <ul> <li>Part I: 83a33d18-660e-43b2-b0e2-2629e86f01fc.mp4&nbsp;&rarr; 42129 woman and boy 40531 woman and boy</li> <li>Part II: 06fbcba6-50e3-4675-9469-49375c085be6.mp4&nbsp;&rarr; 40534 human-horse hybrid 1 human-horse hybrid 2</li> <li>Part II: 682852d6-24c6-41f3-9eb1-774d723fc35f.mp4&nbsp;&rarr; 40761 bear 1 bear 2</li> </ul> </blockquote>

opencc-by-sa-4.0Jun 2022View details →
zenodo36/100

Digital Twin Technologies Towards Understanding the Interactions between Transportation and other Civil Infrastructure Systems: Traffic Sign and Day 1 Video

<p>This dataset contains three files. The first is raw video files collected from a GoPro camera that was dash mounted and driven around the UTEP campus. The telemetry from these files was extracted using the process outlined here (https://lucaselbert.medium.com/extracting-gopro-gps-and-other-telemetry-data-fadf97ed1834). The videos were manual evaluated to record the time in the video where a sign appeared, and the time stamp was noted. The Python file compared the timestamps from the manual file and the GoPro telemetry to create a combined data set for each route driven that includes the type of sign and the location. This data is in the Microsoft Excel file.</p> <p>&nbsp;</p> <p>Note that this data set is split into two because of the size of the videos. This is the video data from day 1 of 2 of data collection.</p>

opencc-by-4.0Jun 2022View details →
zenodo36/100

Digital Twin Technologies Towards Understanding the Interactions between Transportation and other Civil Infrastructure Systems: Traffic Sign and Day 2 Video

<p>This dataset contains three files. The first is raw video files collected from a GoPro camera that was dash mounted and driven around the UTEP campus. The telemetry from these files was extracted using the process outlined here (https://lucaselbert.medium.com/extracting-gopro-gps-and-other-telemetry-data-fadf97ed1834). The videos were manual evaluated to record the time in the video where a sign appeared, and the time stamp was noted. The Python file compared the timestamps from the manual file and the GoPro telemetry to create a combined data set for each route driven that includes the type of sign and the location. This data is in the Microsoft Excel file.</p> <p>&nbsp;</p> <p>Note that this data set is split into two because of the size of the videos. This is the video data from day 2 of 2 of data collection.</p>

opencc-by-4.0Jun 2022View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

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Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.