Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
54
datasets available to search
ShareScore release 0.9.0
Dataset results
54 results for “computational humanities”
Vax Facts Human Papillomavirus (HPV): Study of a Computer-based Tailoring System and Mothers' Intentions to Vaccinate Their Daughters Against HPV
ClinicalTrials.gov study NCT01143142. IPD Sharing: Not stated. Countries: 1. Publications: 8.
Computationally defined and in vitro validated putative genomic safe harbour loci for transgene expression in human cells
Open the record for dataset details and reuse information.
Banking dataset used for cloud computing and comparison with Human
<p>Banking dataset used for cloud computing </p>
Multiplicity of human scent signature: Confirmation by computer-based olfactronics
<p>Data from GCxGC-MS chromatography processed by ChromaTOF </p>
3d virtual histology of the human hippocampus based on phase-contrast computed-tomography
<p>This data package contains:<br> - exemplary data sets of multiscale imaging of the human hippocampus as raw-files (gray values, segmentation masks)<br> - object properties as xlsx-files (for all data sets)<br> - analysis scripts (based on matlab, R, python)</p>
Osteolitic vs Osteoblastic metastatic lesion: Computational modeling of fracture risk in the human vertebra after screws fixation procedure
<p>Metastatic lesions compromise the mechanical integrity of vertebrae, increasing the fracture risk. Screwfixation is usually performed to guarantee spinal stability and prevent dramatic fracture events. Accordingly, predicting the overall mechanical response in such conditions is critical to planning and optimizing the surgical treatment. This work proposes an image-basedfinite element computational approach describing the mechanical behavior of a patient-specific instrumented metastatic vertebra by assessing the effect of lesion size, location, type and shape on the fracture load and fracture patterns under physiological loading conditions. A specific constitutive model for the metastasis is integrated to account for the effect of the diseased tissue on the bone material properties. Computational results demonstrate that size, location, and type of metastasis significantly affect the overall vertebral mechanical response, and suggest better account these parameters in estimating the fracture risk. Combining multiple osteolytic lesions to account for irregular shape of the overall metastatic tissue has a not significant effect on fracture load of vertebra macroscopically. In addition, the combination of loading mode and metastasis type is shown for the first time as a critical modeling parameter in determining the fracture risk. The proposed computational approach moves towards defining a clinically integrated tool to improve the management of metastatic vertebrae and quantitatively evaluate fracture risk.</p>
Pre-computed MGCs from human microbiome reference genomes
<p>This dataset contains non-redundant metabolic gene clusters (MGCs) collected by running gutSMASH and BiG-MAP on a collection of unique high-quality reference genomes. This collection consist of MGCs predicted by gutSMASH using 1,520 genomes from the Culturable Genome Reference (CGR), 2,308 genomes from the Human Microbiome Project (HMP) and 414 Clostridia genomes as input and then filtered for redundancy using the family module of BiG-MAP. For more information: <a href="http://doi.org/10.1101/2021.02.25.432841">https://doi.org/10.1101/2021.02.25.432841</a></p> <p><strong>BiG-MAP_mg.pickle</strong> -> suitable for <strong>metagenome</strong> analyses</p> <p><strong>BiG-MAP_mt.pickle </strong>-> suitable for <strong>metatranscriptome </strong>analyses</p> <p>The files can be used as direct input in the third module of BiG-MAP (BiG-MAP.map.py: <a href="https://github.com/medema-group/BiG-MAP">https://github.com/medema-group/BiG-MAP</a>).</p>
Supplementary Materials for Discovery of Hub Genes and Construction of Competitive Endogenous RNA Network in Human Cytomegalovirus Infection Using Computational and Bioinformatics Tools
<p><span>Table S1: List of targeted genes by 41 differentially expressed microRNAs (DEMs) agreed in Targetscan and miRDB; Table S2: Significant biological process (BP) of 144 genes associated with Human Cytomegalovirus (HCMV); Table S3: Significant cellular components (CC) of 144 genes associated with HCMV; Table S4: Enriched molecular function (MF) of 144 genes associated with HCMV; Table S5: Pathways significantly affected by 144 genes in HCMV; Figure S1: Number of interactions for each gene in protein-protein interaction (PPI) network.</span></p>
Mental comparison of 3D objects is based on 2D optical flow computations: human data
<p>Human behavioural data for manuscript:</p> <p><strong>Mental comparison of 3D objects is based on 2D optical flow computations.</strong></p>
Computational Neuroscience of Language Processing in the Human Brain
ClinicalTrials.gov study NCT05222594. IPD Sharing: NO. Countries: 1. Publications: 14.
Human Versus Computer-based Predictions of Long Allograft Survival
ClinicalTrials.gov study NCT04918199. IPD Sharing: NO. Countries: 1. Publications: 1.
Photoacoustic tomography versus cone-beam computed tomography versus micro-computed tomography: Accuracy of 3D reconstructions of human teeth
Open the record for dataset details and reuse information.
Data from: A collection of non-human primate computed tomography scans housed in MorphoSource, a repository for 3D data
Open the record for dataset details and reuse information.
Die Rolle von Mensch und Computer in den Digital Humanities
<p>The video shows the closing keynote by Daniel A. Keim from the Universität Konstanz and the closing of the DHd 2016 conference.</p> <p>The programme of the closing is available <a href="http://dhd2016.de/?q=Abschluss">here</a>.</p>
Data from: Investigating human repeatability of a computer vision based task to identify meristems on a potato plant (Solanum tuberosum)
<p>Labelled training data in artificial intelligence (AI) is used to teach so-called 'supervised learning models'. However, such data may contain error or bias, which can impact model prediction accuracy. Thus, obtaining accurate training data is of high importance. In applications of AI, such as in classification and detection problems, raw training data is not always made available in published research. Likewise, the process of obtaining labelled data is not always documented well enough to enable reproducibility. This training data set captures a repeatability exercise in AI training data collection for a task that is difficult for humans to perform, delineating a bounding box in a two-dimensional image of a growing apical meristem in potato plants.</p>
NOVA: Rendering Virtual Worlds with Humans for Computer Vision Tasks
<p>Today, the cutting edge of computer vision research greatly depends on the availability of large datasets, which are critical for effectively training and testing new methods. Manually annotating visual data, however, is not only a labor-intensive process but also prone to errors. In this study, we present NOVA, a versatile framework to create realistic-looking 3D rendered worlds containing procedurally generated humans with rich pixel-level ground truth annotations. NOVA can simulate various environmental factors such as weather conditions or different times of day, and bring an exceptionally diverse set of humans to life, each having a distinct body shape, gender and age. To demonstrate NOVA's capabilities, we generate two synthetic datasets for person tracking. The first one includes 108 sequences, each with different levels of difficulty like tracking in crowded scenes or at nighttime and aims for testing the limits of current state-of-the-art trackers. A second dataset of 97 sequences with normal weather conditions is used to show how our synthetic sequences can be utilized to train and boost the performance of deep-learning based trackers. Our results indicate that the synthetic data generated by NOVA represents a good proxy of the real-world and can be exploited for computer vision tasks.</p>
Computational modeling of human multisensory spatial representation by a neural architecture
<p>Architecture and processed dataset used to train it, referring to the manuscript:</p> <p>Computational modeling of human multisensory spatial representation by a neural architecture</p>
Data from: Investigating human repeatability of a computer vision based task to identify meristems on a potato plant (Solanum tuberosum)
Open the record for dataset details and reuse information.
Data from: Adaptive multi-degree of freedom Brain Computer Interface using online feedback: Towards novel methods and metrics of mutual adaptation between humans and machines for BCI.
Open the record for dataset details and reuse information.
Data from: Comparative finite-element analysis: a single computational modeling method can reliably estimate the mechanical properties of porcine and human vertebrae
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
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.
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.
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.
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.