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.
644
datasets available to search
ShareScore release 0.9.0
Dataset results
644 results for “Data Visualization”
Data for: Exploring Emerging Social Media: Acquiring, Processing, and Visualizing Data with Python and OSoMe Web Tools
<p>Data collected from Bluesky and Mastodon via streaming covering the period between 2024-06-25 and 2024-07-02. Entries contains any the of following terms: biden, trump, or debate. Data also contains embedding precalculated for each dataset. The data also contains embeddings pre calculcated for the datasets.</p>
Distance sampling visual observation sightings data for cetaceans from Antarctic Tourist vesssels
<p>The following is two summer sampling seasons of distance sampling data collected by trained observer teams of two from Antarctic tourist vessels. The data set contains 5 key dataframes. This data has be cleaned and quality controlled. </p> <p>Effort - details the type of visual observation effort, the observer on effort and other information </p> <p>Environment - details the environmental conditions under which the data were collected. </p> <p>Sightings - details the observations made, and distance estiamtes (relative to the ship) for cetceans. </p> <p>Resightings - used in select cases, see protocols.</p> <p>gpsData - automated collection of location data at 5 sec intervals, some gaps exists, which were interpolated later for analysis</p> <p>Work is ongoing with the dataset, please contact authors about its use. </p>
Data file for paper: Javier Rubio-Garcia; Anthony R J Kucernak, and Alexandra Charleson, "Direct visualization of reactant transport in forced convection electrochemical cells and its application to Redox Flow Batteries, Electrochemistry Communications, 2018
<p>Excel Data file containing the data presented in the figures of the paper:</p> <p>Javier Rubio-Garcia; Anthony R J Kucernak, and Alexandra Charleson, "Direct visualization of reactant transport in forced convection electrochemical cells and its application to Redox Flow Batteries</p> <p>Electrochemistry Communications, 2018,</p> <p>DOI:10.1016/j.elecom.2018.07.002</p> <p>Please cite the above reference if you wish to use this data</p>
Discovering and explaining the learning process of neural networks: A study on EEG data. The animated visualizations.
<p>In the paper 'Discovering and explaining the learning process of neural networks: A study on EEG data' frames of animated visualizations are presented. Here, the full animations are made available so they can be used for interpretation.</p>
data and appendix for paper "From Analytical Purposes to Data Visualizations: A Decision Process Guided by a Conceptual Framework and Eye Tracking"
<p>the folder contains the following:</p> <p>1. Data from the pre-experiment questionnaire provided to the participants (pre-experiment_data.xlsx)</p> <p>2. Questions and answer data (answers_accuracy.xlsx)</p> <p>3. Online figures appendix (figures.pdf)</p>
Supporting data (pre-processed) for: "Frequency-tagged visual evoked responses track syllable effects in visual word recognition"
<p>Pre-processed data. </p> <p>Data were re-referenced off-line to the average of left and right mastoid electrodes, bandpass filtered from 5 to 100 Hz (4th order Butterworth filter) and then segmented to include 200 ms before and 2000 ms after stimulus onset. Epoched data were normalized based on a prestimulus period of 200 ms, and then evaluated according to a sample-by-sample procedure to remove noisy sensors that were replaced using spherical splines. Additionally, EEG epochs that contained data samples exceeding threshold (100 uV) were excluded on a sensor-by-sensor basis, including horizontal and vertical eye channels</p> <p>The original data:<br> Montani, Veronica. (2019). Supporting data for: "Frequency-tagged visual evoked responses track syllable effects in visual word recognition" [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3260451</p>
TMS abolishes visual learning: Data and code
<p>Data and code for paper titled "Post-training TMS abolishes performance improvement and releases future learning from interference" by Bang, Milton, Sasaki, Watanabe, & Rahnev.</p>
Manuscript data for "Iroki: automatic customization and visualization of phylogenetic trees"
<p>Manuscript data for "Iroki: automatic customization and visualization of phylogenetic trees"</p>
Data and Analysis Scripts for Generation (Not Production) Improves the Fidelity of Visual Representations in Picture Naming
<p>Data and Analysis Scripts for Generation (Not Production) Improves the Fidelity of Visual Representations in Picture Naming</p>
1906 Data: Visualization as defamiliarization
Open the record for dataset details and reuse information.
Source code for CPBS Report 23UNM03 - Enhancing Collaboration through Web-based Visualization and Analysis of Traffic Crash Data
<p>Python source code for the crash mapping web application.</p>
Data from: Visual environment, attention allocation, and learning in young children: when too much of a good thing may be bad
A large body of evidence supports the importance of focused attention for encoding and task performance. Yet young children with immature regulation of focused attention are often placed in elementary-school classrooms containing many displays that are not relevant to ongoing instruction. We investigated whether such displays can affect children's ability to maintain focused attention during instruction and to learn the lesson content. We placed kindergarten children in a laboratory classroom for six introductory science lessons, and we experimentally manipulated the visual environment in the classroom. Children were more distracted by the visual environment, spent more time off task, and demonstrated smaller learning gains when the walls were highly decorated than when the decorations were removed.
Data from: Inhibition decorrelates visual feature representations in the inner retina
The retina extracts visual features for transmission to the brain. Different types of bipolar cell split the photoreceptor input into parallel channels and provide the excitatory drive for downstream visual circuits. Mouse bipolar cell types have been described at great anatomical and genetic detail, but a similarly deep understanding of their functional diversity is lacking. Here, by imaging light-driven glutamate release from more than 13,000 bipolar cell axon terminals in the intact retina, we show that bipolar cell functional diversity is generated by the interplay of dendritic excitatory inputs and axonal inhibitory inputs. The resulting centre and surround components of bipolar cell receptive fields interact to decorrelate bipolar cell output in the spatial and temporal domains. Our findings highlight the importance of inhibitory circuits in generating functionally diverse excitatory pathways and suggest that decorrelation of parallel visual pathways begins as early as the second synapse of the mouse visual system.
Data from Schmitt et al. 2021: Preattentive processing of visually guided self-motion in humans and monkeys. Progress in Neurobiology
<p><strong>Dataset associated with the following publication:</strong></p> <p>Constanze Schmitt, Jakob C.B. Schwenk, Adrian Schütz, Jan Churan, André Kaminiarz, Frank Bremmer.<br> Preattentive processing of visually guided self-motion in humans and monkeys. Progress in Neurobiology,<br> 2021,102117. https://doi.org/10.1016/j.pneurobio.2021.102117. Published 2021 July 2.</p> <p><strong>Description of dataset:</strong></p> <p>In our study we presented an optic flow stimulus simulating forward self-motion across a ground plane in an oddball EEG paradigm to 12 human participants and 2 macaque monkeys. We simulated two different headings (forward-left vs. forward-right) presented either as standard or deviant trials and tested for the occurrence of a visual mismatch negativity (vMMN) by comparing the visual-evoked potentials (VEPs). </p> <p>Human data:</p> <p>The dataset contains the preprocessed VEPs of all 12 human participants already averaged over all trials per participant. It contains data from all electrodes used for analysis (P1, P2, O1, O2, PO3, PO4, CP1, CP2) divided into data recordings in standard ('_std') or deviant ('_odd') trials. Each of these files consists of four subfiles representing the presented combinations of heading (forward to the right: '_r' or forward to the left: '_l') and attention condition (attention towards fixation target: 'fix' or attention towards the ground plane: 'plane'). The data matrices in these subfiles are sorted as [participants x time-points].</p> <p>Monkey data:</p> <p>Each .mat file contains the preprocessed VEPs from one monkey ('data'), the corresponding electrode labels ('elec') and the common time vector in seconds ('time'). The data struct contains VEPs for left- and rightwards heading in separate subfields, which again contain standard ('stan') and deviant ('odd') presentations of that heading. Within each subcondition, the actual data matrices are sorted as [electrodes x time-points x trials]. Here, the numbering of electrodes corresponds to the electrode labels contained in the 'elec' variable.</p>
Data from: How biological attention mechanisms improve task performance in a large-scale visual system model
How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude observed experimentally. We find that, at earlier layers, attention applied according to tuning does not successfully propagate through the network, and has a weaker impact on performance than attention applied according to values computed for optimally modulating higher areas. This raises the question of whether biological attention might be applied at least in part to optimize function rather than strictly according to tuning. We suggest a simple experiment to distinguish these alternatives.
Data for: A test of Sensory Drive in plant-pollinator interactions: habitat heterogeneity shapes pollinator preference for a floral visual signal
<p>DATA:</p> <p>FinnKoski_PollData_Final: Pollinator visitation data to floral arrays analyzed</p> <p>Spectra used for vismodels.zip: reflectance spectra of flowers and floral backgrounds, irradiance spectra</p> <p>ColorContrastData: visual contrast data analyzed</p> <p>CODE: </p> <p>vismod_code.R : code used for visual system modeling and calculation of contrast</p> <p>SAS_modelcode.R: SAS code used to analyze pollinator visitation data and color contrast data</p>
Data related to the manuscript "Visualizing endogenous Rho activity with an improved localization-based, genetically encoded biosensor"
<p>These are the data that are related to the manuscript "Visualizing endogenous Rho activity with an improved localization-based, genetically encoded biosensor" by </p> <p>Eike K. Mahlandt<sup>1,*</sup>, Janine J. G. Arts<sup>1,2</sup>,Werner J. van der Meer<sup>1</sup>, Franka H. van der Linden<sup>1</sup>, Simon Tol<sup>2</sup>, Jaap D. van Buul<sup>1,2</sup>, Theodorus W. J. Gadella Jr.<sup>1</sup>, Joachim Goedhart<sup>1,*</sup></p> <p><sup>1</sup> Swammerdam Institute for Life Sciences, Section of Molecular Cytology, van Leeuwenhoek Centre for Advanced Microscopy, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands</p> <p><sup>2</sup> Molecular Cell Biology Lab at Dept. Molecular Hematology, Sanquin Research and Landsteiner Laboratory, Amsterdam, The Netherlands</p>
DrAsync: Identifying and Visualizing Anti-Patterns inAsynchronous JavaScript [Anonymous Experimental Data]
<p>////////////////////////////////////<br> //</p> <p>This directory contains the raw data used to compute aggregate numbers in the paper.<br> There are five files, and 2 subdirectories:</p> <p>(1) apply_run_times: has the raw execution times of various calls to apply throughout vuepress' tests;</p> <p>(2) cpdir_run_times: has the raw execution times of calling cpDir on a large directory as part of the cpDir case study;</p> <p>(3) eleventy_test_executions: contains 50 run times x 2 (before, after refactoring) for eleventy's test suite;</p> <p>(4) promise_resolve_then_case_study: contains execution times for the code fragment from strapi's evaluate function;</p> <p>(5) vuepress_test_executions: contains 50 run times x 2 (before, after refactoring) for vuepress' test suite.</p> <p>For the subdirectories:</p> <p>(1) DynamicAndExecutedAntiPatterns: for each of 20 subject applications x for each of 8 anti-patterns, contains the number<br> of static occurences of anti-patterns which are executed, as well as how often.</p> <p>(2) StaticAntiPatterns: for each of 20 subject applications x for each of 8 anti-patterns, contains the number of static<br> occurrences of the anti-pattern. We further filtered this by discounting anti-patterns appearing<br> in test, generated, build, etc. directories with a separate command.</p> <p>////////////////////////////////////<br> //</p> <p>CodeQL queries for the anti-patterns are given in supplemental material (available on the submission form). <br> We will make the code for the visualization tool available as part of the artifact submission process if this paper is accepted.</p>
Integration-based Extraction and Visualization of Jet Stream Cores - Demo Data
<p>Demo data for the publication "Integration-based Extraction and Visualization of Jet Stream Cores", containing the meteorological attirbutes for September 01, 2016 at 00:00. The data is derived from ERA5.</p> <p>The ERA5 data is courtesy of the European Centre for Medium-Range Weather Forecasts (ECMWF) and is documented here: <a href="https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation">https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation</a> The data is available under the Copernicus License Agreement: <a href="https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf">https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf</a></p>
Structural control within flawed rock specimens under external loading as visualized through repeating nucleation on multiple sites by acoustic emission (AE) [DATA]
<p>Data for article: Structural control within flawed rock specimens under external loading as visualized through repeating nucleation on multiple sites by acoustic emission (AE).</p>
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.