Skip to main content
Powered by ShareScore

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.

27

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

27 results for “Design and Data Analysis”

Learn how ShareScore rates datasets ↗
zenodo40/100

Doctoral Thesis Artifact "User-Centered Tool Design for Data-Flow Analysis"

<p>This artifact contains the evaluation data and source code accompanying the doctoral thesis &quot;User-Centered Tool Design for Data-Flow Analysis&quot; by Lisa Nguyen Quang Do. The artifact contains (1) the survey questions and anonymized answers of the surveys conducted during the thesis, (2) the user study questionnaires, results, and test applications of the user studies conducted for the thesis, (3) the source code of the research prototypes and video demonstrations of their interfaces, and (4) the benchmark suites used for the empirical evaluation of those prototypes.</p>

opencc-by-4.0Jul 2019View details →
dryad40/100

Data from: Potentials of closed contour analysis in species differentiation and holotype designation: a case study on lower Norian (Upper Triassic) conodonts

<p><span>Geometric morphometric approaches become increasingly applied in the fields of biology and paleontology. Taxonomy is a good example, where a long-standing intention of scientists is to eliminate subjectivity as much as possible. In the case of biostratigraphically important conodont elements, the application of such methods is not widespread. Indeed, only a handful of studies attempted to deal with the morphological variance of conodont elements from this aspect. The detailed description of five lower Norian (Upper Triassic) taxa (<em>Ancyrogondolella quadrata, A. rigoi, A. triangularis, A. uniformis</em> and <em>Metapolygnathus mazzai</em>) is presented here based on landmarks and Fourier analysis of the P1 element and keel outlines. Both methods led to similar outcomes regarding taxonomic differentiation and exposing shape variability. Consensus shapes were generated to objectively reveal the typical contour shape of each taxon, which allowed their comparison with each other, and with the members of their respective sample population including the holotypes. The results pointed out that the holotype of a taxon is generally not an average representative, but rather a peripheral form with well-separable morphological characteristics. <em>Ancyrogondolella quadrata</em> and <em>A. rigoi</em> turned out to represent a morphological continuum with ample transitional forms between these two end-members that may cause bias in their biostratigraphic applicability; however, their combined shape variance seems to be too large for uniting them into a single species. Given the results that may be too subtle to realize based solely on qualitative observations, future taxonomic studies and type material designation could greatly benefit from the application of similar methodologies.</span></p>

opencc-zeroApr 2023View details →
zenodo40/100

Microscopy data for the paper: Analysis and design of single-cell experiments to harvest fluctuation information while rejecting measurement noise.

<p>Microscopy data for the paper: Analysis and design of single-cell experiments to harvest fluctuation information while rejecting measurement noise.</p> <p>&nbsp;</p> <p>List of files used for each dataset.</p> <p>&nbsp;</p> <p>Dataset 0 : MS2-CY5_Cyto543_560_woStim</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;Images in the dataset :</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001_XY1657814108_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;0</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI002_XY1657815441_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;1</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI003_XY1657814110_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;2</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI004_XY1657814111_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;3</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI005_XY1657814112_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;4</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI006_XY1657814113_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;5</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI007_XY1657814114_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;6</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI008_XY1657814115_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;7</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI009_XY1657814116_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;8</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI010_XY1657814117_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;9</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI011_XY1657814118_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;10</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI012_XY1657814119_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;11</p> <p>&nbsp;</p> <p>Datset 1 : MS2-CY5_Cyto543_560_18minTPL_5uM</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;Images in the dataset :</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 1_XY1657818948_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;0</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 2_XY1657818949_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;1</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 4_XY1657818951_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;2</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 5_XY1657818952_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;3</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 6_XY1657818953_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;4</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 7_XY1657818954_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;5</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 8_XY1657818955_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;6</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 9_XY1657818956_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;7</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 10_XY1657818957_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;8</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 11_XY1657818958_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;9</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001 - Position 12_XY1657818959_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;10</p> <p>&nbsp;</p> <p>Dataset 2: MS2-CY5_Cyto543_560_5hTPL_5uM</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;Images in the datset :</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI001_XY1657822809_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;0</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI002_XY1657822933_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;1</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI003_XY1657822934_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;2</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI005_XY1657822936_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;3</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI006_XY1657822937_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;4</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI007_XY1657822938_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;5</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI008_XY1657822939_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;6</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI010_XY1657822941_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;7</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI013_XY1657822944_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;8</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI014_XY1657822945_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;9</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI015_XY1657822946_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;10</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI016_XY1657822947_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;11</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI017_XY1657822948_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;12</p> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;ROI018_XY1657822949_Z00_T0_merged.tif &nbsp;&nbsp;- Image Id Number: &nbsp;13</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2023View details →
dryad40/100

Data from: Potentials of closed contour analysis in species differentiation and holotype designation: a case study on lower Norian (Upper Triassic) conodonts

Open the record for dataset details and reuse information.

publicApr 2023View details →
zenodo36/100

Informing antenna design for Global 21-cm experiments using a simulated Bayesian data analysis pipeline (supplementary data)

<p>These are the posterior files, foreground simulation data sets and chromaticity factor values used to produce the results for <a href="https://arxiv.org/abs/2106.10193">arXiv:2106.10193</a>.</p> <p>Plots of the fitted signal and residuals for each case are included, as is a plotting function to reproduce key figures.</p> <p>Naming conventions:</p> <ul> <li>f0: Centre frequency of the 21cm signal present in the simulated data</li> <li>A: Amplitude of the simulated 21cm signal present in the simulated data</li> <li>M_sig: Model being fit to the data includes a 21cm signal</li> <li>M_nosig: Model being fit to the data is a foreground only</li> </ul> <p>Software used:</p> <ul> <li><a href="https://github.com/PolyChord/PolyChordLite/tree/839292290a7747dbee82933bb9f7f955ac45c3ca">PolyChord</a></li> </ul> <p>&nbsp;</p>

opencc-by-4.0Apr 2021View details →
dryad36/100

Data and analysis scripts: Evidence supporting an evolutionary trade-off between material properties and architectural design in Anolis lizard long bones

<p>In biology, 'many-to-one mapping' occurs when multiple morphological forms can meet a particular functional demand. Knowledge of this mapping is crucial for understanding how selection on performance shapes the evolution of morphological diversity. Past research has focused primarily on the potential for geometrically alternative morphological designs to produce equivalent performance outcomes. Here we ask whether the material properties of biological tissues hold similar potential. Through phylogenetic comparative study of <em>Anolis</em> lizards, we show that the architectural design and mineral density of the femur trade off in a many-to-one functional system, yielding a morphospace featuring parallel isolines in size-relative bending strength. Anole femur evolution has largely tracked a narrow band of strength isolines over phylogenetic timescales, suggesting that geometry and mineral content shape the course of macroevolution through compensatory effects on performance. Despite this conserved evolutionary relationship, insular and continental species evolve strong bones differently, likely reflecting underlying ecological differences. Mainland anoles, which exhibit fast-paced life histories, typically have femora with lower mineralization and thinner walls than island species, which exhibit the opposite strategy. Together, our results reveal an overlooked dimension in the relationship between form and function, expanding our understanding of how many-to-one mapping can shape patterns of phenotypic diversity.</p>

opencc-zeroNov 2023View details →
zenodo36/100

Research Data Supporting "Coupling Lipid Nanoparticle Structure and Automated Single Particle Composition Analysis to Design Phospholipase Responsive Nanocarriers"

<p>Raw research data supporting Barriga, Pence, et al. 2022, Advanced Materials. <a href="https://doi.org/10.1002/adma.202200839">https://doi.org/10.1002/adma.202200839</a></p>

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

Developing Implementable Climatic Input Data and Moisture Boundary Conditions for Pavement Analysis and Design

<p>Corresponding data set for Tran-SET Project No. 18POKS03. Abstract of the final report is stated below for reference:</p> <p>&quot;The main objective of this study is to develop a practical and implementable numerical model for predicting the moisture (suction) regime within the pavement subgrade system. The research quality and uniformly-dispersed climate data over short distances from Oklahoma Mesonet and the Mitchell based moisture (suction) prediction methods establish the main background of the research study. &nbsp;The study involved numerical modeling and statistical analysis of climatic weather data. The proposed moisture variation model predicts the suction distribution throughout the soil subgrade by solving the diffusion equation and incorporates the measured suction from the Oklahoma Mesonet to estimate the diffusion coefficient. The research study resulted in a practical prediction model that could be used to determine the moisture boundary conditions within the pavement structure.&quot;</p>

opencc-by-4.0Jul 2019View details →
zenodo36/100

Data and data analysis for "Human Preferences for the Visual Appearance of Desks: Examining the Role of Wooden Materials and Desk Designs"

<p>Data and data analysis&nbsp;for the article &quot;Human Preferences for the Visual Appearance of Desks: Examining the Role of Wooden Materials and Desk Designs&quot;.</p>

opencc-by-4.0Jun 2023View details →
dryad36/100

Data from: Optimisation design and analysis of mobile pump truck frame using response surface methodology

<p><span>In order to realize the lightweight design of mobile pump truck, this paper takes the frame of a certain type of mobile pump truck as the research object. The response surface method is used to carry out lightweight design of the longitudinal beam structure of the frame, and the finite element method is used to establish the finite element model to analyze and compare the frame before and after optimization.The results show that the height, width and thickness of the optimized longitudinal beam section are reduced by 10 mm, 11 mm, and 0.8 mm respectively, and the weight of the whole frame is reduced by 35.8 kg.</span> <span>Before and after optimization, the displacement and stress changes of the frame are small in four motion situations, which meet the lightweight requirements of optimization design.</span></p>

opencc-zeroAug 2023View details →
dryad36/100

Data and analysis scripts: Evidence supporting an evolutionary trade-off between material properties and architectural design in Anolis lizard long bones

Open the record for dataset details and reuse information.

publicNov 2023View details →
dryad36/100

Data from: Optimisation design and analysis of mobile pump truck frame using response surface methodology

Open the record for dataset details and reuse information.

publicAug 2023View details →
zenodo32/100

Data accompanying the dissertation "Genre Analysis and Corpus Design: 19th Century Spanish American Novels (1830-1910)" (part of data-nh)

<p>This dataset includes research data that resulted from the analysis of the bibliography Bib-ACM&eacute; (see https://github.com/cligs/bibacme) and the corpus Conha19 (see https://github.com/cligs/conha19) as part of the work on the dissertation &quot;Genre Analysis and Corpus Design: 19th Century Spanish American Novels (1830-1910)&quot; by Ulrike Henny-Krahmer. Both the bibliography and the corpus include novels from Argentina, Cuba, and Mexico published between 1830 and 1910 which were analyzed by subgenre on the levels of metadata and text (see the dissertation for details).</p> <p>The dataset is part of &quot;data-nh&quot; (see https://github.com/cligs/data-nh), which is the whole collection of research data accompanying the above-mentioned dissertation.</p>

openother-pdJan 2021View details →
dryad32/100

Data from: Evaluating the interaction of faecal pellet deposition rates and DNA degradation rates to optimize sampling design for DNA-based mark-recapture analysis of Sonoran pronghorn

Knowledge of population demographics is important for species management but can be challenging in low-density, wide-ranging species. Population monitoring of the endangered Sonoran pronghorn (Antilocapra americana sonoriensis) is critical for assessing the success of recovery efforts, and noninvasive DNA sampling (NDS) could be more cost-effective and less intrusive than traditional methods. We evaluated faecal pellet deposition rates and faecal DNA degradation rates to maximize sampling efficiency for DNA-based mark–recapture analyses. Deposition data were collected at five watering holes using sampling intervals of 1–7 days and averaged one pellet pile per pronghorn per day. To evaluate nuclear DNA (nDNA) degradation, 20 faecal samples were exposed to local environmental conditions and sampled at eight time points from one to 124 days. Average amplification success rates for six nDNA microsatellite loci were 81% for samples on day one, 63% by day seven, 2% by day 14 and 0% by day 60. We evaluated the efficiency of different sampling intervals (1–10 days) by estimating the number of successful samples, success rate of individual identification and laboratory costs per successful sample. Cost per successful sample increased and success and efficiency declined as the sampling interval increased. Results indicate NDS of faecal pellets is a feasible method for individual identification, population estimation and demographic monitoring of Sonoran pronghorn. We recommend collecting samples &gt;7 days old and estimate that a sampling interval of 4–7 days in summer conditions (i.e. extreme heat and exposure to UV light) will achieve desired sample sizes for mark–recapture analysis while also maximizing efficiency.

opencc-zeroDec 2013View details →
zenodo32/100

Data for "Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection"

<p>Once decompressed, the file contains a folder which contains:</p> <ul> <li>The files &quot;s100_Nth.fasta&quot; (where &quot;N&quot; is 5, 6, 7 or 8), which are the output of the SELEX experiment described in the paper with DOI:&nbsp;<a href="https://doi.org/10.1002/cbic.201900265">10.1002/cbic.201900265</a>. They are standard fasta files, and the descriptor of each sequence is of the form &quot;seqX-Y&quot;, where &quot;X&quot;&nbsp;is an increasing label, and &quot;Y&quot; is the number of times &quot;seqX&quot;&nbsp;has been obtained (number of counts of &quot;seqX&quot;).</li> <li>The file &quot;Aptamer_Exp_Results.csv&quot;, which contains the sequences tested experimentally for the paper &quot;Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection&quot; (preprint available at https://doi.org/10.1101/2022.03.12.484094), with the following experimental results for each sequence: (i) whether the sequence was able to bind thrombin (&#39;B&#39; for binders, &#39;NB&#39; for non-binders); (ii) the thrombin exosite used for binding&nbsp;(&#39;I&#39; for exosite I, &#39;II&#39;&nbsp;for exosite II, &#39;n/a&#39; for sequences not tested).</li> </ul> <p>Examples of usage of the data are available at&nbsp;https://github.com/adigioacchino/RBMsForAptamers.</p>

opencc-by-4.0Mar 2022View details →
zenodo32/100

Data Set and Replication Package of Paper on Handling Environmental Uncertainty in Design Time Access Control Analysis

<p>Data set and replication package for Paper &quot;Handling Environmental Uncertainty in Design Time Access Control Analysis&quot;.</p> <p>The data set contains an overview of used case studies, with illustrations and descriptions.</p> <p>The replication package contains the implemented application&nbsp;as well as model instances of every case study used for the evaluation.</p>

opencc-by-4.0Mar 2022View details →
zenodo32/100

Source data for "Design and construction of a microfluidics workstation for high-throughput multi-wavelength fluorescence and transmittance activated droplet analysis and sorting".

<p>Contains numeric data for figures 16-18 and supplementary fig 6&nbsp;linked with the publication:&nbsp;Panwar, J., Autour, A. &amp; Merten, C.A. Design and construction of a microfluidics workstation for high-throughput multi-wavelength fluorescence and transmittance activated droplet analysis and sorting.&nbsp;<em>Nat Protoc</em>&nbsp;(2023).&nbsp;<a href="https://doi.org/10.1038/s41596-022-00796-2">https://doi.org/10.1038/s41596-022-00796-2</a></p>

opencc-by-4.0Jan 2023View details →
zenodo32/100

Data for publication - Design, simulation and experimental analysis of a monolithic bending section for enhanced maneuverability of single use laparoscopic devices

<p>The dataset contains all processed data and raw data which are used for the publication &quot;<em>Design, simulation and experimental analysis of a monolithic bending section for enhanced maneuverability of single use laparoscopic devices</em>&quot;</p>

opencc-by-4.0May 2023View details →
dryad32/100

Data from: Evaluating the interaction of faecal pellet deposition rates and DNA degradation rates to optimize sampling design for DNA-based mark-recapture analysis of Sonoran pronghorn

Open the record for dataset details and reuse information.

publicDec 2014View details →
zenodo24/100

Data analysis on the design requirements of the app for communication bridging as part of Co-design Activity 1

<p>This dataset includes the analyses of the participants&#39; statements and drawing toward the design requirements of the app for communication bridging.</p>

opencc-by-4.0Oct 2020View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

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

ScienceDex for faculty

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.