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363 results for “stack”
theoretical and experimental study of the deposition of dielectric stacks on twin-hole silica fibers for implementation of compact all-fiber resonators
<p>This dataset includes the Matlab code to engineer theoretically a Bragg stack made of different dielectric layers. By changing the number of alternating stacks, their thickness and the refractive index of each layer it is possible to obtain the transmission curve of the Bragg stack versus the wavelength of the light in a certain range of values. The dataset includes also the experimental measurements of the resonances related to one of the fabricated compact resonators (based on the twin-hole fiber not poled) and obtained sweeping the wavelength of the input light injected through one of the two Bragg stacks and collecting the power at the exit of the other Bragg stack. </p>
Perceptions on the utility of community question and answer websites like Stack Overflow to software developers (Replication package)
<p>Interview Questions on the perception of the utility of CQAs like Stack Overflow to software developers. In this study, we focused on the questions highlighted in yellow.</p>
Usage and Attribution of Stack Overflow Code Snippets in GitHub Projects — Supplementary Material
<p><em>Background:</em> Stack Overflow (SO) is the largest Q&A website for software developers, providing a huge amount of copyable code snippets. Using those snippets raises various maintenance and legal issues. SO’s license (CC BY-SA 3.0) requires attribution, i.e., referencing the original question or answer, and requires derived work to adopt a compatible license. While there is a heated debate on SO’s license model for code snippets and the required attribution, little is known about the extent to which snippets are copied from SO without proper attribution.</p> <p><em>Aim:</em> Our main goal was to analyze how often code from SO posts is used in public GitHub projects, but not attributed as required by the license. Further, we wanted to investigate if developers are aware of SO’s license and its implications, and to what degree they adhere to the attribution requirements defined in SO’s terms of service.</p> <p><em>Method:</em> We present results of a large-scale empirical study analyzing the usage and attribution of non-trivial Java code snippets from SO answers in public GitHub projects. We followed three different approaches to triangulate an estimate for the ratio of unattributed usages and conducted two online surveys with software developers to complement our results.</p> <p><em>Results:</em> For the different sets of projects that we analyzed, the amount of projects containing files with a reference to SO varied between 3.3% and 11.9%. We found that at most 1.8% of all analyzed repositories containing code from SO used the code in a way compatible with CC BY-SA 3.0. Moreover, we estimate that at most a quarter of the copied code snippets from SO are attributed as required, i.e., using a link in a source code comment. About half of the surveyed developers admitted copying code from SO without attribution. Furthermore, about two thirds of them were not aware of the license of SO code snippets and its implications.</p>
InSAR stack of the 2019 Ridgecrest, California earthquake sequence from Sentinel-1 descending track 71 processed with ASF HyP3
<p>A stack of unwrapped interferograms on Owens Valley, California for the <a href="https://earthquake.usgs.gov/earthquakes/eventpage/ci38457511/executive">2019 Ridgecrest earthquake sequence</a>.</p> <p>Sensor: Sentinel-1 descending track 71</p> <p>Time: 2019.06.10 - 2019.08.15, 7 acquisitions, 11 interferograms</p> <p>Processor: <a href="https://hyp3-docs.asf.alaska.edu/guides/insar_product_guide/">ASF HyP3</a> (GAMMA)</p> <p>Tropospheric delay estimated from ERA-5 using PyAPS is attached.</p> <p>This is an input dataset for the time series analysis with <a href="https://github.com/insarlab/MintPy">MintPy</a>.</p>
Room Temperature NIR Phosphorescence from C64 Nanographene Tetraimide by π-Stacking Complexation with Pt(II)Porphyrin
<p>Additional data to report <a href="https://doi.org/10.1002/anie.202406353">https://doi.org/10.1002/anie.202406353</a>:</p> <p>Near Infrared (NIR) phosphorescence at room temperature is challenging to achieve for organic molecules due to a negligible spin-orbit coupling and a low energy gap leading to fast non-radiative transitions. Here, we show a supramolecular host–guest strategy to harvest the energy from the low-lying triplet state of C<sub>64</sub> nanographene tetraimide <strong>1</strong>. <sup>1</sup>H NMR and X-ray analysis confirmed the 1:2 stoichiometric binding of a Pt(II)porphyrin on the two π-surfaces of <strong>1</strong>. While the free <strong>1</strong> does not show emission in the NIR, the host–guest complex solution shows NIR phosphorescence at 77 K. Further, between 860–1100 nm room temperature NIR phosphorescence (<em>λ</em><sub>max</sub> = 900 nm, <em>τ</em><sub>avg</sub> = 142 µs) was observed for a solid-state sample drop-casted from a preformed complex in solution. Theoretical calculations reveal a non-zero spin-orbit coupling between isoenergetic S<sub>1</sub> and T<sub>3 </sub>of π-stacked [<strong>1</strong>·Pt(II)porphyrin] complex. External heavy atom induced spin-orbit coupling along with rigidification and protection from oxygen in the solid state promotes both the intersystem crossing from the first excited singlet state into the triplet manifold and the NIR phosphorescence from the lowest triplet state of <strong>1</strong>.</p>
BRAIN Journal-About the Design of QUIC Firefox Transport Protocol-Figure 1. TLS vs QUIC protocol stack
<p>QUIC addresses many network problems such as the Head Of Line (HOL) blocking as well as the TCP reconnection over a subnet/network change. In addition, QUIC has many features such as connection IDs, which can overcome the challenge of changing networks. In this way, if someone switches from a WIFI network to a cellular network, the connection to the server will not be broken or lost. Paper (Langley and Chang, 2016) described the QUIC crypto protocol, representing the part of QUIC that provides transport security to a connection. The QUIC crypto protocol is now replaced by TLS 1.3. Currently, QUIC provides security of TLS 1.3 (in an experimental stage), considered the highest security standards for the communication protocols (Valsorda; 2016). </p> <p>Figure 1 describes the TLS vs. QUIC protocol user level stack in the context of application layer and transport layer.</p>
SOTorrent: Reconstructing and Analyzing the Evolution of Stack Overflow Posts — Supplementary Material
<p>Stack Overflow is the most popular question-and-answer website for software developers, providing a large amount of code snippets and free-form text on a wide variety of topics. Like other software artifacts, questions and answers on Stack Overflow evolve over time, for example when bugs in code snippets are fixed, code is updated to work with a more recent library version, or text surrounding a code snippet is edited for clarity. To be able to analyze how content on Stack Overflow evolves, we built <em>SOTorrent</em>, an open dataset based on the official Stack Exchange data dump. <em>SOTorrent </em>provides access to the version history of Stack Overflow content at the level of whole posts and individual text or code blocks.</p> <p>This dataset has been retrieved from <em>SOTorrent </em>using the following scripts:</p> <p><a href="https://doi.org/10.5281/zenodo.1201679">https://doi.org/10.5281/zenodo.1201679</a></p> <p>For the MSR 2018 paper about SOTorrent, we used the following scripts to analyze the data:</p> <p><a href="https://doi.org/10.5281/zenodo.1201706">https://doi.org/10.5281/zenodo.1201706</a></p> <p>The files <em>sample_before_10.ods</em> and <em>sample_after_10.ods</em> contain our qualitative analysis of 50 comments that were made up to 10 minutes before/after an edit.</p>
Herschel‐ATLAS/GAMA: a census of dust in optically selected galaxies from stacking at submillimetre wavelengths
<p> </p> <p>Stacked sub-millimetre fluxes, luminosities, and derived dust masses and temperatures for GAMA galaxies...</p> <ul> <li>as a function of stellar mass, optical colour and redshift: StackResults_g-r_Mstar</li> <li>as a function of r-band absolute magnitude, optical colour and redshift: StackResults_g-r_Mr</li> </ul> <p>See readme files for full details.</p>
Recognising innovative companies by using a diversified stacked generalisation method for website classification – the raw results
<p><strong>Introduction</strong></p> <p>The classification models were trained out by using the Classification and Regression Training package (caret) [1]. The models' parameters were fine-tuned by the 10-fold cross-validation procedure [2].</p> <p><strong>Cluster parameters</strong></p> <p>Most computations were carried out on a cluster having the following parameters:</p> <ul> <li>GPU: NVIDIA Tesla P100;</li> <li>CPU: 2.0 GHz Intel® Xeon® Platinum 8167M;</li> <li>The number of GPUs: 2;</li> <li>The number of CPU cores: 28;</li> <li>The number of CPU threads: 56;</li> <li>RAM: 192 GB;</li> <li>Storage: 3 TB.</li> </ul> <p>Only one model (k-nn) was calculated on a cluster having the following parameters:</p> <ul> <li>Processor: Intel(R) Core(TM) i7-4770 CPU @ 3.40GHz 3.40 GHz;</li> <li>RAM: 16 GB;</li> <li>Windows 64 bit.</li> </ul> <p><strong>Performance statistics</strong></p> <p>All performance statistics are stored in cvs files. Each file corresponds to a particular machine learning method such as a file, "methodName-stat.csv" contains all data regarding a method, "methodName." All files cover the following columns:</p> <ul> <li><em>dataSetName – </em>a name of a data set on which evaluation was carried out; there are three possible values: (i) <em>firstPages</em> refers to the first data set (<em>L<sub>D</sub></em>) that contains textual description of a company; (ii) <em>firstPageLabels</em> refers to the second data set (<em>L<sub>L</sub></em>) that involves link labels that were extracted from an index page; (iii) <em>aggregateDocument</em> refers to the third data set (<em>L<sub>B</sub></em>) that consists of a so-called big document;</li> <li><em>fmeasure</em> - the number of features that were taken into account during evaluation;</li> <li><em>method</em> - the name of function in the caret package;</li> <li><em>parameters</em> - the values of parameters received from a tuning phase of a given classification method;</li> <li><em>precision </em>– the value of method’s precision;</li> <li><em>recall </em>– the value of method’s recall;</li> <li><em>fmeasure</em> - the value of method’s F-measure; </li> <li><em>error</em> - the value of method’s error;</li> <li><em>acc </em>– the value of method’s.</li> </ul> <p><strong>Time processing statistics</strong></p> <p>All time processing statistics, like the performance statistics, are stored in cvs files. Each file corresponds to a particular machine learning method such as a file, "methodName-time.csv". All files cover the following columns:</p> <ul> <li><em>dataSetName – </em>a name of a data set on which evaluation was carried out; there are three possible values: (i) <em>firstPages</em> refers to the first data set (<em>L<sub>D</sub></em>) that contains textual description of a company; (ii) <em>firstPageLabels</em> refers to the second data set (<em>L<sub>L</sub></em>) that involves link labels that were extracted from an index page; (iii) <em>aggregateDocument</em> refers to the third data set (<em>L<sub>B</sub></em>) that consists of a so-called big document;</li> <li><em>featureNo</em> - the number of features that were taken into account during evaluation;</li> <li><em>method</em> - the name of function in the caret package;</li> <li><em>user</em> - user time elapsed for executing a <em>method</em> as an R process;</li> <li><em>system</em> - system time elapsed for executing a <em>method</em> as an R process;</li> <li><em>elapsed</em> - total time elapsed for executing a <em>method</em> as an R process.</li> </ul> <p>For more information about user, system and total elapsed time, please see documentation [3].</p> <p><strong>References</strong></p> <p>[1] https://cran.r-project.org/web/packages/caret/</p> <p>[2] https://topepo.github.io/caret/model-training-and-tuning.html</p> <p>[3] https://stat.ethz.ch/R-manual/R-devel/library/base/html/proc.time.htm</p>
Cryogenically Cooled Periodically Poled Lithium Niobate Wafer Stacks for Multi-Cycle Terahertz Pulses
<p>Dataset used for the figures in the paper: "Cryogenically Cooled Periodically Poled Lithium Niobate Wafer Stacks for Multi-Cycle Terahertz Pulses" by Dalton et al. Accepted for publication in Applied Physics Letters on the 6th September 2024.</p>
Ternary π–π Stacking Complexes by Allosteric Regulation in Multilayer Nanographenes
<p>Additional data to report <a href="https://doi.org/10.1021/jacs.4c11119">https://doi.org/10.1021/jacs.4c11119</a>:</p> <p>Construction of π–π stacking supramolecular complexes with more than two components is challenging due to the weak and directionless nature of dispersion interactions. Here we report ternary complexes of a ditopic nanographene tetraimide (<strong>1</strong>), α-substituted phthalocyanine (<strong>Pc</strong>) and polyaromatic hydrocarbons (PAHs) in solution and crystalline state via allosteric regulation. Binding of one <strong>Pc</strong> give rise to significant distortion and conformational changes in <strong>1</strong> that in turn lead to the inhibition of the second binding of <strong>Pc</strong>. The conformational changes associated with first binding allowed an allosteric binding of a third component (PAHs) to form ternary complexes in solution. <sup>1</sup>H NMR titration revealed a moderately high thermodynamic stability for the ternary complexes in CDCl<sub>3</sub>. Competition between allosterically regulated ternary complexes ([<strong>Pc·1</strong>·PAH]) and 1:2 stoichiometric binary complexes of <strong>1</strong> with PAHs ([PAH·<strong>1</strong>·PAH]) were elucidated. Further, selective formation of ternary complexes in solution led to the generation of ternary cocrystals from a 1:1:1 mixture of three components in solution. Our work shows that large π-conjugated nanographenes designed with allosteric recognition sites allow the construction of multilayer ternary complexes in solution and solid-state even with dispersive π–π interactions.</p>
Stacks of microCT Scans, Cell size, weight, volume and thallus size data supporting the paper 'Mechanical regulation of tissue flatness in Marchantia'
<div> <div> <div> <p>These data are the supporting elements to the following paper: 'Mechanical regulation of tissue flatness in Marchantia'</p> </div> </div> </div> <p> .tif files contain MicroCT (MCT) scans of 16-day-old <em>Marchantia polymorpha</em> thalli. Three genotypes were analysed here: <strong><em>fer-2</em></strong> mutant (from Mecchia et al., 2022), <strong>FER-OE #9</strong> (proMpEF1::MpFERONIA-mCitrine trangenic line 9)<strong> </strong>from Mecchia et al., 2022), and Tak-1 (WT line). These plants were grown in 3 different media: Gamborgh B5 + vitamins and 0.6, 1.2 and 2.5% agar, and one stress condition consisting of the adjunction of a thin PDMS film at 4, to mimich external mechanical stimulus (only performed on thalli grown on 1.2% agar).</p> <p>MicroCT scans were performed at the faculity of odontology of Université Paris-Cité (Plateform imagerie du vivant) with the technical support of Lotfi Slimani and Baptiste Casel. https://piv.u-paris.fr/micro-ct-haute-resolution/ </p> <p>All files already have embeded scales.</p> <p>Each file name consists of a unique ID number in the following form:</p> <p>P+<LETTER>+<NUMBER>-<CONDITION></p> <p>-LETTER: One letter = one imaging session</p> <p>-NUMBER: Individual and Genotype: 33-40 -> Tak1; 200-207-><em>fer-2</em>; 41-49 -> FER-OE</p> <p>-CONDITION : AGAR0.6/AGAR2.5/PDMS. Absence of condition indicates growth on standard medium (1.2% agar). PDMS indicated growth on standard medium and supplementation of a topping PDMS film at day 4)</p> <p> </p> <p>-Volume data were calculated from MicroCT scans</p> <p>-thallus projected surfaces were calculated from MicroCT scans</p> <p><a href="https://zenodo.org/api/records/13981438/draft/files/Lambda%20curvature%20calculation.ipynb/content" target="_blank" rel="noopener noreferrer">-Lambda curvature calculation.ipynb</a> is suited for MorphographX mesh exported .txt files.</p> <p> </p> <p> </p> <p> </p>
'Invisible' Molecular Dynamics Revealed for a Conformationally Chiral π-Stacked Perylene Bisimide Foldamer
<p>Additional data to report <a href="https://doi.org/10.1002/anie.202414069">https://doi.org/10.1002/anie.202414069</a>:</p> <p><a name="_Hlk172654864"></a>Whilst energetic and kinetic aspects of folding processes are meanwhile well understood for natural biomacromolecules, the folding dynamics in so far studied artificial foldamer counterparts remain largely unexplored. This is due to the low energy barriers between their conformational isomers that make the dynamic processes undetectable with conventional methods such as UV/vis absorption, fluorescence, and NMR spectroscopy, making such processes ‘invisible’. Here we present an asymmetric perylene bisimide dimer (bis-PBI <strong>1</strong>) that possesses conformational chirality in its folded state. Owing to the large interconversion barrier (≥ 116 kJ mol<sup>–1</sup>), four stereoisomers could be separated and isolated. Since the interconversion between these stereoisomers requires the foldamer to first open and then to re-fold, the transformation of one stereoisomer into others allowed us to ‘visualize’ the dynamics of folding with time and determine its lifetimes and the energetic barriers associated with the folding process. Supported by quantum chemical calculations, we identified the open structure to be only a fleeting metastable state of higher energy. Our experimental observation of the kinetics associated with the molecular dynamics in the PBI foldamer advances the fundamental understanding of folding in synthetic foldamers and paves the way for the design of smart functional materials.</p>
Measured magnetic susceptibility data for different magnetite tracer stacking scenarios
<p>Dataset includes measured data of the volume magnetic susceptibility of 36 artificial soil profiles with various distribution of magnetic tracer. The monitoring was done with Bartington MS2D field probe.</p> <p>The dataset was created for the fitting and calibration of the parameters of a MagHut model. The model and the procedure is described in a manuscript by Zumr D., Li T., Gómez J., Guzmán G., Modelling the response of a field probe for non-destructive measurements of the magnetic susceptibility of soils (to date of the data submission under review).</p>
Diverse Title Generation for Stack Overflow Posts with Multiple Sampling Enhanced Transformer
<p>Dataset for our paper "Diverse Title Generation for Stack Overflow Posts with Multiple Sampling Enhanced Transformer"</p> <p>(<a href="https://github.com/zfj1998/M3NSCT5">zfj1998/M3NSCT5: the code base for our paper "Diverse Title Generation for Stack Overflow Posts with Multiple Sampling Enhanced Transformer" (github.com)</a>)</p> <p>Including three files representing the train/val/test datasets. Each file contains all the collected data covering eight programming languages.</p>
Dataset - What are the Machine Learning best practices reported by practitioners on Stack Exchange?
<p>The data correspond to the posts (questions and answers) retrieved by querying for posts related to the tag 'machine learning' and the phrase 'best practice(s).' The data were used as the basis for a study currently under review on discussing machine learning best practices as discussed by practitioners in question-and-answer communities such as Stack Exchange. The information from each type of post (i.e., questions and answers) is presented in multiple formats (i.e., .txt, .csv, and .xlsx).</p> <p> </p> <p><strong>Answers - Variables</strong></p> <ul> <li><strong>AID</strong>:<strong> </strong> Unique identification of the answer in the Q&A website.</li> <li><strong>ParentId</strong>: Unique identification of the question associated with the answer in the Q&A website </li> <li><strong>AcceptedAnswerId</strong> : In the case in which an answer is the most voted question associated with the <em>ParentId</em>, and it is different from the accepted answer, a different identifier from the <em>AID</em> is available. In the case in which the accepted question had a <em>score</em> lower than 1, a -1 is assigned. </li> <li><strong>ABody:</strong> HTML text of the answer.</li> <li><strong>Score:</strong> Upvotes - downvotes of the answer.</li> <li><strong>url_Answer:</strong> URL of the answer. The question URL can be from different websites. </li> <li><strong>type:</strong> best or accepted. Accepted in the case that the information belongs to the accepted answer of the <em>ParentId </em>question and best in the case in which it is the most voted question of the <em>ParentId </em>question.</li> <li><strong>Date: </strong>Creation date of the answer.</li> </ul> <p><strong>Questions - Variables</strong></p> <ul> <li><strong>QID</strong>: Unique identification of the question in the Q&A website. </li> <li><strong>AcceptedAnswerId</strong>: Unique identification of the accepted answer for a specific question in the Q&A website. In the case in which a question had a most-voted answer different from the accepted one, and the accepted one had a negative score, a -1 was assigned to the <em>AcceptedAnswerId</em><strong>. </strong></li> <li><strong>BestAnswerId</strong>: Unique identification of the most voted answer for a specific question in the Q&A website. In the case in which the most voted and accepted questions were the same, then a -1 was assigned to the <em>BestAnswerId</em>. </li> <li><strong>Qtitle</strong>: Title of the question.</li> <li><strong>QBody</strong>: HTML text of the question.</li> <li><strong>Score</strong>: Upvotes - downvotes of the questions.</li> <li><strong>QTags</strong>: Tags that are associated with each question.</li> <li><strong>url_question</strong>: URL of the question. The question URL can be from different websites. </li> <li><strong>Date</strong>: Creation date of the question</li> </ul> <p>This dataset is a subset of the Stack Exchange dump of 03.2021 (<a href="https://archive.org/details/stackexchange_20210301">https://archive.org/details/stackexchange_20210301</a>) in which a series of filters were applied to obtain the data used in the study.</p>
Test data for 3D with focal stacking
<p>* the data contains a set of .tiff images of a grasshopper eye taken with a Canon</p> <p>* shutter speed: 1/5, ISO: 200</p> <p>* objective Met 20/0.5</p> <p>* speed within stack: 10 um/s, step size: 5 um</p> <p> </p> <p>* Authors: Stefanie Homberger, John Meshreki, Ivo Ihrke, 2023, Universität Siegen / Chair of Computational Sensorics / Communications Engineering</p> <p> </p>
Confocal stacks from archaeological tools used for harvesting and threshing cereals
<p>Series of confocal stacks obtained with SensoScan, using a S Neox 3D profilometer from Sensofar. Measured surfaces from a series of archaeological tools.</p>
Mid to late Pleistocene IODP Expedition 354 Bengal Fan 8⁰ North transect age models, sedimentation rate stack, magnetic susceptibility stack, and XRF data
<p>Mid to late Pleistocene age models for the International Ocean Discovery Program (IODP) Expedition 354 8⁰ North drilling transect. Stacked records of sedimentation rates and magnetic susceptibility. U-channel XRF scans of calcareous clay sediments at Site U1452.</p> <p> </p> <p><strong>Abstract:</strong></p> <p>We investigate chronology and age uncertainty for the middle to upper Pleistocene lower Bengal Fan using a novel age-depth modeling approach that factors litho-, magneto-, bio-, cyclo-, and seismic stratigraphic constraints, based on results from the International Ocean Discovery Program Expedition 354 Bengal Fan and analysis of the GeoB97-020/027 seismic line. The initial chronostratigraphic framework is established using regionally extensive hemipelagic sediment units and only age-depth models of fan deposits that respect the superposition of channel-levee systems between sites are accepted. In doing so, we reconstruct signals of regional sediment accumulation rate and lithogenic sediment input through the perspective of a two-dimensional ~320 km transect at 8⁰ N that are consistent with more distal and more ambiguous regional records. This chronology allows us to discuss the depositional history of the middle to upper Pleistocene lower Bengal Fan within the context of sea level, climate, and tectonic controls. We hypothesize, based on the timing of accumulation rate changes, that progradation and intensification of the Bengal Fan’s channel-levee system at 8⁰ N was largely driven by increases in sea level amplitude during this time. However, it is also possible this progradation was influenced by changes in Pleistocene climate and increased Himalayan erosion rates, driving greater sediment flux to the fan.</p> <p> </p>
Application-Motivated, Holistic Benchmarking of a Full Quantum Computing Stack: Experimental Data
<p>Full experimental dataset for the publication "Application-Motivated, Holistic Benchmarking of a Full Quantum Computing Stack". The archive `application_motivated_benchmarks.zip` contains the following files and directories:</p> <p>- uncompiled_log.csv</p> <p>Gives IDs for the uncompiled circuits initially generated for use in our<br> experiments, along with the properties of the circuits.</p> <p>- properties_log.csv</p> <p>Gives IDs for device property files, along with the device and the time at which<br> they were collected.</p> <p>- compiled_log.csv</p> <p>Gives the calculated figures of merits for the compiled and run circuits.<br> Compiled circuits are identified by the ID of the uncompiled circuit, the<br> compilation strategy used, and the device compiled onto. Device property IDs at<br> the time of compilation and run are given.</p> <p>- circuits/</p> <p>Contains a subdirectory for each uncompiled circuit. Each subdirectory has files<br> of 2 forms.<br> <br> - uncompiled.qasm is the uncompiled circuit.<br> - files of the form 'strategy'_'device'.qasm are the compiled circuits.</p> <p>- data/</p> <p>Contains a subdirectory for each uncompiled circuit. Each subdirectory has files<br> of 3 forms.</p> <p> - prob_vector.csv contains the ideal output probability distribution.<br> - files of the form 'strategy'_'device'.csv contain the shot counts for<br> each compiled circuit when run on the real device.<br> - files of the form 'strategy'_'device'_simulated.csv contain the shot<br> counts for each compiled circuit when run using a classical simulator<br> with noise model build from device properties at the time of the real<br> run.</p> <p>- device_properties/</p> <p>Contains json files detailing device properties for each device property ID.</p> <p> </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.