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 “open code”
Data and codes: Changing the Academic Gender Narrative through Open Access
<p>This Zenodo entry includes data and R codes used to generate the figures included in the manuscript "Changing the Academic Gender Narrative through Open Access", authored by members of the Curtin Open Knowledge Initiative (COKI). These include data that are either publicly available or derived through the COKI data infrastructure.</p> <p>The R file includes codes used to generate Figures 1, 2, 3, 4, 1A, 2A and 3A. It uses data contained in the files "au_data_all.csv", "au_groupings.csv", "uk_data_all.csv" and "uk_groupings.csv".</p> <p>This entry also includes the full data files (.csv and .xlsx) for Figures 5 and 6 included in the manuscript:</p> <ul> <li>Figure 5: ‘Percentages of women academic staff (headcount) compared to the total number of academics in the institution for 43 Australian universities by grouping, 2020’. The analysis is of publicly available data sourced from the Australian Department of Education, Skills and Employment.</li> <li>Figure 6: ‘Percentages of women academic staff (headcount) compared to the total number of academics in the institution for a subset of 165 United Kingdom higher education institutions by grouping, 2020’. The analysis is of publicly available data sourced from the United Kingdom Higher Education Statistics Agency (HESA).</li> </ul>
Data and Code open availability for the FRETsael paper
<p>This dataset includes the raw files of the measurements of Actin-Myosin interactions in SH-SY5Y cells, as well as the Matlab code for the simulations and analyses used in the paper about FRETsael: "<strong>FRET-sensitized acceptor emission localization (FRETsael) – nanometer localization of biomolecular interactions using fluorescence lifetime imaging</strong>"</p>
Thermodynamic and hydrological drivers of the subsurface thermal regime in Central Spain: open data and code
<p>Quality controlled temperature data at daily resolution at CTS, HRR, HYS, NVC, RSI and SGV and the most relevant codes for data processing used in:</p> <p>García-Pereira, F., González-Rouco, J. F., Schmid, T., Melo-Aguilar, C, Vegas-Cañas, C., Steinert, N. J., Roldán-Gómez, P. J., Cuesta-Valero, F. J., García-García, A., Beltrami, H., and de Vrese, H.: "Thermodynamic and hydrological drivers of the subsurface thermal regime in Central Spain". Earth Surf. Dynam., submitted, 2023.</p> <p>All data can be also freely obtained for research from the original data sources, GuMNet (https://www.ucm.es/gumnet/) and AEMET (https://www.aemet.es/en/datos_abiertos). Further details of the code are available upon request to the corresponding author (Félix García-Pereira, felgar03@ucm.es).</p>
Open-population models for estimating roadkill rates - Data and R Code
<p>Roadkill carcass capture-recapture data, capture histories for four and eight-occasion designs, and R code (with JAGS code) for roadkill rates estimation.</p>
Data and MATLAB Code for the paper entitled "A modified Chezy formula for one-dimensional unsteady frictional resistance in open channel flow"
<p>This link includes the data and MATLAB code files for the research paper entitled "A modified Chezy formula for one-dimensional unsteady frictional resistance in open channel flow" by Zhou, J.W.; Bro, W.M.; Tick*, G.R.; Mofatakari, H.; Li, Y.; and Cheng, L., which has been submitted to the Journal of Fluids Engineering. These files are edited under the GB18030 character set standard.</p>
Open Code SORTEE infographics
<p>CRediT (in alphabetical order by family name):<br> - Amin, Bawan (University College Dublin, Ireland): Visualization, Writing – review & editing<br> - Burke, Samantha (University of New South Wales Sydney, Australia): Visualization, Writing – review & editing<br> - Drobniak, Szymon (University of New South Wales Sydney, Australia): Conceptualization, Visualization, Writing – original draft, Writing – review & editing<br> - Lagisz, Malgorzata (University of New South Wales Sydney, Australia): Conceptualization, Visualization, Writing – original draft, Writing – review & editing<br> - Pottier, Patrice (University of New South Wales Sydney, Australia): Visualization, Writing – review & editing<br> - Tam, Jessica Tin-Ying (University of New South Wales Sydney, Australia): Conceptualization, Visualization, Writing – original draft</p>
Landfill: An open dataset of code smells with public evaluation
<p>Code smells are symptoms of poor design and implementation choices that may hinder code comprehension and possibly increase the change- and fault-proneness of source code. Several techniques have been proposed in the literature for detecting code smells. These techniques are generally evaluated by comparing their accuracy on a set of detected candidate code smells against a manually-produced oracle. Unfortunately, such comprehensive sets of annotated code smells are not available in the literature, with only a few exceptions. This dataset provides 243 instances of five types of code smells identified from 20 open-source software projects. In particular, it contains a SQL file with the information concerning such instances and a zip file with their source code.</p>
Core bibliometric Covid19 and comparable research dataset and code for the study "From intent to impact: Investigating the effects of open sharing commitments"
<p>This document provides the underlying dataset for the bibliometric component for the 2022 study "From intent to impact: Investigating the effects of open sharing commitments" by Research Consulting and Science-Metrix.</p> <p>Before reproducing the study findings or re-using the underlying datasets for other purposes, please cautiously review their limitations in the study's technical annex and main report, available at: https://zenodo.org/communities/data-sharing-in-public-health-emergencies/ </p> <p>Particularly, note that there is an error rate in attribution of signatory status to journal publications and preprints; in their location within specific thematic disease-based areas; or computing of dimension such as identification of data availability statement sections; identification of data depisition mentions within data availability statement sections; or matching of preprints and journal publications.</p> <p>These error rates are expected and have been estimated, please consult the technical report for full details.</p> <p> </p> <p>Definition of data fields is provided is the table below:</p> <table> <tbody> <tr> <td>Column name </td> <td>Definition</td> </tr> <tr> <td>document_type</td> <td>preprint or journal publication</td> </tr> <tr> <td>doi</td> <td>digital object identifier</td> </tr> <tr> <td>arxiv_id</td> <td>arXiv preprint server's unique identifier for its preprints</td> </tr> <tr> <td>ssrn_id</td> <td>SSRN preprint server's unique identifier for its preprints. Note that some of these IDs are contained within the DOIs also assigned to some (but not all) SSRN preprints , in the form of "10.2139/ssrn." + 'ssrn_id'</td> </tr> <tr> <td>coalesce_id</td> <td>coalesce function applied to the DOI, arxiv_id and ssrn_id. Redundant for journal publications.</td> </tr> <tr> <td>preprint_server</td> <td>Preprint platform on which a preprint has been published, restricted to arXiv, bioRxiv, medRxiv and SSRN for this study.</td> </tr> <tr> <td>journal_title</td> <td>Publishing journal name in the case of a journal publication.</td> </tr> <tr> <td>year</td> <td>The set is restricted to 2020 and 2021 for Covid19 preprints and journal publications. HVRD journal publications restricted to 2018-2019. HVRD preprints were restricted to 2020-2021 instead, to compensate for the lac of year-normalization for preprints, and generally better control findings against the launch of medRxiv in 2019.</td> </tr> <tr> <td>publication_title</td> <td>Title of the individual journal publication or preprint, not that of the publishing journal or preprint server.</td> </tr> <tr> <td>authors</td> <td>First 100 researchers that appear as authors of a preprint or journal publication. These are not parsed and provided for qualitative validation or assessments rather than for further quantitative treatment.</td> </tr> <tr> <td>Covid19</td> <td>Journal publications or preprints are coded 1 if they has been identified as falling into this thematic area through our queries (see the technical annex), 0 otherwise</td> </tr> <tr> <td>HVRD</td> <td>Human viral respiratory disease, the thematic area considered to be the closest to Covid19. Journal publications or preprints are coded 1 if they has been identified as falling into this thematic area through our queries (see the technical annex), 0 otherwise</td> </tr> <tr> <td>Journal_sig</td> <td>Journal publications where the publishing journal and/or its publishing house are Joint Statement signatories. Coded as 1 if they are signatories, 0 if not signatory, null if status could not be determined due to insufficient metadata. Not that all preprint servers included in this study are Joint Statement signatories. This category was fully removed from the models for preprints, rather than all preprints being assigned automatic signatory status.</td> </tr> <tr> <td>RPO_sig</td> <td>Journal publications and preprints where at least one author is affiliated with at least one research performing organization that is a Joint Statement signatory. Coded as 1 ifor signatory, 0 if not signatory, null if status could not be determined due to insufficient metadata.</td> </tr> <tr> <td>Funder_sig</td> <td>Journal publications and preprints where at least one funder supporting the research is a Joint Statement signatory. Coded as 1 ifor signatory, 0 if not signatory, null if status could not be determined due to insufficient metadata. Although funding is attributed to researchers rather than publications, funding metadata is more readily available at the second level. This approach also captures the flexible usage of financial resources that researchers may make accross mulitple concurrently ongoing research projects.</td> </tr> <tr> <td>overton_norm</td> <td>Year and subfield-normalized binary score of whether the journal publications has been cited by one or more policy-related documents from the Overton database. Null scores for journal publications not covered by the database.</td> </tr> <tr> <td>overton</td> <td>Normalizations being unable for preprints, binary score of whether the preprint has been cited by one or more policy-ralated documents from the Overton database. Null scores for preprints not covered by the database.</td> </tr> <tr> <td>daswriting_binary</td> <td>Binary score capturing identification of a data availability statement in the journal publication or preprint using the queries presented in the technical annex. Null scores are for publications and preprints where records of full texts were unavailable for text mining, or were this analysis could not be performed due to licensing restrictions. </td> </tr> <tr> <td>deposition_binary</td> <td>Binary score capturing identification of a data availability statement and data deposition mention therein in the journal publication or preprint using the queries presented in the technical annex. Null scores are for publications and preprints where records of full texts were unavailable for text mining, or were this analysis could not be performed due to licensing restrictions. </td> </tr> <tr> <td>is_oa</td> <td>Binary score capturing OA or free-to-read (also so-calleod "bronze OA" and "green OA") status of journal publications. Unpaywall categories have been used in a mutually exclusive implementation, with the best (gold > hybrid>bronze>green) possible applicable category being retained. Null scores for journal publications not covered in our Unpaywall dataset. Scores of 0 denote journal publications not available under an OA or free-to-read category.</td> </tr> <tr> <td>is_gold</td> <td>as above</td> </tr> <tr> <td>is_hybrid</td> <td>as above</td> </tr> <tr> <td>is_bronze</td> <td>as above</td> </tr> <tr> <td>is_green</td> <td>as above</td> </tr> <tr> <td>matched_journal_binary</td> <td>For preprints, whether one or more matching journal publications could be identified using the queries identified in the technical, or preprint servers' own lists of preprint-journal publication matches. Null scores for preprints with insufficient metadata information to perform the matching operation.</td> </tr> <tr> <td>matched_journal_doi</td> <td>For those preprints with or more matching journal publications, the DOI(s) of the matching journal publication(s). Note that some of the maching journal publications identified do not have DOIs.</td> </tr> <tr> <td>matched_preprint_binary</td> <td>For journal publications, whether one or more matching preceding preprints could be identified using the queries identified in the technical annex, or preprint servers' own lists of preprint-journal publication matches. Null scores for journal publications without sufficient metadata to run the analysis.</td> </tr> <tr> <td>matched_preprint_id</td> <td>For those journal publications preceded with one or more arXiv, bioRxiv, medRxiv or SSRN preprints, the DOI(s), arXiv ID and/or SSRN ID of the matching preprint(s). </td> </tr> <tr> <td>hasdoi</td> <td>Only journal publications with DOIs were retained in the core quantitative analyses.</td> </tr> <tr> <td>hasacknowledgements</td> <td>Only journal publications with funding acknowledgements (to determine funding-based signatory status) were retained in the core quantitative analyses.</td> </tr> <tr> <td>funder_array</td> <td>Array (but cast as string) of names of the funders on the basis of whose idenitification signatory status has been attributed, where relevant. Null if non-signatory or unknown signatory status.</td> </tr> <tr> <td>RPO_array</td> <td>Array (but cast as string) of names of the research performing organizations on the basis of whose idenitification signatory status has been attributed, where relevant. Null if non-signatory or unknown signatory status.</td> </tr> <tr> <td>DAS_excerpt</td> <td>Journal publication or preprint text excerpt on which succesful identifcation of data availability statements and/or data deposition mentions have been made. Null both where the query could not be run at all, or where the query was negative.</td> </tr> <tr> <td>big5</td> <td>Journal publication published in a journal owned by one of the following five publishing houses: Elsevier, Sage, Springer Nature, Taylor-Francis, Wiley.</td> </tr> <tr> <td>LMIC</td> <td>Journal publication whose authors include at least one researcher affiliated with at least one institution located in a lower-middle income country as defined by the World Bank</td> </tr> <tr> <td>LIC</td> <td>Journal publication whose authors include at least one researcher affiliated with at least one institution located in a low income country as defined by the World Bank</td> </tr> <tr> <td>SouthNorth</td> <td>Journal publication whose authors include at least one researcher affiliated with at least one institution located in a upper-middle income country, a lower-middle income country, or a low income country as defined by the World Bank; as well as at least one researcher affiliated with at least one institution located in a high income country. For the purpose of this indicator, Sicnece-Metrix exceptionally includes China and Bulgaria in the list of high income countries.</td> </tr> <tr> <td>DID_allauthors_OR</td> <td>Journal publication is included in the difference-in-difference model defining signatory publication as EITHER holding journal-based signatory status OR funding-based signatory status, and where no filter has been applied to control for author-level biases.</td> </tr> <tr> <td>DID_authorcontrol_OR</td> <td>Journal publication is included in the difference-in-difference model defining signatory publication as EITHER holding journal-based signatory status OR funding-based signatory status, and where a filter has been applied to control for author-level biases.</td> </tr> <tr> <td>DID_authorcontrol_AND</td> <td>Journal publication is included in the difference-in-difference model defining signatory publication as holding journal-based signatory status AND funding-based signatory status, and where a filter has been applied to control for author-level biases.</td> </tr> <tr> <td>DID_allauthors_AND</td> <td>Journal publication is included in the difference-in-difference model defining signatory publication as holding journal-based signatory status AND funding-based signatory status, and where no filter has been applied to control for author-level biases.</td> </tr> <tr> <td>Preprint_authorcontrol</td> <td>Preprint is included in the the analytical breakdowns where a filter has been applied to control for author-level biases. Note that authors have been kept constant in preprints on the basis of their belonging to all analytical breakdowns in journal publications rather than in preprint-based groups.</td> </tr> </tbody> </table> <p> </p>
Making the Most out of a Hydrological Model Dataset: Sensitivity Analyses to Open the Model Black-Box (data and code)
<p>This is "data and code" repository for the Water Resources Research Article 2017WR020401 by Borgonovo et al. (2017): "Making the most out of a hydrological model data set: Sensitivity analyses to open the model black-box". Each sub-directory contains the Matlab or R scripts to reproduce all paper plots. </p> <p>Note, that the data of this repository (i.e. under ./data_input ) are identical to the data analysed by Rakovec et al. (2014).</p> <p>References:</p> <ul> <li>Borgonovo, E., Lu, X., Plischke, E., Rakovec, O. and Hill, M. C. (2017), Making the most out of a hydrological model data set: Sensitivity analyses to open the model black-box. Water Resour. Res.. Accepted Author Manuscript. doi:10.1002/2017WR020767</li> <li>Rakovec, O., M. C. Hill, M. P. Clark, A. H. Weerts, A. J. Teuling, and R. Uijlenhoet (2014), Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models, Water Resour. Res., 50, 409–426, doi:10.1002/2013WR014063.</li> </ul>
Identifying Episodes of Hypovigilance in Intensive Care Units Using Routine Physiological Parameters and Artificial Intelligence: a Derivation Study. Open Code and Dataset
<p>The purpose of this project is to detect hypogilance using the EVEILS database.</p> <p>Database is ICU data from Hôtel-Dieu De Lévis , Québec, Canada. Please cite us if you use either the data or code. </p> <p>This code was written during Raphaëlle Giguère Msc in Computer Science. The goal of her project is to detect hypovigilance using machine learning in the ICU. In this repository, you have the data set before preprocessing:</p> <ul> <li>df_hypovigilance : Contains the hours, date and value of the vigilance level, using either the RASS or Ramsay and already converted using the thresholds shown in the paper.</li> <li>raw_df : Contains the raw values from the gateway for each participant. All of the identifying values have been removed.</li> </ul> <p>At the end of the preprocessing_anonymous script, you should generate a new dataset called "df_final". This dataset is used for the training_model script.</p> <p>The cross validation employs groups of random size meaning the results might differ from time to time but should stay consistent.</p> <p> </p>
Phenotype variation in Niphargus (Amphipoda: Niphargidae): possible explanations and open challenges: data and R code
<p>Data and R code for performing the analyses of phylogenetic signal presented in the manuscript titled "Phenotype variation in Niphargus (Amphipoda: Niphargidae): possible explanations and open challenges. Data contains phylogenetic tree (Delić et al., 2023) and functional trait data in the RDS format (Premate & Fišer, 2024). The R code is available in the html format.</p> <p>References/data sources:</p> <p>Delić, T., Borko, S., Premate, E., Rexhepi, B., Alther, R., Knuesel, M., ... & Altermatt, F. (2023). Evolutionary origin of morphologically cryptic species imprints co-occurrence and sympatry patterns. <em>bioRxiv</em>, 2023-09.</p> <p>Premate, E., & Fišer, C. (2024). Functional trait dataset of European groundwater Amphipoda: Niphargidae and Typhlogammaridae. <em>Scientific Data</em>, <em>11</em>(1), 188.</p>
Galvanising the Open Access Community: A Study on the Impact of Plan S - Data and Code
<div> <div> <div> <div> <p>This repository contains the datasets and code underpinning <em>Chapter 3 "Counterfactual Impact Evaluation of Plan S"</em> of the report <em>"Galvanising the Open Access Community: A Study on the Impact of Plan S"</em> commissioned by the cOAlition S to scidecode science consulting.</p> <p>Two categories of files are part of this repository:</p> <p><strong>1. Datasets <br></strong></p> <p>The 21 CSV source files contain the subsets of publications funded by the funding agencies that are part of this study. These files have been provided by <em>OA.Works</em>, with whom scidecode has collaborated for the data collection process. Data sources and collection and processing workflows applied by <em>OA.Works</em> are described on their website and specifically at <a href="https://about.oa.report/docs/data">https://about.oa.report/docs/data</a>.</p> <p>The file "plan_s.dta" is the aggregated data file stored in the format ".dta", which can be accessed with <em>STATA </em>by default or with plenty of programming languages using the respective packages, e.g., <em>R</em> or <em>Python</em>. </p> <p><strong>2. Code files</strong></p> <p>The associated code files that have been used to process the data files are:</p> <pre> - data_prep_and_analysis_script.do<br> - coef_plots_script.R</pre> <p>The first file has been used to process the CSV data files above for data preparation and analysis purposes. Here, data aggregation and data preprocessing is executed. Furthermore, all statistical regressions for the ounterfactual impact evaluation are listed in this code file. The second code file "coef_plots_script.R" uses the computed results of the counterfactual impact evaluation to create the final graphic plots using the <em>ggplot2 </em>package.</p> <p>The first ".do" file has to be run in STATA, the second one (".R") requires the use of an integrated development environment for R. </p> Further Information are avilable in the final report and via the followng URLs:<br> <pre><a href="https://www.coalition-s.org/">https://www.coalition-s.org/</a> <a href="https://scidecode.com/">https://scidecode.com/</a> <a href="https://oa.works/">https://oa.works/</a> <a href="https://openalex.org/">https://openalex.org/</a><br><a href="https://sites.google.com/view/wbschmal">https://sites.google.com/view/wbschmal</a> </pre> </div> </div> </div> </div>
Code & Data from: Development of a low cost open-source ultrasonic device for plant height measurements
<p>We here provide code and data for the study "Development of a low cost open-source ultrasonic device for plant height measurements"</p> <p>Code:<br> - Arduino code (management of the electronic circuit): "Arduino_ultrasonic_sensor.ino"<br> - OpenSCAD code (3D-printing): "3DShells_ultrasonic_sensor.scad"<br> - R code (statistical analysis of field test): "Statistical_analysis.R"</p> <p>Data:<br> - "manual_vs_sensor_controlled.csv": this file contains the comparison between the ultrasonic device and the ruler in standardized laboratory conditions. It has three columns: "manual_value", the height value measured manually; "sensor_value", the height value obtained from the ultrasonic device; "height_range", the interval to which the height value belongs (we worked with 25 cm intervals).<br> - "manual_vs_ruler_field.csv": this file contains the comparison between the ultrasonic device and the ruler in field conditions. Plant height measurements were performed on 26 sorghum genotypes. The file has four columns: "Genotype", the id of the measured genotype; "rep" the replicate (3 plants were measured for each genotype); "manual_value", the height value measured manually; "sensor_value", the height value obtained from the ultrasonic device. When using the ruler, the operator spent 15 min and 23 s to complete all measurements in the field, and 3 min and 27 s to enter all data manually in a digital file. When using the sensor, the operator spent 10 min and 52 s to complete all measurements in the field, and manual transcription was not needed since all measurements are instantaneously saved on an SD card.</p> <p>More details on the experimental data can be found in the article "Development of a low cost open-source ultrasonic device for plant height measurements".</p> <p>We also provide a tutorial to explain how to build the ultrasonic-sensor ("tutorial.docx")</p>
Research Compendium for Harrington et al. (2021): "An Open-Source Bayesian Atmospheric Radiative Transfer (BART) Code: I. Design, Tests, and Application to Exoplanet HD 189733 b"
<p>This archive is the Reproducible Research Compendium for<br> <br> An Open-Source Bayesian Atmospheric Radiative Transfer (BART) Code: I. Design, Tests, and Application to Exoplanet HD 189733 b<br> <br> by Harrington et al. (2021), published in The Planetary Science Journal.<br> <br> BART is an atmospheric parameter retrieval code. It infers the properties of planetary atmospheres from spectroscopic observations. The compendium includes all the software, documentation, configuration files, plots, and data published in the paper. The compendium is under the Reproducible Research Software License; see LICENSE file. The README provides additional information and describes the contents of each compressed .tar.gz file.</p>
Data and Code for "Value dissonance in research(er) assessment: Individual and institutional priorities in review, promotion and tenure criteria related to research quality, quantity, openness and responsibility"
<p>This snapshot contains code and data for the preprint "Value dissonance in research(er) assessment: Individual and institutional priorities in review, promotion and tenure criteria related to research quality, quantity, openness and responsibility".</p> <p>Instructions on re-using the data and running the code can be found in the README.md.</p> <p>Changes:</p> <ul> <li>Added survey instrument and informed consent.</li> </ul>
Data and Code Supplement to: "Processes of change in a randomized clinical trial of Radically Open Dialectical Behavior Therapy (RO DBT) for adults with treatment refractory depression"
<p>Dataset to support secondary analyses reported in "Processes of change in a randomized clinical trial of Radically Open Dialectical Behavior Therapy (RO DBT) for adults with treatment refractory depression" in the Journal of Consulting and Clinical Psychology</p>
Open anonymous repo hosting code and data for our submission in ASE 2020
<p>This repository presents sample publicly available anonymous source code and data for our submission in ASE 2020 conference.</p> <p>ProgressDroid source code is provided.</p> <p>Data for 10 top apps with the highest number of installs from our dataset are presented.</p> <p>For each app, we provide the following information:</p> <p>- The original APK file for the examined app.</p> <p>- The instrumented APK file using the extended Instrumenter module</p> <p>- Complete trace from running the extended AndroidSlicer tool on each app</p> <p>- Complete list of all UI update points in each specific app</p> <p>- List of slicing criteria for dynamic slicing </p> <p>- List of slices from the automated dynamic slicing analysis </p> <p>- List of all progress indicator occurrences for each trace </p> <p>- Complete runtime trace info including all events and states (including screenshots) </p> <p>Upon acceptance, we’ll complete the data sharing for all our dataset.</p>
Sample Stripped Pre-supernova Progenitors for open-source code CHIPS (Complete History for Interaction-Powered Supernovae)
<p>Inlists, mainly based on the test suite "example_make_pre_ccsn" in r12778, with slight amendments for removal of hydrogen (and helium, for Ic progenitors) envelope at core hydrogen (helium) exhausion.</p><p>For details: https://ui.adsabs.harvard.edu/abs/2023arXiv230810785T/abstract</p>
Open Data, Open Code, Open Infrastructure Schematic Diagram
<p>A schematic diagram of how social workflows, technical workflows, and project governance interact with the open data, open code, and open infrastructure (O3)</p>
Figures code and data of "Coulomb blockade in open superconducting islands on InAs nanowires"
<p>Electrons in closed systems can exhibit Coulomb blockade (CB) oscillations due to charge quantization. Here, we report CB oscillations in aluminum superconducting islands on InAs nanowires in the open regime. The Al island is connected to the source/drain leads through two contacts: One is fully transmitting while the other is tuned into the tunneling regime. This device configuration is typical for tunneling spectroscopy where charging energy is generally considered negligible. The oscillation periods are 2e or 1e, depending on the gate settings. A magnetic field can induce the 2e to 1e transition. Our result is reminiscent of the ``mesoscopic Coulomb blockade'' in open quantum dots caused by electron interference. </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.