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8,537 results for “Openness”
Austrian Science Fund (FWF) Open Access Compliance Monitoring 2021
<p><strong>I. Executive summary</strong></p> <p>The Austrian Science Fund (FWF), which is Austria's main funding organisation for basic research, encourages and helps all project leaders and project staff members to make their peer-reviewed research results freely available on the Internet. Any exceptions must be clearly indicated and justified. For projects that started after 1 January 2015, open access has been compulsory for all peer-reviewed publications. All principal investigators in FWF-funded projects are obliged to submit a final report within four months of completing their projects.</p> <p>In 2021, a total of 584 final reports were submitted to the FWF, 48 of which could not report any publications so far. The publications and other data mentioned in those reports are archived and analysed by the FWF. This report examines the state of compliance with open access requirements for peer-reviewed publications on the basis of final project reports submitted in the year 2021.</p> <p>Main findings:</p> <p>-A total of 7,025 publications were listed in the final project reports submitted in 2021.</p> <p>-Of those publications, 5,735 were conclusively identified as peer-reviewed.</p> <p>-Regarding compliance with the FWF's Open Access Policy, the analysis shows that 82% of the peer-reviewed publications listed in the final project reports submitted in 2021 were openly accessible (2015: 83%, 2016: 92%, 2017: 90%, 2018: 92%, 2019: 89%, 2020: 84%).</p> <p>-The most frequently chosen option was hybrid open access (39%). The share of gold open access was 23%, the share of green open access 20%, and no open access 18%.</p> <p>-The majority of peer-reviewed publications submitted were journal articles (85%), 86% of which were openly accessible.</p> <p>-The lowest rate of compliance with the FWF's Open Access Policy could be found in editions, contributions to edited volumes, and monographs (50%).</p> <p>-The absolute number of publications listed in final reports in 2021 included 403 publications that were mentioned several times in different projects; however, those repetitions did not ultimately affect the relative share of open access publications (81%).</p> <p>II. Bias</p> <p>Most of the publications were submitted to the FWF via a research documentation system (provided by ©Researchfish), in which FWF-funded researchers are able to enter and update their research data on an ongoing basis. The last check of the open access status was performed in March 2022. In some cases, the embargo period may have already expired, and publications labelled ‘closed’ in the FWF’s database may now be accessible through green open access.</p> <p>Whenever the status ‘peer-reviewed’ could not be clearly identified according to the FWF’s guidelines, the publications were classified as non-peer reviewed.</p> <p>Openly available non-peer reviewed publications were entered as 'openly available’.</p>
Dataset: The availability and completeness of open funder metadata - Case study for publications funded by the Dutch Research Council
<p>Data and code belonging to the manuscript: <strong>The availability and completeness of open funder metadata - Case study for publications funded by the Dutch Research Council </strong></p> <p><strong>Abstract:</strong><br> Research funders spend considerable efforts collecting information on outcomes of the research they fund. To help funders track publication output associated with their funding, Crossref initiated FundRef in 2013, enabling publishers to register funding information using persistent identifiers. However, it is hard to assess the coverage of funder metadata because it is unknown how many articles are the result of funded research and therefore should include funder metadata. </p> <p>In this paper we looked at 5,004 publications reported by researchers to be the result of funding by a specific funding agency: the Dutch Research Council NWO. Only 67% of these articles contain funding information in Crossref, with a subset acknowledging NWO as funder name and/or Funder IDs linked to NWO (53% and 45%, respectively). </p> <p>Web of Science (WoS), Scopus and Dimensions are all able to infer additional funding information from funding statements in the full text of the articles. Funding information in Lens largely corresponds to that in Crossref, with some additional funding information likely taken from PubMed. </p> <p>We observe interesting differences between publishers in the coverage and completeness of funding metadata in Crossref compared to proprietary databases, highlighting potential to increase the quality of open metadata on funding. </p> <p><strong>This dataset contains the following files:</strong></p> <ul> <li><strong>DOIs_unique_CR_Lens_Wos_Scopus_Dim.csv</strong><em> - </em>Dataset of unique DOIs (n= 5,004) with collected information from Crossref and presence/absence of funder information in Lens, Web of Science, Scopus and Dimensions </li> <li><strong>NWO_funder_names_Crossref.txt</strong><em> </em>- List of funder name variants for NWO found in Crossref</li> <li><strong>Google_Apps_Script.js</strong> - Google Apps Script for retrieving information from Crossref and processing Dimensions results </li> <li><strong>DOI_cleaning.R</strong><em> - </em>R script for cleaning DOIs</li> </ul>
Funding Covid-19 research: Insights from an exploratory analysis using open data infrastructures - Supplementary material
<p>This dataset contains supplementary material for the paper 'Funding Covid-19 research: Insights from an exploratory analysis using open data infrastructures' by Alexis-Michel Mugabushaka, Nees Jan van Eck, and Ludo Waltman.</p> <ul> <li>supplementary_material_1_dataset.ods: Dataset of Covid-19 publications.</li> <li>supplementary_material_2_sample.ods: Samples of publications used to assess the accuracy of funding data in the different databases.</li> <li>supplementary_material_3_tables_and_figures.ods: Statistics underlying the tables and figures presented in the paper.</li> </ul>
TrainRuns.jl: an Open-Source Tool for Running Time Estimation - Supplement Data
<p>This additional data contains the initial data and the calculated results for comparing FBS and TrainRuns.jl.</p> <p><strong>File description</strong></p> <ul> <li><em>local.yaml</em>: input parameters for the local train</li> <li><em>freight.yaml</em>: input parameters for the freight train</li> <li><em>running_path.yaml</em>: input parameters for the path</li> <li><em>freight_FBS.csv</em>: export of calculation from FBS for the freight train</li> <li><em>freight_TrainRuns.csv</em>: export of calculation from TrainRun.jl converted in FBS units for the freight train</li> <li><em>freight_diff.csv</em>: the calculated difference between FBS.csv and TrainRuns.csv for the freight train</li> <li><em>local_FBS.csv</em>: export of calculation from FBS for the local train</li> <li><em>local_TrainRuns.csv</em>: export of calculation from TrainRun.jl converted in FBS units for the local train</li> <li><em>local_diff.csv</em>: the calculated difference between FBS.csv and TrainRuns.csv for the local train</li> <li><em>running_path.csv</em>: converted running_path.yaml for displaying</li> <li><em>comparison.tex</em>: LaTeX code for the graph in comparison.pdf</li> </ul> <p><strong>Sources</strong></p> <p>The calculations in FBS were done with the file 'Ostsachsen_V220.railml'. FBS needs a commercial license, which can be purchased. License for 'Ostsachsen_V220.railml' is Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0).<br> The file 'Ostsachsen_V220.railml' can be found at:<br> https://www.railml.org/en/user/exampledata.html (last accessed 2022-06-06 with login) -> "Real world railway examples from professional tools" -> "East Saxony railway network by FBS" -> "Ostsachsen_V220.railml"</p> <p>Other sources are mentioned in the files.</p>
Data for manuscript sumitted to Open Research Europe, entitled "Low-resistivity, high-resolution W-C electrical contacts fabricated by direct-write focused electron beam induced deposition"
<p>These are the data obtained experimentally and used to draw the figures in the article submitted to Open Research Europe</p>
Do Go Chasing Waterfalls: Enoyl Reductase (FabI) in Complex with Inhibitors Stabilizes the Tetrameric Structure and Opens Water Channels - full trajectories of SaFabI and EcFabI monomers and G112/113V mutants
<p>The following IDs are related to trajectories:</p> <p>v36 = EcFabI apo, monomer<br> v42 = EcFabI + TCL complex, monomer<br> v43 = EcFabI + MUT complex, monomer<br> v44 = EcFabI + AFN complex, monomer<br> v35 = SaFabI apo, monomer<br> v45 = SaFabI + TCL complex, monomer<br> v46 = SaFabI + MUT complex, monomer<br> v47 = SaFabI + AFN complex, monomer<br> v52 = G112V EcFabI apo, tetramer<br> v53 = G112V EcFabI apo, monomer<br> v54 = G113V SaFabI apo, tetramer<br> v55 = G113V SaFabI apo, monomer</p>
Do Go Chasing Waterfalls: Enoyl Reductase (FabI) in Complex with Inhibitors Stabilizes the Tetrameric Structure and Opens Water Channels - full trajectories of SaFabI and EcFabI tetramers
<p>The following IDs are related to trajectories:</p> <p>v1 = EcFabI apo, tetramer<br> v2 = EcFabI + TCL complex, tetramer<br> v3 = EcFabI + MUT complex, tetramer<br> v39 = EcFabI + AFN complex, tetramer<br> v16 = SaFabI apo, tetramer<br> v17 = SaFabI + TCL complex, tetramer<br> v18 = SaFabI + MUT complex, tetramer<br> v40 = SaFabI + AFN complex, tetramer</p>
Success Stories of Open Science Graphic
<p>Graphic for use in promoting open science success stories. Five scientists who are using open science everyday in their research were chosen as Success Stories of Open Science. Two scientists are pictured on the top of the image, Dr. Reina Camacho Toro on the top left and Dr. Afshin Beheshti on the top right. On the bottom of the image from left to right are headshots of Dr. Leo Stinger, Dr. Africa Ixmucane Flores-Anderson, and Dr. Flavio Azevedo. The middle of the image is white text that reads, "Success Stories of Open Science." The TOPS logo is in the upper right of the image.</p>
Open Access Publication of Public Health Research in African Journals: Dataset
<p>This study explored the open publishing practices of African journals expected to publish articles on Public Health.</p>
Data for: Open COVID Trials (OCT) Project
<p><span>The COVID-19 pandemic has brought substantial attention to the systems used to communicate biomedical research. In particular, the need to rapidly and credibly communicate research findings has led many stakeholders to encourage researchers to adopt open science practices such as posting preprints and sharing data. To examine the degree to which this has led to the actual adoption of such practices, we examined the "openness" of a sample of 539 published papers describing the results of randomized controlled trials testing interventions to prevent or treat COVID-19. The majority (56%) of the papers in this sample were free to read at the time of our investigation and 23.56% were preceded by preprints. However, there is no guarantee that the papers without an open license will be available without a subscription in the future, and only 49.61% of the preprints we identified were linked to the subsequent peer-reviewed version. Of the 331 papers in our sample with statements identifying if (and how) related datasets were available, only a paucity indicated that data was available in a repository that facilitates rapid verification and reuse. Our results demonstrate that, while progress has been made, there is still a significant mismatch between aspiration and actual practice in the adoption of open science in an important area of the COVID-19 literature.</span></p>
Do Go Chasing Waterfalls: Enoyl Reductase (FabI) in Complex with Inhibitors Stabilizes the Tetrameric Structure and Opens Water Channels - trajectories employed in Markov State Models and water analyses
<p>The following trajectories were employed in the generation of MSM models and water analyses:</p> <p>SaFabI_60us_align.zip</p> <p>EcFabI_60us_align.zip</p> <p>waters_SaFabI.tar.gz</p> <p>waters_EcFabI.tar.gz</p>
Contributions of Open-loop and Closed-loop Control in a Continuous Tracking Task Differ Depending on Attentional Demands during Practice
<p>We provide tracking data of the analysed segments after filtering, cognitive performance data and indivdual force levels. To this end, the data set contains three zip-files of numbers of csv-files and an additional csv-file. In each csv-file, comma delimits information within the rows. Participant numbers range between 1 and 21 where the first 11 numbers always refer to the participants of the single-task training group and the final 10 numbers refer to the participants of the dual-task training group.</p> <p>The <em>IndividualForceMaximum.csv</em> includes separate rows of participant’s information about training group, individual force maximum, and the 10% value of the force maximum, which was important for adapting the required force to the individual applicable leg force.</p> <p>The <em>CognitiveTaskData.zip </em>contains four csv-files. Two files are for the <em>TEST</em> sessions, which include either the <em>total</em> number of responses or the number of <em>correct</em> responses per trial for each participant within a row. The other two files are for the <em>TRAINING</em> data (either <em>total</em> number of responses or number of <em>correct</em> responses) of the cognitive task for the participants of the dual-task training group. The file includes 15 trials of the first and the last five training days (i.e., days 1 to 5, and days 18 to 22). For each participant the training data is presented in a row.</p> <p>The tracking data is split with respect to the training groups in either the single-task training group, i.e., <em>MotorTaskData_SingleTaskTrainingGroup.zip</em>, or the dual-task training group, i.e., <em>MotorTaskData_DualTaskTrainingGroup.zip</em>. Each of the zip-files includes <em>TESTING</em> and <em>TRAINING</em> data in csv-files for each participant <em>P</em> separately. We further separated the <em>TEMPLATE</em> data and the <em>PERFORMANCE</em> data, i.e., for instance template test file of P1 corresponds with performance test file of P1. Each trial is presented in a row, where the header includes the segment information (i.e., first segment = 1, second segment = 2, and third segment = 3) for each data point. <em>TEST </em>data include trials with the practiced second segment and the catch trials with another second segment. <em>TRAINING</em> data include the 15 trials of the first and the last five training days (i.e., days 1 to 5, and days 18 to 22).</p>
Supplementary data: "Open modeling of electricity and heat demand curves for all residential buildings in Germany"
<p>This repository contains supplementary data for the paper <a href="https://doi.org/10.1186/s42162-022-00201-y"><em> "Open modeling of electricity and heat demand curves for all residential buildings in Germany"</em></a>.</p> <p>See <em>README.md</em> / <em>README.pdf</em> for further details.</p> <p><strong>Citing</strong></p> <p>Please cite as:</p> <p><em>Büttner, C., Amme, J., Endres, J. et al. Open modeling of electricity and heat demand curves for all residential buildings in Germany. Energy Inform 5 (Suppl 1), 21 (2022).</em></p> <p><strong>Funding</strong></p> <p>The authors thank the Federal Ministry for Economic Affairs and Climate Action for funding the research project eGon (funding code: 03EI1002).</p> <p> </p>
Linked Open Data for the maritime domain
<p>Linked Data in this data set have been compiled from diverse data sources providing information about Trade and Transport locations, protected areas, surveillance data of vessels and vessel characteristics. Data have been transformed into triples according to the vesselAI ontology, using <a href="http://core.ac.uk/download/pdf/212138612.pdf">RDF-Gen</a> . All geometries are provided using <a href="http://www.opengis.net/ont/geosparql">OGC</a> terms. The vesselAI ontology documentation is available<a href="http://83.212.101.70/vesselAI_ontology.html"> here</a> .</p> <p>In a nutshell, this data set comprises data from the following sources:</p> <p>1. AIS messages of moving objects retrieved from <a href="https://ais-public.kystverket.no/ais-download/">Norwegian Coastal Administration's SafeSeaNet</a> solution, combined with data provided by the <a href="http://web.ais.dk/aisdata/">Danish Maritime Authority</a>. Each record contains the coordinates of the vessel, a timestamp, an identifier for the vessel, its speed and heading. Typically, each vessel reports this information by sending an AIS message every few seconds. Each reported position is also annotated with the corresponding weather conditions according to Copernicus Climate Change Service (C3S) (files: reconstructed_traj.7z, ais202101_part1.7z, ais202101_part2.7z)</p> <p><br> . The weather variables currently considered as relative to the movement of vessels are:</p> <ul> <li> '10m_u_component_of_wind',</li> <li> '10m_v_component_of_wind',</li> <li> '2m_dewpoint_temperature',</li> <li> '2m_temperature',</li> <li> 'mean_sea_level_pressure',</li> <li> 'mean_wave_direction',</li> <li> 'mean_wave_period',</li> <li> 'precipitation_type',</li> <li> 'sea_surface_temperature',</li> <li> 'total_precipitation'</li> </ul> <p>2. Vessel characteristics retrieved from online sources, combined with information about departure and destination seaports. United Nations Code for Trade and Transport Locations (UN/LOCODE), has been also used, to annotate the seaports with their longitude, latitude and Well Known Text (WKT) information, as well as features and facilities available according to online sources (files: vesselsCharacteristics.7z, worldPorts.7z ).</p> <p>3. Regions of interest in the maritime domain include fishing areas, endangered species habitat areas, exclusive economic zones (EEZ), Natura2000 protected areas. In this snapshot we provide Natura2000 regions (file: natura2000.7z) as well as <a href="https://www.protectedplanet.net/en">World Protected Areas data set</a> (file: wdpa2022.ttl.7z )</p> <p>Updates and additional data sets can be found <a href="http://83.212.101.70/vesselAI_ontology.html">here</a> .</p> <p>The surveillance and weather data in this data set, are for January 2021 and within the region defined by the degrees:</p> <p>#west: 2.53<br> #south: 51.50<br> #north: 60.50<br> #east: 17.50</p>
Open Innovation - Innovationsmanagement bei der Schweizerischen Post
<p><b>Abstract</b></p><p class="dhik-abstract-content">Unternehmen in der Schweiz wie zum Beispiel die Schweizerische Post haben Partnerschaften mit Hochschulen und Universitäten aufgebaut. Ihre Open Innovation Approach wird kurz vorgestellt.</p><p></p><p><b>Weitere Beiträge aus dem DHIK-Forum 2022 auf Zenodo:</b></p><p class="dhik-session-list"></p><ul><li>Session #1: Viktor Sigrist: Internationalisierung - Partnerschaften für den Ausbau von Forschung und Entwicklung (DOI:<a href="https://zenodo.org/record/7123701">10.5281/zenodo.7123701</a>)</li><li>Session #2: Dieter Leonhard: DHIK- Strategien der internationalen Zusammenarbeit in Forschung und Lehre (DOI:<a href="https://zenodo.org/record/7123456">10.5281/zenodo.7123456</a>)</li><li>Session #3: Stephen Wittkopf: Wissens- und Innovationstransfer - Interdisziplinäre Zusammenarbeit mit Unternehmen und Institutionen (DOI:<a href="https://zenodo.org/record/7025707">10.5281/zenodo.7025707</a>)</li><li>Session #4: Xiao Feng: CDHAW - Chinesisch-Deutsche Hochschule für Angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123458">10.5281/zenodo.7123458</a>)</li><li>Session #5: Antonio Pita und Isabel Kreiner: Academy-Industry-Collaboration - Outreach Strategy (DOI:<a href="https://zenodo.org/record/7123460">10.5281/zenodo.7123460</a>)</li><li>Session #6: Martin Sternberg: Promotionsrecht – aktueller Stand an deutschen Hochschulen für angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123757">10.5281/zenodo.7123757</a>)</li><li>Session #7: Adrian Derungs: Duo mit Innovationskraft - Zusammenspiel von Forschung und Wirtschaft in der Zentralschweiz (DOI:<a href="https://zenodo.org/record/7123767">10.5281/zenodo.7123767</a>)</li><li>Session #8: Theres Paulsen: Transdisziplinäre Forschung - komplexe gesellschaftliche Herausforderungen erfordern diverse Ansätze (DOI:<a href="https://zenodo.org/record/7123769">10.5281/zenodo.7123769</a>)</li><li>Session #9: Jörg Schneider: International research collaboration - New funding opportunities for universities of applied sciences (DOI:<a href="https://zenodo.org/record/7123771">10.5281/zenodo.7123771</a>)</li><li>Session #10: Cornelia Spycher und Matthew Whellens: Horizon Europe - overview of funding opportunities for your research and innovation (DOI:<a href="https://zenodo.org/record/7123773">10.5281/zenodo.7123773</a>)</li><li>Session #11: Janique Siffert: Eureka Eurostars - erfolgreiche Förderung für internationale Innovationsprojekte (DOI:<a href="https://zenodo.org/record/7123777">10.5281/zenodo.7123777</a>)</li><li>Session #12: Ludger Fischer: Energy Lab - ein Netzwerk für innovative Lösungen im Energiebereich (DOI:<a href="https://zenodo.org/record/7123779">10.5281/zenodo.7123779</a>)</li><li>Session #13: Jörg Worlitschek: Thermal energy storage - heating the north, cooling the south (DOI:<a href="https://zenodo.org/record/7123781">10.5281/zenodo.7123781</a>)</li><li>Session #14: Jonas Mühlethaler: Neues DC Microgrid-Konzept – netzunabhängige Elektrifizierung in Entwicklungsländern (DOI:<a href="https://zenodo.org/record/7123783">10.5281/zenodo.7123783</a>)</li><li>Session #15: Tommy Claussen: Dekarbonisierung des Gebäudesektors - digitale Transformation in der Gebäudetechnik und im Gebäudemanagement (DOI:<a href="https://zenodo.org/record/7123785">10.5281/zenodo.7123785</a>)</li><li>Session #16: Christoph Imboden: Flexibility solutions - making the power grid fit for the future (DOI:<a href="https://zenodo.org/record/7123787">10.5281/zenodo.7123787</a>)</li><li>Session #17: Uwe Schulz: Spielerisches Sarnetz - Simulationen für die fossile Unabhängigkeit einer Ortschaft (DOI:<a href="https://zenodo.org/record/7123790">10.5281/zenodo.7123790</a>)</li><li>Session #18: Jana Koehler: Künstliche Intelligenz – Erfolg durch Erwünschtheit, Machbarkeit und Wirtschaftlichkeit (DOI:<a href="https://zenodo.org/record/7123792">10.5281/zenodo.7123792</a>)</li><li>Session #19: Rolf Kamps: KI in der Prävention - Befragungsmethoden und Schulungen trainieren, Krankheitserreger erkennen (DOI:<a href="https://zenodo.org/record/7123794">10.5281/zenodo.7123794</a>)</li><li>Session #20: Gwendolyne Pascua: Artificial Intelligence in Space - CIMON assisting astronauts on the International Space Station (DOI:<a href="https://zenodo.org/record/7123796">10.5281/zenodo.7123796</a>)</li><li>Session #21: Tobias Matter et.al.: Augmented Reality Soundscapes - mit maschinellem Lernen Klangkulissen von zukünftigen Bauvorhaben generieren (DOI:<a href="https://zenodo.org/record/7123798">10.5281/zenodo.7123798</a>)</li><li>Session #22: Angela Nicoara: Internet of Things - transforming businesses, people's lives and driving growth in the coming years (DOI:<a href="https://zenodo.org/record/7123800">10.5281/zenodo.7123800</a>)</li><li>Session #23: Adrian Koller: Feldrobotik - unermüdliche und zunehmend intelligentere Hilfe in der Landwirtschaft (DOI:<a href="https://zenodo.org/record/7123802">10.5281/zenodo.7123802</a>)</li><li>Session #24: Widar von Arx et.al.: Realisierung der Verkehrswende - Einfluss der Preispolitik in der Mobilität (DOI:<a href="https://zenodo.org/record/7124000">10.5281/zenodo.7124000</a>)</li><li>Session #25: Andreas Liebrich: Tourismusdateninfrastruktur - Was die Schweiz von Europa lernen kann (DOI:<a href="https://zenodo.org/record/7123806">10.5281/zenodo.7123806</a>)</li><li>Session #26: Frank Pöhlau und Stefan May: Find life on Mars - Schülerprojekte zur mobilien Robotik (DOI:<a href="https://zenodo.org/record/7123808">10.5281/zenodo.7123808</a>)</li><li><b>Session #27: Jiayun Shen: Open Innovation - Innovationsmanagement bei der Schweizerischen Post (<a href="#collapseTwo">Video</a>)</b></li><li>Session #28: Tobias Specker: Interkulturelles Management – innovative Konzepte zum Ausbau der China-Kompetenzen an Hochschulen (DOI:<a href="https://zenodo.org/record/7123812">10.5281/zenodo.7123812</a>)</li><li>Session #29: Elena Algorri: Swimming robots - exploring the unterwater from the surface (DOI:<a href="https://zenodo.org/record/7123814">10.5281/zenodo.7123814</a>)</li><li>Session #30: Sergio Camacho: Robotics and Digital Systems Engineering at the Tec de Monterrey (DOI:<a href="https://zenodo.org/record/7123816">10.5281/zenodo.7123816</a>)</li><li>Session #31: Thomas Dorn: Industrie 4.0 - Forschungskooperationen mit der CDHAW und der Tongji Universität Shanghai (DOI:<a href="https://zenodo.org/record/7123818">10.5281/zenodo.7123818</a>)</li><li>Session #32: Walter Reichert et.al.: Kollaboration und Unterstützung - Mobile Robotik und Exoskelette in der flexiblen Produktion (DOI:<a href="https://zenodo.org/record/7123820">10.5281/zenodo.7123820</a>)</li><li>Session #33: Louis Palmer: Solar Butterfly - climate pioneer world tour supported by HSLU (DOI:<a href="https://zenodo.org/record/7123822">10.5281/zenodo.7123822</a>)</li></ul><p></p>
CrossNet-Open-Unmix for Music Source Separation (X-UMXL)
<p>Weights of CrossNet-Open-Unmix (X-UMX) trained on the internal 100h dataset which is larger than <a href="https://sigsep.github.io/datasets/musdb.html">MUSDB18</a>, named X-UMX Large (X-UMXL). The weights can be used with <a href="https://github.com/asteroid-team/asteroid/tree/master/egs/musdb18/X-UMX">X-UMX on Asteroid (PyTorch)</a>. The details of X-UMX are described in <a href="https://ieeexplore.ieee.org/document/9414044">here</a>.</p>
Supplementary Data for "Adoption of Transparency and Openness Promotion (TOP) guidelines across journals"
<p>Supplementary data for: https://zenodo.org/record/7129250</p>
Data for "The APC-Barrier and its effect on stratification in open access publishing"
<p>Dataset to reproduce the analysis of the paper "The APC-Barrier and its effect on stratification in open access publishing". An earlier version of the manuscript with the title "The APC-Effect: Stratification in Open Access Publishing" is available at <a href="https://doi.org/10.31222/osf.io/w5szk">https://doi.org/10.31222/osf.io/w5szk</a>.</p> <p>Data is licensed under CC-BY-SA International (4.0), see the file LICENSE.</p> <p>A full description of the dataset is provided in the README.md.</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 9 April 2010
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 9 April 2010</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 14 January 2016
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 14 January 2016</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.