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8,537 results for “Openness”
Researcher views on Open Science
<p>Responses to a questionaire from a group of researchers on Open Science</p>
Monument the opening of Ueno Station
📍 [台東区, 東京都](https://scaniver.se/L35.71103,139.77517) Source: Objaverse 1.0 / Sketchfab
Journal based analysis of the Open Access Europe PMC articles.
<p>This file shows the 20 most-represented journals that tag data citations in the XML within articles in the Open Access set from Europe PMC (May 2013). Secondly, it shows the 20 most-represented journals according to number of individual articles, demonstrating that the journals that undertake tagging of data citations most frequently are not the same as those that occur most frequently.</p>
Open Turbulent Image Set (OTIS) Grayscale-PNG Version
<p>This the grayscale version of the OTIS dataset saved in PNG format</p>
Open Turbulent Image Set (OTIS) Color-PNG Version
<p>This the colored version of the OTIS dataset saved in PNG format</p>
Open Turbulent Image Set (OTIS) Grayscale-Matlab Version
<p>This the grayscale version of the OTIS dataset saved in Matlab format</p>
Open Turbulent Image Set (OTIS) Color-Matlab Version
<p>This the colored version of the OTIS dataset saved in Matlab format</p>
Nordic44 - 2015 Powerflow Data: An Open Data Repository of an Equivalent Nordic Grid Model Matched to Historical Electricity Market Data for 2015
<p>This repository is used to provide documentation related to the model and data development process, provide source (raw) data for the model in different forms (i.e. Modelica, CIM 14, and PSS/E) for an equivalent Nordic grid model that has been matched to historical power flow data.</p> <p>The repository is documented in the paper below, see [Ref00].</p> <p><strong>Using this model, data or related software = cite our publications!</strong></p> <p>We are happy to contribute with this dataset, however, if you use any of the data or software provided, we will appreciate if you cite the following publications, as follows:</p> <p>A) Cite that "the raw and processed data files corresponding to the model are available as an open data set and documented in [Ref00]."</p> <p>B) Cite that the first appearance of the model, i.e. "the model is first presented in [Ref01]"</p> <p>[Ref00] L. Vanfretti, S.H. Olsen, V. S. Narasimham Arava, G. Laera, A. Bibadafar, T. Rabuzin, H. Jackobsen, J. Lavenius, and M. Baudette, "An Open Data Repository and a Data Processing Software Toolset of an Equivalent Nordic Grid Model Matched to Historical Electricity Market Data," submitted for publication, Data in Brief, 2016.</p> <p>[Ref01] L. Vanfretti, T. Rabuzin, M. Baudette, M. Murad, iTesla Power Systems Library (iPSL): A Modelica library for phasor time-domain simulations, SoftwareX, Available online 18 May 2016, ISSN 2352-7110, http://dx.doi.org/10.1016/j.softx.2016.05.001.</p> <p><strong>Acknowledgment:</strong></p> <p>This model was originally developed in the context of the FP7 iTesla project, and further extended within the ITEA3 openCPSproject.</p> <p>Structure of the repository:</p> <p><strong>01_PSSE_Resources</strong>:</p> <ol> <li> <p><strong>Models</strong> :</p> <ul> <li> <p>A folder with PSS/E files of the base case</p> </li> <li> <p>A folder with a 7zip archive containing files of the original N44 system that has been modified to have the PSS/E base case</p> </li> </ul> </li> <li> <p><strong>Snapshots</strong> :</p> <ul> <li> <p><strong>N44_2015xxxx</strong> are folders named according to the day they refer to (for example <em>N44_20150401</em> refers to the 1st of April 2015). In each folder there are Excel files (<em>Consumption_xx.xlsx</em>, <em>Exchange_xx.xlsx</em>, <em>Production_xx.xlsx</em>) with data downloaded from Nord Pool website, an Excel file (<em>PSSE_in_out.xlsx</em>) summarizing the results from the Python script <em>Nordic44.py</em> in the folder <strong>04_Python_Resources</strong>, PSS/E snapshots for each hour before solving the power flow (<em>hx_before_PF.raw</em>) and after solving the power flow (<em>hx_after_PF.raw</em>)</p> </li> <li> <p><em>N44_BC.sav</em> is the PSS/E solved base case that Python script <em>Nordic44.py</em> (put the reference)</p> </li> </ul> </li> </ol> <p><strong>02_CIM14_Snapshots</strong>:</p> <ul> <li> <p><strong>N44_2015xxxx</strong> are folders named according to the day they refer to (e.g. <strong>N44_20150401</strong> refers to the 1st of April 2015). In each folder there are CIM files for each hour (<em>N44_hx_EQ.xml</em>, <em>N44_hx_SV.xml_, _N44_hx_TP.xml</em>)</p> </li> <li> <p><strong>N44_noOL_RDFIDMAP.xml</strong> is the file with IDs mapping of those cases (<em>N44_hx_noOL_EQ.xml</em>, <em>N44_hx_noOL_SV.xml</em>, <em>N44_hx_noOL_TP.xml</em>) with fixed overloading problems.</p> </li> <li> <p><strong>N44_RDFIDMAP_2015-1.xml</strong> and <strong>N44_RDFIDMAP_2015-2.xml</strong> are the files with IDs mapping of the remaining snapshots from 2015</p> </li> </ul> <p><strong>03_Modelica</strong>:</p> <ol> <li> <p><strong>iTesla_Platform</strong></p> <ul> <li> <p><strong>iPSL</strong> folder contains the version of the library which can be used to simulate snapshots generated from the iTesla Platform</p> </li> <li> <p><strong>Modelica_snapshots</strong> Modelica models generated from the snapshots by iTesla Platform</p> </li> </ul> </li> <li> <p><strong>SmarTSLab</strong></p> <ul> <li> <p><strong>OpenIPSL</strong> folder contains the version of the forked iPSL library which can be used to simulate the manually generated Modelica model of N44 with the record structures corresponding to the snapshots</p> </li> <li> <p><strong>Snapshots</strong> folder contains Modelica records automatically generated from the PSS/E records</p> </li> <li> <p><em>N44_Base_Case.mo</em> is the handmade N44 model with the loaded record of the power flow results from the PSS/E base case. It can be used to load other PF results from the folder <strong>03_Modelica/Snapshots</strong></p> </li> </ul> </li> </ol>
FIGURE 6. Pelonaia corrugata body ventrally opened A in Pelonaia quadrivena n. sp. a case of bipolarity in Ascidiacea
FIGURE 6. Pelonaia corrugata body ventrally opened A: without stain; B: stained with hemalum.
GitHub Open Source Survey 2017
<p>Data and accompanying documentation for the Open Source Survey fielded by GitHub and collaborators in 2017. Respondents were sourced via random sampling from traffic to licensed open source repositories on GitHub.com and from invitations sent to selected open source communities that work on other platforms. The files here include a README, a full copy of the (English) questionnaire, notes for working with the data, and two CSV data files. A report based on the subset of responses sampled from GitHub.com is available at http://opensourcesurvey.org/2017/. </p> <p>See the README for details on sampling methodology, and notes and questionnaire files for question wordings, response options, branching logic, and recoded variables. </p>
Open Science Austria 2017 - SPSS Rohdaten
<p><strong>Open Science in Austria 2017</strong></p> <p>Based on the hypothesis that the currently heated debate on Open Science is shaped by strategic action to preserve the prevailing power relations rather than mutual understanding based on free recognition and equality, it is assumed that the respective position of power held by scientists within the scientific field, has an impact on their attitude towards an opening of science and the practical application of Open Science principles in their daily work.</p> <p>To test this assumption, a quantitative online survey was conducted at eight Austrian universities (n=454) to ascertain each participating scientist’s position of power within the academic field. In a second step both the attitude of the participants toward seven predefined Open Science principles as well as their active application of these principles was empirically determined and analysed with regard to any possible correlation with their position of power.</p> <p> </p> <p>*this raw SPSS file contains all 454 data sets which were used for the evaluation</p> <p>** please note that incomplete questionnaires were not considered and have been deleted from this file </p>
Publishers of journals listed in the Directory of Open Access Journals (DOAJ)
<p>The file contains all publishers of journals listed in the Directory of Open Access Journals (DOAJ).</p> <p>On August 1, 2017, 9,621 journals were listed in the Directory of Open Access Journals (DOAJ). Only 32 publishers published more than 20 of these journals and thus have a quantitatively significant influence on Open Access. PLOS can not be found among them, but still has influence, but more qualitative than quantitative.</p> <p>These 32 publishers publish 2,950 journals, which are 31% of all journals listed in the DOAJ. At this date, the DOAJ reported 7,474 publishers, thus 0.43% of all DOAJ-listed publishers produced 31% of the journals.</p> <p>Of these 2,950 journals, 1,641 (56%) are in the hand of publishers who already dominate the market in the subscription model: e.g. Elsevier, Springer Nature (including BioMed Central, Frontiers), Wiley, SAGE, De Gruyter, Taylor & Francis, OUP, Wolters Kluwer).</p> <p>The data was gathered at August 1, 2017 using the Directory of Open Access Journals web interface. The total number of journals at this point of time was 9,621.</p>
Lauds Factories open data
Open data created inside the Lauds Factories project
Data Bundle for PyPSA-Eur: An Open Optimisation Model of the European Transmission System
<p><strong>PyPSA-Eur</strong> is an open model dataset of the European power system at the transmission network level that covers the full ENTSO-E area. It can be built using the code provided at <a href="https://github.com/PyPSA/PyPSA-eur">https://github.com/PyPSA/PyPSA-eur</a>.</p> <p><strong>It contains</strong> alternating current lines at and above 220 kV voltage level and all high voltage direct current lines, substations, an open database of conventional power plants, time series for electrical demand and variable renewable generator availability, and geographic potentials for the expansion of wind and solar power.</p> <p><strong>Not all data dependencies</strong> are shipped with the <a href="https://github.com/PyPSA/PyPSA-eur">code repository</a>, since git is not suited for handling large changing files. Instead we provide separate <strong>data bundles</strong> to be downloaded and extracted as noted in the <a href="https://pypsa-eur.readthedocs.io/en/latest/installation.html">documentation</a>.</p> <p>This is the <strong>full</strong> data bundle to be used for rigorous research. It includes large bathymetry and natural protection area datasets.</p> <p>While the <a href="https://github.com/PyPSA/PyPSA-eur">code</a> in PyPSA-Eur is released as free software under the MIT, <strong>different licenses and terms of use</strong> apply to the various input data, which are summarised below:</p> <p><strong>corine/*</strong></p> <ul> <li>CORINE Land Cover (CLC) database</li> <li><strong>Source:</strong> <a href="https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012/">https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012/</a></li> <li><strong>Terms of Use: </strong><a href="https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012?tab=metadata">https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012?tab=metadata</a></li> </ul> <p><strong>natura/*</strong></p> <ul> <li>Natura 2000 natural protection areas</li> <li><strong>Source:</strong> <a href="https://www.eea.europa.eu/data-and-maps/data/natura-10">https://www.eea.europa.eu/data-and-maps/data/natura-10</a></li> <li><strong>Terms of Use:</strong><a href="https://www.eea.europa.eu/data-and-maps/data/natura-10#tab-metadata"> https://www.eea.europa.eu/data-and-maps/data/natura-10#tab-metadata</a></li> </ul> <p><strong>gebco/GEBCO_2014_2D.nc</strong></p> <ul> <li>GEBCO bathymetric dataset</li> <li><strong>Source:</strong> <a href="https://www.gebco.net/data_and_products/gridded_bathymetry_data/version_20141103/">https://www.gebco.net/data_and_products/gridded_bathymetry_data/version_20141103/</a></li> <li><strong>Terms of Use: </strong><a href="https://www.gebco.net/data_and_products/gridded_bathymetry_data/documents/gebco_2014_historic.pdf">https://www.gebco.net/data_and_products/gridded_bathymetry_data/documents/gebco_2014_historic.pdf</a></li> </ul> <p><strong>je-e-21.03.02.xls</strong></p> <ul> <li>Population and GDP data for Swiss Cantons</li> <li><strong>Source:</strong> <a href="https://www.bfs.admin.ch/bfs/en/home/news/whats-new.assetdetail.7786557.html">https://www.bfs.admin.ch/bfs/en/home/news/whats-new.assetdetail.7786557.html</a></li> <li><strong>Terms of Use: <br></strong></li> <li><a href="https://www.bfs.admin.ch/bfs/en/home/fso/swiss-federal-statistical-office/terms-of-use.html">https://www.bfs.admin.ch/bfs/en/home/fso/swiss-federal-statistical-office/terms-of-use.html</a></li> <li><a href="https://www.bfs.admin.ch/bfs/de/home/bfs/oeffentliche-statistik/copyright.html">https://www.bfs.admin.ch/bfs/de/home/bfs/oeffentliche-statistik/copyright.html</a></li> </ul> <p><strong>nama_10r_3popgdp.tsv.gz</strong></p> <ul> <li>Population by NUTS3 region</li> <li><strong>Source:</strong> <a href="http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nama_10r_3popgdp&lang=en">http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nama_10r_3popgdp&lang=en</a></li> <li><strong>Terms of Use:</strong></li> <li><a href="https://ec.europa.eu/eurostat/about/policies/copyright">https://ec.europa.eu/eurostat/about/policies/copyright</a></li> </ul> <p><strong>GDP_per_capita_PPP_1990_2015_v2.nc</strong></p> <ul> <li>Gross Domestic Product per capita (PPP) from years 1999 to 2015</li> <li>Rectangular cutout for European countries in PyPSA-Eur, including a 10 km buffer</li> <li>Kummu et al. "Data from: Gridded global datasets for Gross Domestic Product and Human Development Index over 1990-2015"</li> <li><strong>Source:</strong> https://doi.org/10.1038/sdata.2018.4 and associated dataset https://doi.org/10.1038/sdata.2018.4</li> </ul> <p><strong>ppp_2019_1km_Aggregated.tif</strong></p> <ul> <li>The spatial distribution of population in 2020: Estimated total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 30 arc (approximately 1km at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel. The mapping approach is Random Forest-based dasymetric redistribution.</li> <li>Rectangular cutout for non-NUTS3 countries in PyPSA-Eur, i.e. MD and UA, including a 10 km buffer</li> <li>WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00647</li> <li><strong>Source:</strong> https://data.humdata.org/dataset/worldpop-population-counts-for-world and https://hub.worldpop.org/geodata/summary?id=24777</li> <li><strong>License: </strong>Creative Commons Attribution 4.0 International Licens</li> </ul> <p><strong>data/bundle/era5-HDD-per-country.csv</strong></p> <p>- Link: https://gist.github.com/fneum/d99e24e19da423038fd55fe3a4ddf875<br>- License: CC-BY 4.0<br>- Contains country-level heating degree days in Europe for<br> 1941-2023. Used for rescaling heat demand in weather years not covered by<br> energy balance statistics.</p> <p><strong>data/bundle/era5-runoff-per-country.csv</strong></p> <p>- Link: https://gist.github.com/fneum/d99e24e19da423038fd55fe3a4ddf875<br>- License: CC-BY 4.0<br>- Contains country-level daily sum of runoff in Europe for<br> 1941-2023. Used for rescaling hydro-electricity availability in weather years<br> not covered by EIA hydro-generation statistics.</p> <p><strong>shipdensity_global.zip</strong></p> <ul> <li>Global Shipping Traffic Density</li> <li>Creative Commons Attribution 4.0</li> <li><a href="https://datacatalog.worldbank.org/search/dataset/0037580/Global-Shipping-Traffic-Density">https://datacatalog.worldbank.org/search/dataset/0037580/Global-Shipping-Traffic-Density</a></li> </ul> <p><strong>seawater_temperature.nc</strong></p> <ul> <li>Global Ocean Physics Reanalysis</li> <li>Seawater temperature at 5m depth</li> <li>Link: https://data.marine.copernicus.eu/product/GLOBAL_MULTIYEAR_PHY_001_030/services</li> <li>License: https://marine.copernicus.eu/user-corner/service-commitments-and-licence</li> </ul> <p><strong>hera_be_2013-03-01_to_2013-03-08.zip</strong></p> <ul> <li>Tilloy, A., Paprotny, D., Luc, F., Grimaldi, S., Goncalo, G., Hylcke, B., Lange, S., Bianchi, A. (2024): HERA: a high-resolution pan-European hydrological reanalysis (1950-2020).</li> <li>6-hourly river discharge and ambient temperature for 2019 at 1-arc minute spatial resolution. Subset to the PyPSA-Eur test cutout (2013-03-01 to 2013-03-08 for longitude 1.5 to 7 and latitude 49 to 52)</li> <li>Link: <a href="https://publications.pik-potsdam.de/pubman/faces/ViewItemOverviewPage.jsp?itemId=item_29543">https://publications.pik-potsdam.de/pubman/faces/ViewItemOverviewPage.jsp?itemId=item_29543</a></li> <li>License: <a href="https://data.jrc.ec.europa.eu/licence/com_reuse">https://data.jrc.ec.europa.eu/licence/com_reuse</a></li> </ul>
Assets for "A Systematic Technology Review of General-Purpose Open-Source TOSCA Orchestrators"
<p>These datasets contain the results of a systematic technology review of general-purpose open-source TOSCA orchestrators that we conducted in order to support organizations in selecting a suitable TOSCA orchestrator: </p> <ul> <li>Definition of the TOSCA Orchestrator Classification Framework</li> <li>List of all identified TOSCA orchestrator </li> <li>Classification data of selected TOSCA orchestrators</li> </ul>
Maintaining an open landscape: a 15-year multi-site experiment comparing seven management methods for semi-natural grasslands
<p>The data and publications presented here stems from a field trial started in Sweden ca 1972 (at one site still running in 2023). The purpose of the trial was to compare traditional management of semi-natural grasslands by grazing or annual mowing with five alternative management methods. At <strong>e</strong>leven locations in southern Sweden, block experiments were conducted evaluating seven treatments in 5 m * 20 m plots: grazing, annual mowing, annual spring burning, mowing every third year, mechanical removal of woody plants, herbicide control of woody plants, and untreated control. After approximately 13 years, trends for woody plants and species richness, and the occurrence of management-dependent plant species, low-grown species, and pollinator-attracting plant species were analysed. Overall, the annual mowing and grazing treatments resulted in fewer woody plants, the highest species richness, and more management-dependent, low-grown, and pollinator-attracting species. The untreated control plots showed the opposite effect, whereas less intense management (annual burning, mowing every third year, and mechanical and chemical treatments of woody plants) showed mixed and often intermediate effects. </p><p>On this ZENODO-page, one can find all the orginal publication, most in Swqedish. An article summarizing much of results can be found here: <a href="https://doi.org/10.1016/j.gecco.2023.e02721">https://doi.org/10.1016/j.gecco.2023.e02721</a></p>
OpenSCV: An Open Hierachical Taxonomy for Smart Contract Vulnerabilities – Supplemental Material
<p>Dataset and other supplemental material.</p>
Open Access Resources
<p>Data analysis from from DOAJ, DOAB, OpenDOAR, re3Data, CWTS Leiden Ranking (2023)</p>
Open Shelves
<p>Open Shelves is an open source computer vision project to identify book spines.</p> <p>The dataset for this project is hosted on Roboflow. <a href="https://universe.roboflow.com/capjamesg/open-shelves" rel="nofollow">You can also try all models</a> that have been trained with this dataset on Roboflow.</p> <p>You can use this dataset to train vision models to identify bookshelves.</p> <p>This dataset was designed to improve the <a href="https://jamesg.blog/2024/02/14/clickable-bookshelves/" rel="nofollow">clickable bookshelves</a> (<a href="https://github.com/capjamesg/cv-book-svg">source code</a>) project. A key limitation of the project was the foundation models on which it depends, Grounding DINO and Segment Anything, require signifiant computational resources to run, particularly on large numbers of images. With Open Shelves, a fine-tuned model can be trained that is faster than the Grounding DINO and Segment Anything combination.</p>
Deep carbon cycling in subduction zones: 1. Coupled thermo-metamorphic-dissolution model in open versus closed system
Open the record for dataset details and reuse information.
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.