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3,172 results for “public”
Research Scholars Workshop: Non-Traditional Scholarly Publication
<p>Not all scholarly work is published in a research journal. You may be interested in preparing editorials, standard operating procedures, books or book chapters, or internally published research (e.g., FAA or DoD research). This session will start with an overview of non-traditional publication options and then will separate into small groups to explore each further with faculty who have experience with these types of non-traditional scholarly publications. </p>
nuMIDAS public use cases data
<p>This data set contains all public data related to the use cases that were deployed in the nuMIDAS Horizon 2020 project during 2022 an 2023.</p> <p>For reasons of privacy, we have only provided data from the following use cases:</p> <ul> <li>UC1 (Pre-planning of shared mobility services)</li> <li>UC2 (Operative areas analysis)</li> <li>UC4 (Planning for parking)</li> <li>UC6 (Assessment of traffic management scenarios)</li> </ul> <p><em>UC3 (Air quality analysis and forecasting) and UC5 (Inflows and outflows in a metropolitan area) are as such not available due to private data.</em></p> <p>For more information, please refer to the public deliverables at <a href="https://www.numidas.eu/.">https://www.numidas.eu/.</a></p>
Large-eddy simulation source code and data for (LS)2D reference publication in JAMES.
<p>This archive contains the MicroHH large-eddy simulation source code, the (LS)2D source code, and all simulation input and statistics, used for the publication:</p> <p><em>"The Benefits and Challenges of Downscaling a Global Reanalysis with Doubly-Periodic Large-Eddy Simulations" </em>by B.J.H. van Stratum et al.</p>
Supplementary Data for the publication "High economic costs of reduced carbon sinks and declining biome stability in Central American forests"
<p>Supplementary data from the DGVM simulations underlying the main figures presented in the publication.</p> <p>Naming convention: {variable}_{aggregation period}-{comparison period [only relevant for bsprob]}_{climate model}-{climate scenario}.tif</p> <p>Variables are:</p> <ul> <li>bsprob-Snell2013ed = biome shift probability (biomization adjusted from Snell et al. 2013) [%]</li> <li>nee = net ecosystem exchange [kgC/m2/year]</li> </ul> <p>Global climate models include GFDL = GFDL-ESM4 and IPSL= IPSL-CM6A-LR. Climate scenarios refer to the shared socioeconomic pathways (SSP) SSP126= SSP1-2.6 and SSP370= SSP3-7.0.</p>
Supplementary data to publication "Abomasal infusion of essential fatty acids and conjugated linoleic acid during late pregnancy and early lactation affects immunohematological and oxidative stress markers in dairy cows"
<p>Supplementary data to publication "Abomasal infusion of essential fatty acids and conjugated linoleic acid during late pregnancy and early lactation affects immunohematological and oxidative stress markers in dairy cows" in Journal of Dairy Science; DOI: <a href="https://doi.org/10.3168/jds.2022-22514">https://doi.org/10.3168/jds.2022-22514</a></p>
Raw SP-ICP-MS data for the publication "Vertical distribution of inorganic nanoparticles in a Norwegian fjord"
<p>The compressed archive contains SP-ICP-MS data to reproduce results for the paper "Vertical distribution of inorganic nanoparticles in a Norwegian fjord"". F4 in the sample name denotes the outer station, F2 denotes the inner station. The suffix integer (1-6) indicates the depth position, lowest numbers nearest bottom. The letter A denotes acidified sampling, N neutral sampling. The data consists of integer intensity versus time data in .csv-format.</p> <p>The remaining data to produce all other results, visualizations and statistics for the paper is included in the supplementary or GitHub. Associated code is deposited in a GitHub repository, github.com/arebruvold/fordefjorden_distribution. Note that these data may have different licenses:</p> <ul> <li>The excel file "total_metals.xlsx" contains the total metal data.</li> <li>"sjovann_partikler_noytral.xls" and "sjovann_minste_partikler_2.xls" contains quantitative SEM-EDS data.</li> <li>"204473_F4.txt" and "204473_F2.txt" contains CTD data for salinity and temperature.</li> <li>"dens_comps_large.csv" and "dens_comps_large.csv" contain the particle compositions used for particle size calculations.</li> </ul>
Dataset corresponding to the publication: Friction and slip measured at the bed of an Antarctic ice stream
<p>The following data is included here, which comprises the data presented in the publication:<br> Hudson, T. S., Kufner, S., Brisbourne, A. M., Kendall, J., Smith, A. M., Arthern, R., & Alley, R. (2023). Friction and slip measured at the bed of an Antarctic ice stream. Nature Geoscience.</p> <p>Files included are:<br> all_icequakes_2018to2019.csv - A catalogue of the icequakes used in the study.<br> cluster_????.csv - csv files containing the results for each icequake, grouped by cluster (i.e. one csv file per cluster).<br> slip_rate_movie.mp4 - A movie of slip-rate for each icequake through time.</p> <p>Headers for the files are as follows:<br> ------------------------------------- all_icequakes_2018to2019.csv file -------------------------------------<br> origin_time - Origin time of icequake, in UTC time.<br> Mw - Moment magnitude.<br> Mw_err - Error in Mw.<br> fc - Corner frequency (Hz).<br> fc_err - Error in corner frequency.<br> Q - Quality factor (measure of attenuation).<br> Q_err - Error in Q.<br> inter-event_time_s - Inter-event time between this icequake and the previous icequake (s).<br> stress_drop - Stress-drop of icequake (Pa).<br> stress_drop_err - error in stress-drop.<br> lat - Latitude (decimal degrees).<br> lon - Longitude (decimal degrees).<br> x (km) - x grid location (km).<br> y (km) - y grid location (km).<br> z (km bsl) - Depth (km bsl).<br> x_err (km) - Error in x (km).<br> y_err (km) - Error in y (km).<br> z_err (km) - Error in z (km).</p> <p>------------------------------------- cluster_XXXX.csv file -------------------------------------<br> mean_Mw - Mean moment magnitude for icequake from all receivers.<br> mean_fc - Corner frequency for icequake from all receivers (Hz).<br> stdev_Mw - Standard deviation in Mw.<br> stdev_fc - Standard deviation in corner-frequency.<br> mean_Q - Mean Q for icequake from all receivers.<br> stdev_Q - Standard deviation in Q.<br> n_obs - Number of receivers used to calculate above means.<br> lat - Latitude of icequake.<br> lons - Longitude of icequake.<br> depths - Depth of icequake (km bsl).<br> x - x location of icequake (km).<br> y - y location of icequake (km).<br> zs - z location of icequake (km bsl).<br> origin_time - Origin time of icequake (UTC time).<br> origin_time_days - Origin time in days relative to 1st January 2019 (days).<br> inter-event_time_s - Inter-event time from previous to current event (s).<br> stress_drop - Stress drop (Pa)<br> uncertainty_stress_drop - Uncertainty in stress-drop.<br> M_0 - Seismic moment release (Nm).<br> uncertainty_M_0 - Uncertainty in M_0.<br> fault_radius_m - Fault radius, in metres.<br> uncertainty_fault_radius_m - Uncertainty in fault radius (m).<br> slip_ice_m - Slip in the ice (m).<br> slip_till_m - Slip in the till (m).<br> uncertainty_slip_ice_m - Uncertainty in slip_ice_m.<br> uncertainty_slip_till_m - Uncertainty in slip_till_m.<br> RSF_v/v_0 - v/v_0 calculated for the rate-and-state model.<br> RSF_sigma - Normal stress calculated for the rate-and-state model (Pa).<br> RSF_tau - Shear-stress calculated for the rate-and-state model (Pa).<br> uncertainty_RSF_v/v_0 - Uncertainty in RSF_v/v_0.<br> uncertainty_RSF_sigma - Uncertainty in RSF_sigma.<br> uncertainty_RSF_tau - Uncertainty in RSF_tau.<br> RSF_G* - Effective shear-modulus calculated for the rate-and-state model (Pa).<br> RSF_Gb - Bed shear modulus calculated for the rate-and-state model (Pa).<br> RSF_slip_m - Slip calculated for the rate-and-state model (Pa).<br> uncertainty_RSF_G* - Uncertainty in RSF_G*.<br> uncertainty_RSF_Gb - Uncertainty in RSF_Gb.<br> uncertainty_RSF_slip_m - Uncertainty in RSF_slip_m.</p>
Simulation data and code used for the publication in Magn. Reson. "Time-domain proton-detected local-field NMR for molecular structure determination in complex lipid membranes"
<p>Simulation data used in the publication Magn. Reson. "Time-domain proton-detected local-field NMR for molecular structure determination in complex lipid membranes". The simulation data set, and the code developed to generate such data, are included. Details in the published paper </p>
List of multinational publishers of serial publications established by the ISSN Network (PDF format)
<p>The ISSN International Centre and the ISSN Network of nearly 100 national centres around the world are authorized by the International Organization for Standardization (ISO) to implement serial identification according to the terms of ISO3297:2022 standard.<br> The ISSN Network serves publishers who wish to uniquely identify their serial publications. These publishers contact the National Centres of the countries where they are located. When there is no national centre, they contact the ISSN International Centre.<br> The place of publication determines the ISSN Centre responsible for identification. However, when a publisher operates in several countries, an agreement may be reached between this multinational publisher and the involved ISSN Centres so that all requests for identification are handled by one centre.<br> The following list identifies more than 300 multinational publishers. These publishers have been identified through the ISSN Portal (https://portal.issn.org) data. The ISSN International Centre works with the National Centres on this list of publishers to determine their responsibility for identifying the publications of these publishers.<br> The list also contains information on the names by which these publishers are known and a mapping of links between publishers. It also contains a link to the ISNI and VIAF databases in which these publishers are also recorded. This data is managed by the ISSN Network in an internal wiki that will be updated regularly.<br> The ISSN Network makes this list available to the publishing community and to librarians. They can contact the ISSN International Centre to share comments (additions, modifications, deletions) on this list which will be published quarterly.</p>
Figure |. Accumulation of species / publication year for the tribe Zammarini, since Distant recognized the tribe in 1905. in A historical overview of the classification of the Neotropical tribe Zammarini (Hemiptera, Cicadidae) with a key to genera
Figure |. Accumulation of species / publication year for the tribe Zammarini, since Distant recognized the tribe in 1905.
Supporting data for the publication "Emission ensemble approach to improve the development of multi-scale emission inventories"
<p>This dataset includes the source IDL code as well as the three emission inventory aggregated emission datasets necessary to perform the analysis presented in the publication: "Emission ensemble approach to improve the development of multi-scale emission inventories (GMD)"</p>
Data example and code used in the publication "Is transport of microplastics different from that of mineral dust? Results from idealized wind tunnel studies"
<p>Background</p> <p>The code labels microspheres and counts them. Further, the code determines which microspheres are independent of microsphere-microsphere collisions by their relative position to the other microspheres in an image. Images were taken with a full-frame visual camera (Sony Alpha 7RII) with a long-distance-microscopy lens (K2 DistaMax).</p> <p>Description of the dataset</p> <ul> <li>image_data_all.zip contains 228 tif-format images taken in a single experiment <ul> <li>the images show borosilicate microspheres with diameters from 63 to 75 µm</li> <li>during the experiment, the microspheres are detached from the substrate and are transported out of the image</li> </ul> </li> <li>functions_particle_labeling.jl contains all necessary functions for particle labeling</li> <li>analysis_protocol.jl is an example, that first determines a color threshold, and then labels all microspheres in all images stored in "image_data_all/substrate_a/image_data_single_experiment"</li> <li>post_processing_visualisation.R is an r-script, that reads the output of analysis_protocol.jl and demonstrates how logistic functions were fitted to the data</li> </ul> <p> </p> <p>We used julia 1.8.5 and R 4.3.0.</p> <p> </p>
EUR publication package example
<p>This publication package serves as an example for how a publication package could look like based on the <a href="https://doi.org/10.5281/zenodo.7583831">Guideline for the archiving of academic research for Faculties of Behavioural and Social Sciences in the Netherlands</a> (but might be useful for other disciplines and countries as well).<br> Dataset used in this example is the <a href="https://doi.org/10.6084/m9.figshare.6262019.v4">SAFI Survey Results</a> dataset. The original dataset was generated by Philip Woodhouse, Gert Jan Veldwisch, Daniel Brockington, Hans C. Komakech, Angela Manjichi, Jean-Philippe Venot</p>
[HECAT] [ETAPAS] [TECHETHOS] Policy Launch: Public Service AI /// Trust – Values – Accuracy
<p><strong>Public Service AI /// Trust – Values – Accuracy</strong></p> <p><strong>Policy Launch 26.05.23 11:00 CET Zoom</strong></p> <p><strong>YouTube Link to POLICY LAUNCH Recording: </strong><a href="https://youtu.be/OqkqUbA-6PI">https://youtu.be/OqkqUbA-6PI</a></p> <p><strong>Policy 1 – HECAT Project </strong> <a href="https://zenodo.org/record/7921614">“Algorithm Profiling in Public Employment Services; Reporting Standards”</a></p> <p><strong>Policy 2 – ETAPAS Project </strong> <a href="https://zenodo.org/record/7634617#.ZFIf7ezMKt_">“ETAPAS AND ALTAI – Two European Trustworthy AI Assessment Methodologies”</a></p> <p><strong>Policy 3 – TechEthos Project </strong><a href="https://www.techethos.eu/wp-content/uploads/2023/03/TECHETHOS_Policy-Brief_XR-General-purpose-AI_final.pdf">“XR and General Purpose AI: From Values and Principals to Norms and Standards”</a></p>
BioNames persistent identifiers for taxonomic names and publications
<p>Linked data for taxonomic names in BioNames linked to publications of those names. Triples use terms from http://schema.org vocabulary, taxonomic names identified by Life Science Identifiers, publications identified with DOIs.</p>
Index Fungorum persistent identifiers for taxonomic names and publications
<p>Linked data for taxonomic names in Index Fungorum linked to publications of those names. Triples use terms from http://schema.org vocabulary, fungal names identified by Life Science Identifiers, publications identified with DOIs.</p>
Public dataset about students' leadership competence
<p>Public dataset about students' leadership competence. The evidence consists of the activities and responsibilities of shared leadership. 40 work teams and 237 students participated in this research work. The subject in which the experience was carried out was “Fundamentals of Programming” in the first year and first semester of the Biotechnology degree at the Technical University of Madrid. The data was collected during the 2019-2020 academic year (pre-Covid-19 Pandemic); 15 teams and 90 students participated face-to-face (37.11% male and 62.89% female). In the 2020-2021 academic year (Covid-19 Pandemic), 12 teams and 70 students participated online (34.78% male and 65.22% female). During the 2021-2022 academic year (post-Covid-19 Pandemic), 13 teams and 77 students participated in person (41.03% male and 58.97% female). All the research was carried out in compliance with the standards defined by the Ethical Committee of the Technical University of Madrid.</p>
Dataset associated with publication "Direct observation of coherence transfer and rotational-to-vibrational energy exchange in optically centrifuged CO2 super-rotors" to be published in Nature Communications
<p>This dataset contains all data to compose figures in the associated manuscript. Some of the images are presented in MatLab .mat files. If a different format is needed, please contact the corresponding author. </p>
Qualitative review data of Indian Public Sector Banks' qualitative review data
<p>This data is very useful in text mining. This data s useful for identifying key service quality dimensions for mobile banking apps using text mining.</p>
Dataset accompanying the publication "Transport and retention of micro-Polystyrene in coarse riverbed sediments: Effects of flow velocity, particle and sediment sizes"
<p>The dataset in this repository is accompanying the publication "Transport and retention of micro-Polystyrene in coarse riverbed sediments: Effects of flow velocity, particle and sediment sizes" (in Microplastics and Nanoplastics, 2023, submitted 09.06.2023)</p> <p>The repository contains the raw image files of all sample filters which were scanned using the fluorescence imaging system ChemiDoc and used to analyse the infiltration behaviour of microplastic polystyrene in the manuscript. In addition, we provide the resulting data from the particle identification and geometric analysis which were derived from the raw data using ImageJ in tabular excel format. The data is structured in folders following the naming of the columns from the manuscript.</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.