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747 results for “Open Data”
Input data for the OnStove Nepal model "AAchieving Nepal's clean cooking ambitions: an open source and geospatial cost–benefit analysis"
<p>This repository includes input data to run the OnStove Nepal model presented in the paper "<strong>Achieving Nepal's clean cooking ambitions: an open source and geospatial cost–benefit analysis</strong>" DOI: <a href="https://doi.org/10.1016/S2542-5196(24)00209-2">https://doi.org/10.1016/S2542-5196(24)00209-2</a>.</p> <p>The code and automated workflow to run the model can be found in the Github repository <a href="https://github.com/Open-Source-Spatial-Clean-Cooking-Tool/OnStove-Nepal">https://github.com/Open-Source-Spatial-Clean-Cooking-Tool/OnStove-Nepal</a>. All result files and figures can be downloaded from the permanent repository <a href="https://doi.org/10.5281/zenodo.10643983">https://doi.org/10.5281/zenodo.10643983</a>.</p> <p>The "<strong>GIS_input_data/</strong>" directory includes all the geospatial datasets needed to run the model. Each dataset folder contains a Source.md file describing the dataset, source, attribution, and license. To run the model extract the data inside your "<strong>1. Data</strong>"<strong> </strong>folder in your project. </p> <p>The "<strong>Scenario_inputs/</strong>" directory includes the CSV files with the input socio- and techno-economic data for the different scenarios. Sources for the socio- and techno-economic data can be found in the <strong>supplementary material</strong> of the related publication in the link <a href="https://doi.org/10.1016/S2542-5196(24)00209-2">https://doi.org/10.1016/S2542-5196(24)00209-2</a>. To run the model extract the scenario data inside your "<strong>2. Scenario inputs</strong>"<strong> </strong>folder in your project. </p>
Scripts, Data, and Figures for "MesoHOPS: Size-invariant scaling calculations of multi-excitation open quantum systems"
<div> <p>This archive contains the scripts required to run all calculations presented in "MesoHOPS: Size-invariant scaling calculations of multi-excitation open quantum systems," the figure generation scripts and attendant processed data, and a copy of MesoHOPS version 1.4.0, as used in the paper.</p> </div>
Thermochemical Data for Furan-based Monomer Candidates for Frontal Ring-Opening Metathesis Polymerization (FROMP)
<p>This dataset includes 471 furan-based monomer candidates for frontal ring-opening metathesis polymerization (FROMP) and relevant thermochemistry as calculated with density functional theory (DFT). The monomer candidates were combinatorically enumerated using Diels-Alder reactions of furan derivatives as dienes and four types of dienophiles (alkenes, alkynes, allenes, and benzynes). Common substituents were enumerated for the dienophile classes, and methyl substitution on the diene was explored. We used the SMILES arbitrary target specification (SMARTS) language to produce monomers and ring-opened structures from diene and dienophile precursor SMILES, and we studied the ring-opening reaction using a homodesmotic equation with ethene. RDKit conformers were initially generated from SMILES, then optimized with GFN2-xTB. The two conformers lowest in energy were then optimized with DFT using the wb97x-D3 functional, def2-TZVP basis set, and def2/J auxiliary basis set. Gibbs free energy corrections were obtained through frequency calculations. Structures with imaginary frequencies below -50 cm^{-1} were excluded from this work, and smaller imaginary modes were flipped to be positive for free energy calculations. Modes below 50 cm^{-1} were treated with the modified rigid rotor approximation, and all thermochemical values were calculated at T=200C. The CSV file contains the monomer SMILES, the free energy of reaction for Diels-Alder addition (G_DA_200), and the enthalpy of the ring-opening reaction (H_RO_200). All energies are given in kcal/mol. An interactive HTML is also included to visualize the monomers in this dataset.</p>
RAYUELA - Open Data (small) Preliminary Pilots - Data collected through a serious game created to identify patterns and profiles of young potential victims/perpetrators of cybercrimes.
<p>The data of this dataset have been collected in the pilots carried out by the RAYUELA project in different countries of the European Union. The participants are minors and the game sessions have been carried out in schools and summer camps in a supervised way.</p> <p>This is the first version of a larger dataset: https://doi.org/10.5281/zenodo.10604760</p>
Solution-processed PbS quantum dot infrared laser with room-temperature tuneable emission in the optical telecommunications window - Open Data
<p>This is a supplementary upload attached to the paper titled "Solution-processed PbS quantum dot infrared laser with room-temperature tuneable emission in the optical telecommunications window" 10.1038/s41566-021-00878-9.</p> <p><strong>Figures</strong></p> <p>All figure data from the publication can be obtained from the original MATLAB .fig files. If one does not have access to MATLAB the figures can be opened using the open source software GNU Octave.</p> <p><strong>FDFD Simulation</strong></p> <p>Also in the upload is the original matlab code used to perform the simulations presented in the paper.</p> <p>"FDFD_2D_Ez_Hz_DFB_laser_UPLOAD" - Variable gain FDFD solver is uploaded as .mat and .pdf files.</p> <p>To run the code the functions "Dgen" and "gen2xDFB" are required and the .mat files containing the refractive indices "PbS1520" and "Al2O3".</p> <p>Parameters to vary can be found in the "DASHBOARD" section of the code. The uploaded code solves for the out-of-plane electric field (Ez Mode).</p>
Data supporting the Master thesis "Monitoring von Open Data Praktiken - Herausforderungen beim Auffinden von Datenpublikationen am Beispiel der Publikationen von Forschenden der TU Dresden"
<p>Data supporting the Master thesis "Monitoring von Open Data Praktiken - Herausforderungen beim Auffinden von Datenpublikationen am Beispiel der Publikationen von Forschenden der TU Dresden" (Monitoring open data practices - challenges in finding data publications using the example of publications by researchers at TU Dresden) - Katharina Zinke, Institut für Bibliotheks- und Informationswissenschaften, Humboldt-Universität Berlin, 2023</p> <p>This ZIP-File contains the data the thesis is based on, interim exports of the results and the R script with all pre-processing, data merging and analyses carried out. The documentation of the additional, explorative analysis is also available. The actual PDFs and text files of the scientific papers used are not included as they are published open access.</p> <p>The folder structure is shown below with the file names and a brief description of the contents of each file. For details concerning the analyses approach, please refer to the master's thesis (publication following soon).</p> <p>## Data sources </p> <p>Folder 01_SourceData/</p> <p>- PLOS-Dataset_v2_Mar23.csv (PLOS-OSI dataset)</p> <p>- ScopusSearch_ExportResults.csv (export of Scopus search results from Scopus)</p> <p>- ScopusSearch_ExportResults.ris (export of Scopus search results from Scopus)</p> <p>- Zotero_Export_ScopusSearch.csv (export of the file names and DOIs of the Scopus search results from Zotero)</p> <p>## Automatic classification </p> <p>Folder 02_AutomaticClassification/</p> <p>- (NOT INCLUDED) PDFs folder (Folder for PDFs of all publications identified by the Scopus search, named AuthorLastName_Year_PublicationTitle_Title) </p> <p>- (NOT INCLUDED) PDFs_to_text folder (Folder for all texts extracted from the PDFs by ODDPub, named AuthorLastName_Year_PublicationTitle_Title)</p> <p>- PLOS_ScopusSearch_matched.csv (merge of the Scopus search results with the PLOS_OSI dataset for the files contained in both)</p> <p>- oddpub_results_wDOIs.csv (results file of the ODDPub classification)</p> <p>- PLOS_ODDPub.csv (merge of the results file of the ODDPub classification with the PLOS-OSI dataset for the publications contained in both)</p> <p>## Manual coding </p> <p>Folder 03_ManualCheck/</p> <p>- CodeSheet_ManualCheck.txt (Code sheet with descriptions of the variables for manual coding)</p> <p>- ManualCheck_2023-06-08.csv (Manual coding results file)</p> <p>- PLOS_ODDPub_Manual.csv (Merge of the results file of the ODDPub and PLOS-OSI classification with the results file of the manual coding)</p> <p>## Explorative analysis for the discoverability of open data<br> <br>Folder04_FurtherAnalyses </p> <p>Proof_of_of_Concept_Open_Data_Monitoring.pdf (Description of the explorative analysis of the discoverability of open data publications using the example of a researcher) - in German</p> <p>## R-Script </p> <p>Analyses_MA_OpenDataMonitoring.R (R-Script for preparing, merging and analyzing the data and for performing the ODDPub algorithm)</p>
Data and scripts for the publication "A case for open communication of bugs in climate models"
<p>Primary data and scripts for the publication "A case for open communication of bugs in climate models" (submitted to GMDD as EGUSPHERE-2024-3493)</p>
The OpenITI Self-reuse Data
<p>This data set pertains to the OpenITI <a href="https://zenodo.org/records/10007820">2023.1.8 release</a> of the corpus and the corresponding <a href="https://zenodo.org/records/11501559">passim run</a>. The data will be analysed by Sarah Bowen Savant in a forthcoming monograph under contract with Edinburgh University Press.</p>
Data from "The academic impact of Open Science: a scoping review"
<p>These files include the data from the "The societal impact of Open Science - a scoping review", part of a series of studies conducetd within the PathOS Horizon Europe project on the academic, economic, and societal impacts of Open Science. This study was conducted in two phases. In phase 1 an academic database search was conducted. For phase 2 an automatic snowball search was performed based on results from phase 1 ( and grey literature was searched manually.</p> <p>The upload contains five files:</p> <ol> <li>Main file with extracted information for the 485 studies included in the review ("academic_impact_included_all_data.csv").</li> <li>Excel file documenting the grey literature search ("Grey_Literature_Search.xlsx").</li> <li>R project for the snowball search ("academic_impact_snowball.zip").</li> <li>R project for cleaning data and producing summaries and figures ("academic_impact_stats.zip").</li> <li>Excel file mapping the frascati codes used in file (1) to their textual representations ("Frascati definitions.xlsx")</li> </ol> <p>For more details on the methods see the <a href="https://osf.io/m4rnc">protocol</a> and its <a href="https://osf.io/3b6xj">addendum</a>. For the background, results and discussion see the <a href="../records/7883699">deliverable</a> (reporting on phase 1) and the pre-print.</p>
The macroeconomic determinants of trade openness in Latin American countries: A panel data analysis
<p><strong><span>Background:</span></strong><span> Trade openness shows a positive impact on economic growth, supported by economic theory, and export diversification and economic complexity show a positive dynamic in trade openness in the world; however, a specificity is generated in South American countries. Therefore, the objective of the research is to analyse the macroeconomic determinants of trade openness in Latin American countries.</span></p> <p><strong><span>Methods: </span></strong><span>The research approach was quantitative and explanatory using panel data methodology from the databases of the World Bank, Harvard University and the Economic Commission for Latin America and the Caribbean for the period 2000-2020.</span></p> <p><strong><span>Results: </span></strong><span>The fixed effects panel data model showed that the variables that had a negative impact on trade openness were GDP, the economic complexity index and the logistic performance index, while the variables that had a positive impact were exports of high-tech products (a proxy for innovation), exports, imports, research and development expenditure and interregional trade in goods.</span></p> <p><strong><span>Conclusions: </span></strong><span>Therefore, during the analysis period of 2000-2020 in South America, based on the panel data analysis under fixed effects, a total of 8 countries had a negative impact on trade openness, and only the economies of Chile, French Guiana, and Brazil had a positive impact on trade openness; these economies are characterized by their better performance in the economic complexity index, their higher percentage of budget for research and development expenses, and their trade policies oriented towards the industrialization of their value-added products.</span></p>
Data Extracted for the Systematic Literature Review on Non-profit Open data Intermediaries and their effects on Open data Usability Barriers
<p>The dataset contains the data extracted from the literature for the Systematic Literature Review and is referenced or used in the extended abstract titled "How do Non-profit Open data Intermediaries enhance Open data Usability? A Systematic Literature Review", submitted to the 18th International Symposium on Open Collaboration (Companion), September 6–10, 2022, Madrid, Spain. <a href="https://doi.org/10.1145/3555051.3555061" target="_blank" rel="noopener">https://doi.org/10.1145/3555051.3555061</a> </p>
Open Data SORTEE infographics
<p><em>CRediT (in alphabetical order by family name):</em></p> <ul> <li>Amin, Bawan (University College Dublin, Ireland): Conceptualization, Visualization, Writing – original draft, Writing – review & editing</li> <li>Burke, Samantha (University of New South Wales Sydney, Australia): Conceptualization, Visualization, Writing – original draft, Writing – review & editing</li> <li>Drobniak, Szymon (University of New South Wales Sydney, Australia): Visualization, Writing – review & editing</li> <li>Lagisz, Malgorzata (University of New South Wales Sydney, Australia): Visualization, Writing – review & editing</li> <li>Norton, Luke (University of the Witwatersrand, South Africa): Conceptualization, Visualization, Writing – original draft</li> <li>Pottier, Patrice (University of New South Wales Sydney, Australia): Conceptualization, Visualization, Writing – original draft, Writing – review & editing</li> </ul>
Quantum stochastic resonance of individual Fe atoms. Open data sets.
<p>Data sets for publication:</p> <p><strong>Quantum Stochastic Resonance of individual Fe atoms</strong><br> Max Hänze, Gregory McMurtrie, Susanne Baumann, Luigi Malavolti, Susan N. Coppersmith, Sebastian Loth</p>
Supporting data and software for: Low-temperature open-air synthesis of PVP-coated NaYF4:Yb,Er,Mn upconversion nanoparticles with strong red emission
<p>Upconversion nanoparticles (UCNPs) have unique photonic properties that make them ideally suited for many applications. They are excited by low-energy near-infrared photons and emit at higher energy (typically visible) wavebands. However, synthesis of UCNPs requires either high pressure reaction chambers or inert atmospheres. Combined with the requirements for high-temperatures (200 to 400 °C) and long reaction times (e.g. up to 24 hours), these place barriers to entry for UCNP research, in terms of both financial barriers and knowledge/"know how". These constraints may also limit the scale of UCNP production for end-user applications.</p> <p>We adapted and further developed a method for producing UCNPs with simple laboratory equipment, i.e. a hot-plate and beakers. No pressure vessel or inert atmosphere is required. The UCNPs produced have a<span> polyvinylpyrrolidone (PVP) polymer coating, with strong red emission due to Mn<sup>2+</sup> co-doping within the UCNP crystal lattice. It was found that UCNPs of composition NaYF<sub>4</sub>:Yb,Er,Mn (Yb = 20 mol %, Er = 2 mol%, Mn = 35 mol%) maximised the red emission whilst also minimising the diameter of the UCNPs to </span> 36 ± 15 nm. These combination of optical and physical properties should make these UCNPs ideal for further development and exploitation, particularly for biological applications where red emission can penetrate over a centimetre of tissue.</p> <p>This dataset and software accompanies the manuscript <em>'Low-temperature open-air synthesis of PVP-coated NaYF<sub>4:</sub>Yb,Er,Mn upconversion nanoparticles with strong red emission</em>', which was published in Royal Society Open Science on 19th January 2022. https://doi.org/10.1098/rsos.211508</p>
Datasets for Linked Open Data Instance Level Analysis for Cultural Heritage
<p>This is the datasets used for Linked Open Data instant level quality analysis for cultural heritage (2020). 7Z and ZIP versions are available for both Excel 2006 and R 4.0.3. The compressed files include, Excel spreadsheets (.xlsx, .csv), VBA scripts (.bas), and R scripts (.r).</p> <p>Please read the full documentation in Linked_Open_Data_Instance_Level_Analysis_Procedure.pdf.</p>
Dataset created in the context of the project "Stable methodologies to evaluate and measure quality, interoperability, blockchain and reuse of open data in the agricultural field"
<p>The project "Stable methodologies to evaluate and measure quality, interoperability, blockchain and reuse of open data in the agricultural field", whose website is https://datause.es/, is a project funded by the Ministry of Science and Innovation - State Research Agency, with reference PID2019-105708RB-C22.</p> <p>Within the framework of the project, a bibliographic search is carried out in all thematic categories of the Web of Science (WoS) related to agriculture and related areas. The search equation included the following categories:</p> <p><strong>WC </strong>= (FOOD SCIENCE TECHNOLOGY OR PLANT SCIENCES OR FORESTRY OR AGRICULTURAL ENGINEERING OR AGRONOMY OR HORTICULTURE OR AGRICULTURE DAIRY ANIMAL SCIENCE OR AGRICULTURE MULTIDISCIPLINARY OR AGRICULTURAL ECONOMICS POLICY) </p> <p>This data set shows the distribution of journals and the quartile they occupy in each of the thematic categories in 2019, with the aim of serving researchers in this area and for future data mining.</p>
Open access data from the International Design Engineering Annual (IDEA) Challenge 2021
<p>Open access dataset from the IDEA challenge 2021. </p> <p>The generation of this dataset has been undertaken as part of the ProtoTwin project (Improving the product development process through integrated revision control and twinning of digital-physical models during prototyping). The work was conducted at the University of Bristol in the Design and Manufacturing Futures Lab (<a href="http://www.dmf-lab.co.uk/">http://www.dmf-lab.co.uk</a>) and is funded by the Engineering and Physical Sciences Research Council (EPSRC), Grant reference <a href="https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/R032696/1">EP/R032696/1</a>. The dataset was generated in collaboration with the Norwegian Technical University (NTNU), University of Zagreb and University of Twente.</p> <p>For more information please contact Mark (mark.goudswaard @ bristol.ac.uk) or James ( james.gopsill @ bristol.ac.uk)</p>
GreenCharge Open Research Data
<p>These datasets are collected from the pilots in the H2020 GreenCharge project. The data format and content is described in the GreenCharge Deliverable D5.6 Open Research Data.</p>
i-SoMPE Inventories A and B: open factor data
<p>Open data (factor data) of the inventory (A and B)</p>
How green is my valley? Measuring open access friendliness of Indian Institutes of Technology (IITs) through data carpentry (dataset)
<p>This data set is related to the book chapter with the following bibliographic details - Mukhopadhyay, P. (2022). How green is my valley? Measuring open access friendliness of Indian Institutes of Technology (IITs) through data<br> carpentry. In A. Biswas & M. Das Biswas (Eds.), Panorama of open access: Progress, practices & prospects (1st ed., pp. 67–89). Ess Ess. https://doi.org/10.5281/zenodo.6511080.</p> <p>It includes the truncated version of the final data set that has been used for analyzing Open Access Friendliness (OAF) of the Indian Institutes of Technology (IITs). The zipped version of the data set is around 95 MB (465 MB after decompress).</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.