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Dataset results
12 results for “Horizon 2020”
OpenAIRE and FAIR Data Expert Group survey about Horizon 2020 template for Data Management Plans
<p>This dataset is published in 2017 by the OpenAIRE project and the FAIR Data Expert Group.</p> <p>It contains two survey data files, two pdf-files summarising the results in a report and an infographic, and a Readme.txt file.</p> <p>The OpenAIRE project supports the open science ambitions of the European Commission. The project and in particular the Research Data Management team provide support, training and information on the Open Research Data Pilot. In this context, a survey was carried out to collect feedback on the Horizon 2020 template for Data Management Plans (DMPs). The team collaborated with the FAIR data expert group, which is providing recommendations to the European Commission on turning FAIR data into reality. One of the specific tasks of the Expert Group is contributing to an evaluation of the Horizon 2020 approach to DMPs, including future revisions of the template and the development of additional sector/ discipline-specific guidance. The aim of the survey was to collect experiences of researchers and DMP reviewers with the DMP template and guidelines on FAIR data management in Horizon 2020. The survey assesses the usefulness of the guidelines and any aspects that are confusing and unclear to determine what improvements can be made.</p> <p>Feedback was sought from both researchers and research support staff. The survey was initially scheduled to run from 22 May to 21 June 2017. Several organisations were asked to help announce the survey, including OpenAIRE’s National Open Access Desks, the FAIR data expert group, FOSTER, LIBER, and the RDA Interest Group on Active DMPs. When the first survey responses showed only a small share of researchers, more stakeholders were contacted to specifically target this community. The European Research Area was approached, whose project officers circulated the survey call among award holders of EC projects. Early-career researchers were also informed through the YEAR network and EURODOC. This resulted in an extension of the survey to 21 July 2017.</p> <p>At the close of the survey on 21 July 2017, a total number of 289 responses were reached. 50% of the respondents indicated that they were researchers, and 60% that they were (also) research support staff. OpenAIRE and the FAIR data expert group are very pleased with this balanced outcome and would like to thank all colleagues and organisations who promoted the survey, as well as everyone who took part in it.</p> <p> </p>
IMMERSE Horizon 2020 Project Downstream User Toolbox – data for tutorial on impact of wave coupling on surface particle dispersion simulations
<p>Exemplary data for tutorial on impact of wave coupling on surface particle dispersal simulations<br> <a href="https://github.com/immerse-project/Downstream-Users-Toolbox/tree/main/T8.3_WaveCoupling_ParticleTransport_UniU">https://github.com/immerse-project/Downstream-Users-Toolbox/tree/main/T8.3_WaveCoupling_ParticleTransport_UniU</a><br> created as part of the downstream user toolbox of the IMMERSE Horizon 2020 project (<a href="https://immerse-ocean.eu/">https://immerse-ocean.eu/</a>).</p> <p>In the tutorial the impact of new options for the representation of wave-current interactions in the NEMO ocean model (<a href="https://www.nemo-ocean.eu/">https://www.nemo-ocean.eu/</a>) on surface particle simulations are tested in a case study for the Mediterranean Sea. The tutorial consists of two jupyter notebooks: Parcels_CalcTraj.ipynb and CompTraj_uncoupledVScoupled.ipynb. Parcels_CalcTraj.ipynb calculates Lagrangian particle trajectories based on velocity output from ocean only as well as coupled ocean-wave model simulation by making use of the OceanParcels software (<a href="https://oceanparcels.org/">https://oceanparcels.org/</a>). CompTraj_uncoupledVScoupled.ipynb compares dispersal statistics of Lagrangian particle trajectories calculated from ocean-only vs coupled ocean-wave model simulations.</p> <p>This repository contains the surface velocity and ocean model grid data needed to run Parcels_CalcTraj.ipynb, as well as the trajectory data produced by Parcels_CalcTraj.ipynb, which is needed to run CompTraj_uncoupledVScoupled.ipynb. The surface velocity data stems from two simulations with a regional high-resolution (1/24° horizontal resolution) model configuration for the Mediterranean Sea: a coupled ocean-wave model simulation and a complimentary ocean-only simulation. These model simulations make use of the NEMO v4.2-RC ocean model, the Wave Watch 3 v.6.07 wave model, the OASIS3-MCT coupler, and ECMWF atmospheric fields; they are described in detail in IMMERSE deliverable D5.7 “Assessment of wave-current effects on the circulation in theMed-MFC system”<strong>.</strong></p>
NYMPHE Horizon 2020 project Falasarna (GR) Test Sites preliminary data
<p>The dataset is a preliminary vision on the Falasarna (GR) test site for bioremediation action in the EU funded Horizon 2020 project. The data set iwill be used to futher refine the datasets structure and to define the hyerachical data dependences. The distribution of the typical species for phrigana habitat was investigated. The data were obtain prior application of the bioremediation measures. The data collection mission took place in October 2024. The valuee were obtaiing by direct measurement on site, </p>
Uncommon Commons? Creative Commons licencing in Horizon 2020 Data Management Plans
<p>As policies, good practices and funder mandates on research data management evolve, more emphasis has been put on the licencing of data. Licencing information allow potential re-users to quickly identify what they can do with the data in question and is therefore an important component to ensure the reusability of research.</p> <p>In my research I analyse a pre-existing collection of 840 Horizon 2020 public data management plans (DMPs) available on the repository of the University of Vienna, Phaidra,, to determine which ones mention creative commons licences and among those who do, what licences are being used.</p> <p>This excel file contains the data underlying the publication "Uncommon Commons? Creative Commons licencing in Horizon 2020 Data Management Plans ".</p> <p>Sheet 1 contains the data collected in the previous "Data Re-Use" project: 840 DMPs downloaded from CORDIS and vetted to ensure they are public documents and not copyrighted</p> <p>Sheet 2 contains the same data as sheet 1, with columns D to Q not visible (for better reading) but an added column R which now contains the CC licening information (where available)</p> <p>Sheet 3 is filtered so that only the projects containing CC BY relevant licencing are shown</p> <p>Sheet 4 is filtered so that only the projects containing CC-BY-SA relevant licencing are shown</p> <p>Sheet 5 is filtered so that only the projects containing CC-BY-NC relevant licencing are shown</p> <p>Sheet 6 is filtered so that only the projects containing CC-BY-ND relevant licencing are shown</p> <p>Sheet 7 is filtered so that only the projects containing Cc-BY-NC-ND relevant licencing are shown</p> <p>Sheet 8 is filtered so that only the projects containing CC-BY-NC-SA relevant licencing are shown</p> <p>Sheet 9 is filtered so that only the projects containing CC0 relevant information are shown</p> <p>Sheet 10 provides an overview table of the relevant licences (manual entry)</p> <p>Sheet 11 and 12 contain graphic visulations of the data as used in the article</p>
Tissue Stresses of Cancer (Force Horizon 2020)
ClinicalTrials.gov study NCT03238144. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
UWIPOM2 project presentation in Spring Horizon 2020
<p><a href="https://www.youtube.com/watch?v=e5z84TcIxdU&feature=youtu.be">LINK TO VIDEO</a></p>
Horizon 2020 ER4STEM workshop data Year 1-3 UK
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commision's Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in schools in the UK. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to project vulnerable participants. </p>
Horizon 2020 ER4STEM workshop data Year 1-3 Bulgaria
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commission’s Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in schools in Bulgaria. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to protect vulnerable participants.</p>
Horizon 2020 ER4STEM workshop data Year 1-3 Austria-TU Wien
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commission’s Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in the Technical University Wien in Austria. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to protect vulnerable participants.</p>
Horizon 2020 ER4STEM workshop data Year 1-3 Greece_UoA
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commision's Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in schools in Greece by UoA. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to project vulnerable participants. </p>
Horizon 2020 ER4STEM workshop data Year 1-3 Austria-PRIA
<p>This dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commission’s Horizon 2020 programme, grant agreement No. 665972. The dataset includes quantitative and qualitative data collected over 3 years of<br> robotics workshops held in schools in Austria. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to protect vulnerable participants.</p>
Horizon 2020 ER4STEM workshop data Year 1-3 : Malta
<p>The dataset was collected as part of the Educational Robotics for STEM (ER4STEM) project, funded by the European Commission's Horizon 2020 programme, grant agreement No. 665792. The dataset includes quantitative and qualitative data collected over 3 years of robotics workshops held in schools in Malta. Only data with informed consent to be shared via an open access repository is included. Only anonymised data is included and some data is excluded to protect vulnerable participants.</p>
ScienceDex guides
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