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13,499 results for “researcher”
Research Data Management and Sharing for images: beautiful fountains require ugly piping!
<p>The consensus is clear: research data funded by public resources should be shared. Globally, the advantages of sharing research data are widely recognized. It promotes transparency and validation, reduces redundant efforts, accelerates discovery, enhances equity, and increases the impact of research through collaboration and efficient use of resources.</p> <p>Image data, however, presents unique challenges. Advanced technologies produce large, multimodal, and multiplexed datasets that span multiple targets across various spatiotemporal scales.</p> <p>This image data comes from a range of sources—such as optical, electron microscopy, and medical imaging—each with specific technical requirements. Managing this complexity is a daunting task without global metadata standardization as well as robust Research Data Management and Sharing (RDMS) cyberinfrastructure to bring it all together.</p> <p>The figure illustrates a common issue: while the importance of the <strong>“beautiful fountains”</strong> of scientific discoveries and medical treatments is widely understood, fewer people recognize the <strong>need to invest in building the often ignored “ugly plumbing” </strong>required to build a strong RDMS cyberinfrastructure.</p> <p> </p>
RRING Global Survey Research Dataset (WP3)
<p>The RRING Work Package 3 (WP3) objective was to clarify how Research Funding Organisations (RFOs) and Research Performing Organisations (RPOs) operated within region-specific research and innovation environments. It explored how they navigated the governance and regulatory frameworks for Responsible Research and Innovation (RRI), as well as offering their perspectives on the entities responsible for RRI-related policy and action in their locales.</p> <p>This data set covers the global survey research part, which was designed to contextualise how RPOs and RFOs interacted within the research environment and with non-academic stakeholders. Countries were grouped according to the UNESCO regions of the world and key results per region are listed below. For a detailed analysis and further findings of the work completed under WP3 of the RRING project, please refer to the full deliverable document "State of the Art of RRI in the Five UNESCO World Regions" [link to be inserted].</p> <p> </p> <p><strong>European and North American States</strong></p> <ul> <li>‘Diverse and inclusive': Respondents were most attitudinally supportive of the importance of ensuring ethical principles were applied in R&I (92%), followed by diverse perspectives (88%), and gender equality (79%). Including ethnic minorities was the area which garnered the least attitudinal support (71%). Respondents took the most practical steps towards engaging with diverse perspectives (63%), and the least towards inclusion of ethnic minorities (24%).</li> <li>‘Anticipative and reflective’: Respondents widely agreed (82%) with the importance of ensuring R&I work does not cause concerns for society, but only 37% confirmed they had taken practical steps to ensure this.</li> <li>‘Open and transparent’: Vast majorities of respondents agreed on the importance of keeping R&I methods open and transparent (94%), with 65% also confirming they take practical steps to do this. An equally high number agreed on the importance of making the results of R&I work accessible to as wide a public as possible (94%), and 68% confirmed this through their reported actions. This indicated the smallest value-action gap of all RRI measures for respondents from European and North American countries. Attitudinal agreement on the importance of making data freely available to the public was lower (83%), as was the practical action aspect for this measure (45%).</li> <li>‘Responsive and adaptive to change’: Most respondents agreed (89%) that it was important to ensure their work addresses societal needs, and 62% confirmed that they take practical steps towards this aim.</li> </ul> <p> </p> <p><strong>Latin American and Caribbean States</strong></p> <ul> <li>‘Diverse and inclusive': Respondents were most attitudinally supportive of the importance of gender equality in R&I (86%), followed by ensuring ethical principles are applied (85%), and diverse perspectives incorporated (83%). Including ethnic minorities was the area which garnered the least attitudinal support (77%). Respondents took the most practical steps towards ensuring ethical principles guide their work (50%), and the least towards including ethnic minorities (25%), but the smallest value action gap was found for gender equality.</li> <li>‘Anticipative and reflective’: Respondents agreed (79%) that it is important to ensure R&I work does not cause concerns for society, but only 29% confirmed they had taken practical steps to ensure this.</li> <li>‘Open and transparent’: The majority of respondents agreed on the importance of keeping R&I methods open and transparent (89%), with 45% indicating they had taken practical action. A majority also agreed on the importance of making the results of R&I work accessible to as wide a public as possible (88%), and 44% backed this up with practical action. Attitudinal agreement on the importance of making data freely available to the public was slightly lower (81%), as was the practical action aspect for this measure (35%).</li> <li>‘Responsive and adaptive to change’: Most respondents agreed (84%) that it was important to ensure their work addresses societal needs, and 49% confirmed that they take practical steps towards this aim.</li> </ul> <p> </p> <p><strong>Asian and Pacific States</strong></p> <ul> <li>‘Diverse and inclusive': Respondents were most attitudinally supportive of the importance of ensuring ethical principles were applied in R&I (90%), followed by diverse perspectives (89%), and gender equality (86%). Including ethnic minorities was the area which garnered the least attitudinal support (76%). Respondents took the most practical steps towards engaging with diverse perspectives (65%), and the least towards including ethnic minorities (30%).</li> <li>‘Anticipative and reflective’: Respondents widely agreed (78%) with the importance of ensuring R&I work does not cause concerns for society, and 42% confirmed they had taken practical steps to ensure this.</li> <li>‘Open and transparent’: The majority of respondents agreed on the importance of keeping R&I methods open and transparent (91%), with 58% indicating they take practical steps to do this. A majority also agreed on the importance of making the results of R&I work accessible to as wide a public as possible (89%), and 64% backed this up with practical action. Attitudinal agreement on the importance of making data freely available to the public was lower (79%), as was the practical action aspect for this measure (40%).</li> <li>‘Responsive and adaptive to change’: Most respondents agreed (92%) that it was important to ensure their work addresses societal needs, and 69% confirmed that they take practical steps towards this aim. This was the RRI measure with the smallest valueaction gap for respondents from the Asian and Pacific region.</li> </ul> <p> </p> <p><strong>Arab States</strong></p> <ul> <li>‘Diverse and inclusive': Respondents were most attitudinally supportive of the importance of ensuring ethical principles were applied in R&I (93%), followed by diverse perspectives (81%), and gender equality (85%). Including ethnic minorities was the area which garnered the least attitudinal support (74%). Respondents took the most practical steps towards engaging with diverse perspectives (66%), which equated to one of two equally small value-action gaps for respondents from Arab states, and the least practical steps towards inclusion of ethnic minorities (22%).</li> <li>‘Anticipative and reflective’: A high proportion of respondents (85%) agreed that it is important to ensure R&I work does not cause concerns for society. However, only 38% confirmed they had taken practical steps to ensure this.</li> <li>‘Open and transparent’: The majority of respondents agreed on the importance of keeping R&I methods open and transparent (89%), with 59% also confirming they take practical steps to do this. A majority also agreed on the importance of making the results of R&I work accessible to as wide a public as possible (90%), and 66% backed this up with practical action. Ensuring public accessibility of research results was the second of two measures with equally small value-action gaps. Attitudinal agreement on the importance of making data freely available to the public was much lower (78%), which also reflected the practical action aspect for this measure (49%).</li> <li>‘Responsive and adaptive to change’: Most respondents agreed (96%) that it was important to ensure their work addresses societal needs, and 68% confirmed that they take practical steps to achieve this.</li> </ul> <p><strong>African States</strong></p> <ul> <li>‘Diverse and inclusive': Respondents were most attitudinally supportive of the importance of ensuring engagement with diverse perspectives and expertise in R&I (91%), followed by ensuring ethical principles are applied (90%), and gender equality (89%). Including ethnic minorities was the area which garnered the least attitudinal support (74%). Respondents took the most practical steps towards ensuring ethical principles guide their work (57%), and the least towards including ethnic minorities (32%).</li> <li>‘Anticipative and reflective’: The majority of respondents (85%) agreed that it is important to ensure R&I work does not cause concerns for society, with 59% confirming that they take practical steps to ensure this.</li> <li>‘Open and transparent’: A high proportion of respondents agreed on the importance of keeping R&I methods open and transparent (90%), with 54% also confirming they take practical steps to do this. A majority also agreed on the importance of making the results of R&I work accessible to as wide a public as possible (86%), and 56% backed this up with practical action. Attitudinal agreement on the importance of making data freely available to the public was significantly lower (73%), as was the practical action aspect for this measure (38%).</li> <li>‘Responsive and adaptive to change’: Respondents mostly agreed (92%) that it was important to ensure their work addresses societal needs, and 64% confirmed that they take practical steps towards this aim. This was the RRI measure with the smallest valueaction gap for respondents from African states.</li> </ul> <p> </p> <p><em>Note: Please refer to the "RRING WP3 - Survey Data Documentation" document for detailed instructions on how to use this dataset.</em></p>
Datasets from Analysis of the strategic management of science, research and innovation thesis
<p>Datasets were obtained from Czech R&D information system and used in my diploma thesis. The thesis (in Czech language) explores system of governance in R&D in the Czech republic and his impacts on the field of molecular biology in the period of 1995-2014.</p>
Publishing Reproducible Research Outputs - Interviewees and interview questions
<p>The table '<strong>Interview questions</strong>' shows the focus of our investigation and stakeholder engagement activities. It should be noted that not all interview questions were asked to all stakeholder groups based on appropriateness and time available. Some questions in the table may appear to be repeated: this is because slightly different phrasing was used based on the stakeholder interviewed.</p> <p>Legend:</p> <ul> <li>Research Funding Organisations: RFO</li> <li>Research Performing Organisations: RPO</li> <li>Infrastructure Providers: IP </li> <li>Academic Publishers: AP</li> <li>Researchers and research groups: RRG</li> </ul> <p>The table '<strong>List of interviewees</strong>' includes all stakeholders engaged in the context of this research.</p>
Dataset: Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication
<p>The rainbow color map is scientifically incorrect and hinders people with color vision deficiency to view visualizations in a correct way. Due to perceptual non-uniform color gradients within the rainbow color map the data representation is distorted what can lead to misinterpretation of results and flaws in science communication. Here we present the data of a paper survey of 797 scientific publication in the journal Hydrology and Earth System Sciences. With in the survey all papers were classified according to color issues. Find details about the data below.</p> <ul> <li><code>year</code> = year of publication (YYYY)</li> <li><code>date</code> = date (YYYY-MM-DD) of publication</li> <li><code>title</code> = full paper title from journal website</li> <li><code>authors</code> = list of authors comma-separated</li> <li><code>n_authors</code> = number of authors (integer between 1 and 27)</li> <li><code>col_code</code> = color-issue classification (see below)</li> <li><code>volume</code> = Journal volume</li> <li><code>start_page</code> = first page of paper (consecutive)</li> <li><code>end_page</code> = last page of paper (consecutive)</li> <li><code>base_url</code> = base url to access the PDF of the paper with <code>/volume/start_page/year/</code></li> <li><code>filename</code> = specific file name of the paper PDF (e.g. <code>hess-9-111-2005.pdf</code>)</li> </ul> <p>Color classification is stored in the <code>col_code</code> variable with:</p> <ul> <li><code>0</code> = chromatic and issue-free,</li> <li><code>1</code> = red-green issues,</li> <li><code>2</code>= rainbow issues and</li> <li><code>bw</code>= black and white paper.</li> </ul> <p> </p> <p>See more details (e.g., sample code to analyse the survey data) on https://github.com/modche/rainbow_hydrology</p> <p>Paper: Stoelzle, M. and Stein, L.: Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication, Hydrol. Earth Syst. Sci., 25, 4549–4565, https://doi.org/10.5194/hess-25-4549-2021, 2021.</p> <p> </p> <p> </p>
Publishing Reproducible Research Outputs - Thematic coding of interview findings
<p>The spreadsheet in the present dataset (CSV format) includes the anonymised thematic coding that has been applied to our interview findings. A list of interviewees and interview questions is available <a href="https://doi.org/10.5281/zenodo.5141665">here</a>.</p> <p>The thematic coding has been applied by using <a href="https://www.qsrinternational.com/nvivo-qualitative-data-analysis-software/home">NVivo</a>, a professional qualitative analysis software, and then exported in spreadsheet form for public sharing. The findings of this analysis have been used to inform our final report, which is available in our <a href="https://zenodo.org/communities/ke-prro/?page=1&size=20">Zenodo project Community</a>.</p>
Research data supporting "Considerations for Implementing Electronic Laboratory Notebooks in an Academic Research Environment"
<p><em>Research data supporting the publication:</em></p> <p><em>Higgins SG, Nogiwa-Valdez AA, Stevens MM, Considerations for Implementing Electronic Laboratory Notebooks in an Academic Research Environment, Nature Protocols, 2021.</em></p> <p>This repository contains the raw survey data of 172 current and historic electronic laboratory notebook (ELN) software packages.</p> <p>Main files:</p> <ul> <li>"ELN_Review_Higgins_2021_Survey.csv" = raw survey data in 'tidy' data format</li> <li>"ELN_Review_Higgins_2021.Rmd" = an R Markdown File (R Notebook) that takes the survey data as input and produces summary statistics and plots. This file was written using R Studio as the IDE.</li> </ul> <p>Derived files, generated from those above:</p> <ul> <li>"ELN_Review_Higgins_2021.nb.html" = a self-contained HTML file that is automatically generated by R Studio, based on the markdown file. This can be opened in any web browser to allow manual inspection of the code and comments without the need for specialist software. Embedded within this file is also the original markdown script (i.e. a copy of the code in "ELN_Review_Higgins_2021.Rmd")</li> <li>"ELN_Review_Higgins_2021_Lifetimes_Interactive_Figure1.html" = an HTML file generated by the script above via the plotly package. It contains an interactive version of the ELN survey data, allowing the user to hover over the timeline and explore the data.</li> <li>"ELN_Review_Higgins_2021_Timeline.pdf" = static version of ELN timeline, used to generate figure in main manuscript.</li> <li>"ELN_Review_Higgins_2021_Releases-Per-Year.pdf" = static version of number of new ELNs per year, used to generate figure in main manuscript.</li> </ul> <p>This survey was generated from a mixture of primary and secondary sources (see references for secondary sources).</p>
Data from a three-phase Delphi study used to investigate Knowledge Infrastructure for Research Data in Norway, KIRDN_Data; PhD project
<p>A modified three-phase Delphi study was used to explore the knowledge infrastructure for research data in Norway. The study includes different stakeholders involved in research data sharing. A Delphi study is characterised by the use of an expert panel to elicit opinions on a shared reality from different perspectives. Data collection is performed in several rounds with the intention of reaching consensus or solving an issue. </p> <p>A group of 24 experts took part in the study. The group consisted of policy-makers, representatives of national service providers, and researchers and research support staff from four Norwegian universities. The participants were invited based on their involvement in the development of policies, infrastructure or data-related research support. The research support staff were recruited to include representatives from different research support services at the universities, including libraries, research offices and IT departments. While the researchers were selected from based on their receival of EU funding with requirements of data management plans.</p> <p>Data were collected in three phases. The first phase, the ‘exploration phase’, was conducted using open interviews lasting approximately one hour in January/February 2018. The purpose of this phase was to obtain an initial overview of the panel members opinions’ on issues regarding research data management.</p> <p>In the second phase, the ‘evaluation phase’, conducted in August/September 2018, participants answered a survey containing nine questions on topics such as data stewardship, DMPs, ethical aspects of data sharing and core functions in a research data infrastructure. The survey was designed to further explore issues and tensions uncovered in the first interviews. Several of the questions were formulated as statements that the participants were asked to agree or disagree upon. </p> <p>The third, ‘concluding phase’ was conducted using interviews in March/April 2019. These interviews lasted approximately 30 minutes and were based on results from the questionnaire as well as the first interview. Participants were asked whether they had thoughts on the preliminary findings of the study. </p> <p>Based on requests from some of the participants, the questions were sent to all participants prior to the data collection, in all three phases. The participants were also sent the transcripts from the interviews and were asked for permission to share the complete material or parts of the data material to which they contributed. </p>
OpenAIRE Graph: Dataset for research communities and initiatives
<p>This dataset contains metadata records of the OpenAIRE Graph relevant for the research communities and initiatives collaborating with OpenAIRE and with a public Community Gateway on <a href="https://connect.openaire.eu">OpenAIRE CONNECT</a> as of July 2025.</p> <p>Each file is a tar archive containing gzip files with one json per line. Each json is compliant to the schema available at <a href="https://doi.org/10.5281/zenodo.14891476" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.14891476</a></p> <table style="width: 100%; height: 822.939px;"> <tbody> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;"><strong>Research community name</strong></td> <td style="width: 38.9414%; height: 19.5938px;"><strong>File name</strong></td> <td style="width: 23.1067%; height: 19.5938px;"><strong>URL to the gateway</strong></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Argo France</td> <td style="width: 38.9414%; height: 19.5938px;">argo-france.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://argo-france.openaire.eu/">https://argo-france.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Aurora University Alliance</td> <td style="width: 38.9414%; height: 19.5938px;">aurora.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://aurora.openaire.eu">https://aurora.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Transport Research (EC projects BE OPEN and SciLake)</td> <td style="width: 38.9414%; height: 19.5938px;">beopen.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://beopen.openaire.eu">https://beopen.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">CIVICA Alliance</td> <td style="width: 38.9414%; height: 19.5938px;">civica.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://civica.openaire.eu" target="_blank" rel="noopener">https://civica.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">COVID 19</td> <td style="width: 38.9414%; height: 19.5938px;">covid-19.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://covid-19.openaire.eu">https://covid-19.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">DARIAH EU</td> <td style="width: 38.9414%; height: 19.5938px;">dariah.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://dariah.openaire.eu">https://dariah.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Digital Humanities and Cultural Heritage</td> <td style="width: 38.9414%; height: 19.5938px;">dh-ch.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://dh-ch.openaire.eu">https://dh-ch.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Virtual Twins in Health (EC project EDITH)</td> <td style="width: 38.9414%; height: 19.5938px;">dth.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://dth.openaire.eu">https://dth.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">European Digital Innovation Hubs Network ADRIA</td> <td style="width: 38.9414%; height: 19.5938px;">edih-adria.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://edih-adria.openaire.eu">https://edih-adria.openaire.eu</a></td> </tr> <tr style="height: 39.1875px;"> <td style="width: 33.9453%; height: 39.1875px;">European Geothermal Research and Innovation Search Engine </td> <td style="width: 38.9414%; height: 39.1875px;">egrise.tar</td> <td style="width: 23.1067%; height: 39.1875px;"><a href="https://egrise.openaire.eu">https://egrise.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">ELIXIR Greece</td> <td style="width: 38.9414%; height: 19.5938px;">elixir-gr.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://elixir-gr.openaire.eu">https://elixir-gr.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Energy Planning (EC project SciLake)</td> <td style="width: 38.9414%; height: 19.5938px;">energy-planning_1.tar, energy_planning_2.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://energy-planning.openaire.eu/">https://energy-planning.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Energy Research (EC project Enermaps)</td> <td style="width: 38.9414%; height: 19.5938px;">enermaps.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://enermaps.openaire.eu">https://enermaps.openaire.eu</a></td> </tr> <tr style="height: 39.1875px;"> <td style="width: 33.9453%; height: 39.1875px;">European University for Smart Urban Coastal Sustainability</td> <td style="width: 38.9414%; height: 39.1875px;">eu-conexus.tar</td> <td style="width: 23.1067%; height: 39.1875px;"><a href="https://eu-conexus.openaire.eu/">https://eu-conexus.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">European University of Technology+</td> <td style="width: 38.9414%; height: 19.5938px;">eut.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://eut.openaire.eu/">https://eut.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">EUTOPIA Alliance</td> <td style="width: 38.9414%; height: 19.5938px;">eutopia.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://eutopia.openaire.eu/">https://eutopia.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">FORTHEM Alliance</td> <td style="width: 38.9414%; height: 19.5938px;">forthem.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://forthem.openaire.eu">https://forthem.openaire.eu</a></td> </tr> <tr> <td style="width: 33.9453%;">[NEW] GoTriple </td> <td style="width: 38.9414%;">gotriple_1.tar, gotriple_2.tar</td> <td style="width: 23.1067%;"><a href="https://gotriple.openaire.eu/">https://gotriple.openaire.eu/</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Heritage Science (EC project IPERION HS)</td> <td style="width: 38.9414%; height: 19.5938px;">heritage-science.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://heritage-science.openaire.eu/">https://heritage-science.openaire.eu</a></td> </tr> <tr style="height: 39.1875px;"> <td style="width: 33.9453%; height: 39.1875px;">Institut national de recherche en informatique et en automatique (EC project GraspOS)</td> <td style="width: 38.9414%; height: 39.1875px;">inria.tar</td> <td style="width: 23.1067%; height: 39.1875px;"><a href="https://inria.openaire.eu" target="_blank" rel="noopener">https://inria.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">IPERION HS</td> <td style="width: 38.9414%; height: 19.5938px;">iperionhs.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://iperionhs.openaire.eu">https://iperionhs.openaire.eu</a></td> </tr> <tr style="height: 39.1875px;"> <td style="width: 33.9453%; height: 39.1875px;">Knowmad Institut</td> <td style="width: 38.9414%; height: 39.1875px;">knowmad_1.tar, knowmad_2.tar, knowmad_3.tar, knowmad_4.tar, knowmad_5.tar, knowmad_6.tar, knowmad_7.tar, knowmad_8.tar, knowmad_9.tar</td> <td style="width: 23.1067%; height: 39.1875px;"><a href="https://knowmad.openaire.eu/">https://knowmad.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">LifeWathc ERIC</td> <td style="width: 38.9414%; height: 19.5938px;">lifewatch-eric.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://lifewatch-eric.openaire.eu/">https://lifewatch-eric.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">European Marine Science</td> <td style="width: 38.9414%; height: 19.5938px;">mes.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://mes.openaire.eu">https://mes.openaire.eu</a></td> </tr> <tr style="height: 39.1875px;"> <td style="width: 33.9453%; height: 39.1875px;">Atmospheric Research Community (EC project NEANIAS)</td> <td style="width: 38.9414%; height: 39.1875px;">neanias-atmospheric.tar</td> <td style="width: 23.1067%; height: 39.1875px;"><a href="https://neanias-atmospheric.openaire.eu/">https://neanias-atmospheric.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Space Research Community (EC project NEANIAS)</td> <td style="width: 38.9414%; height: 19.5938px;">neanias-space.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://neanias-space.openaire.eu/">https://neanias-space.openaire.eu</a></td> </tr> <tr style="height: 39.1875px;"> <td style="width: 33.9453%; height: 39.1875px;">Underwater Research Community (EC project NEANIAS)</td> <td style="width: 38.9414%; height: 39.1875px;">neanias-underwater.tar</td> <td style="width: 23.1067%; height: 39.1875px;"><a href="https://neanias-underwater.openaire.eu/">https://neanias-underwater.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Netherlands Research Portal</td> <td style="width: 38.9414%; height: 19.5938px;">netherlands_1.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://netherlands.openaire.eu/">https://netherlands.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">[NEW] Neuroscience<br>(EC project SciLake - former Neuroinformatics community is now a subcommunity of Neuroscience)</td> <td style="width: 38.9414%; height: 19.5938px;">neuroscience_1.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://neuroscience.openaire.eu">https://neuroscience.openaire.eu</a></td> </tr> <tr style="height: 39.1875px;"> <td style="width: 33.9453%; height: 39.1875px;">North American Studies</td> <td style="width: 38.9414%; height: 39.1875px;">north-american-studies.tar</td> <td style="width: 23.1067%; height: 39.1875px;"><a href="https://north-american-studies.openaire.eu">https://north-american-studies.openaire.eu</a></td> </tr> <tr style="height: 39.1875px;"> <td style="width: 33.9453%; height: 39.1875px;">Rural Digital Europe (EC project DESIRA)</td> <td style="width: 38.9414%; height: 39.1875px;">rural-digital-europe.tar</td> <td style="width: 23.1067%; height: 39.1875px;"><a href="https://rural-digital-europe.openaire.eu/">https://rural-digital-europe.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Sustainable Development Solutions Network - Greece </td> <td style="width: 38.9414%; height: 19.5938px;">sdsn-gr.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://sdsn-gr.openaire.eu/">https://sdsn-gr.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">Technological University Network</td> <td style="width: 38.9414%; height: 19.5938px;">tunet.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://tunet.openaire.eu">https://tunet.openaire.eu</a></td> </tr> <tr> <td style="width: 33.9453%;">[NEW] UNITE! University Alliance</td> <td style="width: 38.9414%;">unite.tar</td> <td style="width: 23.1067%;"><a href="https://unite.openaire.eu">https://unite.openaire.eu</a></td> </tr> <tr style="height: 19.5938px;"> <td style="width: 33.9453%; height: 19.5938px;">University of the Arctic (UArctic) </td> <td style="width: 38.9414%; height: 19.5938px;">uarctic_1.tar, uarctic_2.tar</td> <td style="width: 23.1067%; height: 19.5938px;"><a href="https://uarctic.openaire.eu/">https://uarctic.openaire.eu</a></td> </tr> </tbody> </table>
SEEtheSkills resources database from the Interregional research on the status of energy skills
<p>This dataset includes a list of resources identified during the interregional research on the status of energy skills, done in the frame of SEEtheSkills project. The comprehensive overview of the information created in the area of Energy Efficiency (EE) and Renewable Energy Systems (RES), goes both wide, by trying to identify as many different examples as possible, and deep, by digging into the examples themselves. The key areas the research focused on: skills defined in national roadmaps; skills developed as part of previous BUS projects; developed training schemes; the number of trained workers and professionals; companies that design and produce EE materials; status of Recognition of Previous Learning (RPL); status of demand for energy skills; level of awareness of energy skills; available certification schemes; legal obligations promoting the use of energy skills and their timelines, predictions for future development of energy skills. The survey covers mainly the five countries participating in the project Slovenia, Spain, Netherlands, Slovakia and North Macedonia, but also beyond their geographical coverage.</p>
Beyond the passive–active dichotomy: aligning research with the intervention continuum framework of ecological restoration
<p>The dataset and R script file are associated with the publication, "Krishnan, A. and Osuri, A.M. (2022), Beyond the passive-active dichotomy: aligning research with the intervention continuum framework of ecological restoration. Restoration Ecology:e13828. https://doi.org/10.1111/rec.13828"</p> <p>Please refer to the readme.txt file for more information on the dataset and analyses.</p>
An analysis of meiofauna knowledge generated by Latin American researchers
<p>Bibliographic databases used to analyse the document production of benthic meiofauna in Latin American countries. To be opened on R, bibliometrix package.</p> <p> </p>
Data sources for the groundwater depletion manuscript in Water Resources Research
<p>Here, you can access the source files for the figures (and tables) of the publication (see reference).</p> <p>Basically, you find the model output (WaterGAP 2.2a) for global scaled groundwater storage, total water storage, baseflow, groundwater recharge (diffuse and below surface water bodies) and a table where location of grid cell and belonging continental area (e.g. to convert values into km³) is given. In addition, an Excel-File for the diagram of HPA (Figure 2) is accessible.</p> <p>First part of the file name represents the model variant (IRR100, IRR100_S, IRR70_S, NOUSE_S, for details see the manuscript), then the variable name and unit is given (Total Water Storages [mm], groundwater storage [mm], Qb (baseflow) [mm], Rg (diffuse groundwater recharge) [mm], Rg_swb (groundwater recharge below surface water bodies) [mm]). File format is a zipped netCDF. The table "lat_lon_cont_area.txt" contains the ArcID (internal grid cell number), coordinates and the continental area which is used for WaterGAP calculations.</p> <p>Original data description: https://www.uni-frankfurt.de/49903932/6__GW_depletion</p>
Dataset used in the publication entitled "Decomposition by Approximation with Pulse Waves Allowing Further Research on Sources of Voltage Fluctuations"
<p>Dataset obtained from experimental research carried out in the prepared laboratory setup. Based on the dataset, the proposed new decomposition method by approximation with pulse waves has been validated in the publication: Kuwałek P., Decomposition by Approximation with Pulse Waves Allowing Further Research on Sources of Voltage Fluctuations. The description of the prepared laboratory setup is presented in this publication. The research results are part of the work under the project entitled "Voltage fluctuation diagnostic focused on identification and localization disturbing loads in power grids" funded by the National Science Centre, Poland - 2021/41/N/ST7/00397.</p>
Research data for Investigation of coatings and metallic materials for icephobic properties, dataset
<p>This dataset is used in deliverable 3.5, 'Investigation of coatings and metallic materials for icephobic properties', where you can get more information.</p> <p>The Dataset includes:</p> <table> <tbody> <tr> <td>Coating Data</td> </tr> <tr> <td>Metalic materials data</td> </tr> <tr> <td>Coating Freezing spike</td> </tr> <tr> <td>Coating Atmospheric freezing</td> </tr> <tr> <td>Coating contact angle</td> </tr> <tr> <td>Coating Ice adhesion</td> </tr> <tr> <td>Submerged freeze depression</td> </tr> <tr> <td>Metalic materials droplet freezing</td> </tr> <tr> <td>Metalic materials Droplet contact angle</td> </tr> <tr> <td>Coating freeze depression brine test</td> </tr> <tr> <td>Coating freeze depression CFT</td> </tr> <tr> <td>Metalic amorphous materials freeze depression</td> </tr> <tr> <td>Metalic pure materials freeze depression</td> </tr> </tbody> </table>
Datasources in urban and construction research
<p>This table provides information about data sources related to two use-cases from urban and construction research, including information on: use case, name of the datasource, publisher, type of providing institution, type of source, paywalls, download/API availability, data format, and whether the data is structured or nun-structured. The data was collected and analyzed in the context of the DFG-funded "Fachinformationsdienst BAUdigital" and used for an analysis of the used data sources in the research fields of urban and construction research. The used sources for this work can be found in the section "References". The written analysis is currently under review and will be published at the "Netzwerk Architekturwissenschaft" 8. Forum Architekturwissenschaft "The Power of Sources" (<a href="https://architekturwissenschaft.net/">https://architekturwissenschaft.net/</a>).</p>
Research data related to switchable contact model (SCM) development
<p>Research data of the linked journal article, is composed of input and output files of the LIGGGHTS simulations (Project folders) and an Excel data sheet (Results_Excel) which includes calculated data.</p> <p>The contents are the simulation data and results of cake formation in centrifugal filtration using conventional (mesh) method and novel Switchable contact model (SCM, primitive) method. (For more information see the linked article and the source code of SCM: <a href="https://github.com/DamlaSerper/SCM">https://github.com/DamlaSerper/SCM</a>)</p>
UKRI Digital Research Infrastructure Mapping Survey Dataset (for Net Zero Scoping Project)
<p>This dataset was generated as an output for the DRI Mapping exercise carried out during the UKRI Net Zero Digital Research Infrastructure (DRI) Scoping Project undertaken from 2021-2023. The "README.md" provides more information about the dataset and how to use it.</p> <p>The report associated with this dataset is available at:</p> <p>https://doi.org/10.5281/zenodo.7805987</p>
EMB3Rs Open digital research data
<p>The EMB3Rs Unified Modelling Platform is a tool to assist on modelling the recovery of excess heat and its reuse to meet final energy demand within and beyond the boundaries of industrial sites. The tool consists of a knowledge base and several simulation modules.<br> This database comprises the research data generated in the course of the EMB3Rs project by using the EMB3Rs platform.<br> The pdf file contains the detailed description of the database content</p> <p>It has been deposited at Zenodo’s open data repository with DOI 10.5281/zenodo.7994255.</p>
A large EEG database with users' profile information for motor imagery Brain-Computer Interface research
<p><em><strong>Context </strong></em>: <br> We share a large database containing electroencephalographic signals from 87 human participants, with more than 20,800 trials in total representing about 70 hours of recording. It was collected during brain-computer interface (BCI) experiments and organized into 3 datasets (A, B, and C) that were all recorded following the same protocol: right and left hand motor imagery (MI) tasks during one single day session.<br> It includes the performance of the associated BCI users, detailed information about the demographics, personality and cognitive user’s profile, and the experimental instructions and codes (executed in the open-source platform OpenViBE).<br> Such database could prove useful for various studies, including but not limited to: 1) studying the relationships between BCI users' profiles and their BCI performances, 2) studying how EEG signals properties varies for different users' profiles and MI tasks, 3) using the large number of participants to design cross-user BCI machine learning algorithms or 4) incorporating users' profile information into the design of EEG signal classification algorithms.<br> <br> Sixty participants (Dataset A) performed the first experiment, designed in order to investigated the impact of experimenters' and users' gender on MI-BCI user training outcomes, i.e., users performance and experience, (Pillette & al). Twenty one participants (Dataset B) performed the second one, designed to examined the relationship between users' online performance (i.e., classification accuracy) and the characteristics of the chosen user-specific Most Discriminant Frequency Band (MDFB) (Benaroch & al). The only difference between the two experiments lies in the algorithm used to select the MDFB. Dataset C contains 6 additional participants who completed one of the two experiments described above. Physiological signals were measured using a g.USBAmp (g.tec, Austria), sampled at 512 Hz, and processed online using OpenViBE 2.1.0 (Dataset A) & OpenVIBE 2.2.0 (Dataset B). For Dataset C, participants C83 and C85 were collected with OpenViBE 2.1.0 and the remaining 4 participants with OpenViBE 2.2.0. Experiments were recorded at Inria Bordeaux sud-ouest, France.</p> <p><em><strong>Duration</strong> </em>: Each participant's folder is composed of approximately 48 minutes EEG recording. Meaning six 7-minutes runs and a 6-minutes baseline.</p> <p><br> <strong><em>Documents</em></strong><em> </em><br> <em>Instructions</em>: checklist read by experimenters during the experiments.<br> <em>Questionnaires</em>: the Mental Rotation test used, the translation of 4 questionnaires, notably the Demographic and Social information, the Pre and Post-session questionnaires, and the Index of Learning style. English and french version<br> <em>Performance</em>: The online OpenViBE BCI classification performances obtained by each participant are provided for each run, as well as answers to all questionnaires<br> <em>Scenarios/scripts</em> : set of OpenViBE scenarios used to perform each of the steps of the MI-BCI protocol, e.g., acquire training data, calibrate the classifier or run the online MI-BCI</p> <p><strong><em>Database </em></strong>: raw signals<br> Dataset A : N=60 participants<br> Dataset B : N=21 participants<br> Dataset C : N=6 participants<br> <br> The article that expained the database is available here:<br> Dreyer, P., Roc, A., Pillette, L. <em>et al.</em> A large EEG database with users’ profile information for motor imagery brain-computer interface research. <em>Sci Data</em> <strong>10</strong>, 580 (2023).<br> https://doi.org/10.1038/s41597-023-02445-z<br> </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.