Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
339
datasets available to search
ShareScore release 0.9.0
Dataset results
339 results for “Fairness”
DATASET ON TEST FAIRNESS IN A MANDATED ASSESSMENT
<p>Data collected for Masters dissertation, as part of the requirements for a Master of Philosophy degree in Measurement and Evaluation at the University of Cape Coast, Ghana.</p>
Figure 3. Chromatogram from the sample fairs MAC 02 and ARA 0 in Detection of enteropathogens and research of pesticide residues in Lactuca sativa from traditional and agroecological fairs
Figure 3. Chromatogram from the sample fairs MAC 02 and ARA 0, with the peaks of Diphenoconazole compared with the pattern.
M4.4 (associated data) - FAIR-IMPACT Review of Semantic Artefact Catalogues and technologies
<p>This dataset (version 1) takes the form of a spreadsheet corresponding to the associated data described by <a href="../records/12799796" target="_blank" rel="noopener"><strong>M4.4 - Review of Semantic Artefact Catalogues and guidelines for serving FAIR semantic artefacts in EOSC</strong></a></p> <p>The spreadsheept (available here in ODS format) contains the listing of Semantic Artefact Catalogues (SACs) done within FAIR-IMPACT's WP4, their classifications (by status, type, discipline and technology) and the evaluation of their FAIR-enabling dimensions. </p> <p>A "live" version of this spreadsheet is available as an open Google Sheet open for comments and suggestions. We will take external contributions and comments into consideration when producing new verion of this dataset. Contributions could be of several types: </p> <ul> <li>New SAC or modification of the ones currently identified;</li> <li>New SAC technology or modification of the ones currently identified;</li> <li>New FAIR-enabling assessment or modification of the ones currently available.</li> </ul> <p>For more information, interested parties may contact the authors.</p> <p> </p>
WP2 D2.2 questionnaire results June 2017 Maker Faire Barcelona
<p>The data provide the basis for the analysis in D2.3, section 3: you can download it <a href="http://make-it.io/deliverables/d2-3-final-make-it-monitoring-and-assessment-framework-a-new-analysis-of-making-in-europe/">here</a>. The results and analyses in this section have been derived from interviews of a random sample of 42 Maker initiatives present at the Barcelona Maker Faire, 16-18 June 2017, out of 88 registered as present. The Faire consisted of a highly diverse set of exhibitors drawn from across Barcelona and Catalonia. European experts on the <strong>MAKE-IT</strong> team conducted the interviews and validated that the Barcelona maker scene is quite typical of other large cities across Europe. The results obtained are combined, where relevant, with the instrument’s version 3 results of the ten <strong>MAKE-IT</strong> case studies from across the whole of Europe, together with relevant insights from <a href="http://make-it.io/deliverables/d3-2-final-case-study-report-focusing-on-cross-case-analysis/">D3.2</a>.</p> <p>See also: <a href="http://make-it.io/open-data-api/">http://make-it.io/open-data-api/</a></p>
Experiment Result Plots of Data Stewardship (FAIR - Assignment 1)
<p>These plots show the results of the experiment by creating a scatterplot of the variables and a line plot.</p>
Assessing Negative Carbon Dioxide Emissions from the Perspective of a National 'Fair Share' of the Remaining Global Carbon Budget: Supplementary Material
<p>Detailed calculations supporting the results in the published paper, <em>Assessing Negative Carbon Dioxide Emissions from the Perspective of a National 'Fair Share' of the Remaining Global Carbon Budget</em>, <a href="https://link.springer.com/journal/11027">Mitigation and Adaptation Strategies for Global Change</a>, DOI: <a href="https://doi.org/10.1007/s11027-019-09881-6">10.1007/s11027-019-09881-6</a>.</p> <ul> <li><strong>IE-CO2-Quota-2015.ods</strong>: Spreadsheet/workbook in <a href="http://opendocumentformat.org/">Open Document</a> format. Includes table and charts as presented in the paper. Prepared using <a href="http://www.libreoffice.org">LibreOffice</a> (v 5.0+). Should also be accessible also in Microsoft Excel, but some formatting or functionality may be lost.</li> <li><strong>IE-CO2-Quota-2015.ipynb</strong>: Mathematical background and cross-check of detailed calculations in interactive <a href="https://jupyter.org/">Jupyter notebook</a> format (coding in <a href="https://www.python.org/">python</a>).</li> <li><strong>IE-CO2-Quota-2015-ipynb.html</strong>: Static HTML version of the <strong>IE-CO2-Quota-2015.ipynb</strong> suitable for simple viewing/printing.</li> <li><strong>IE-CO2-Quota-2015-ipynb.pdf</strong>: Static version of the <strong>IE-CO2-Quota-2015.ipynb</strong> suitable for simple viewing/printing.</li> </ul>
Dataset [Amazon or Amazônia: FAIR principles applied on using terms and concepts in the Scopus]
<p>This is the raw data behind the publication:</p> <p>Ramos, M. G.; de Souza, R. F. Amazon or Amazônia: FAIR principles applied on using terms and concepts in the base Scopus. XX ENANCIB 2019.</p> <p>The present paper reports an empirical research that sought to analyze possible semantic deviations, ambiguities and false positives in the retrieval of documents in the <strong>Scopus database</strong> through search expressions of the terms <strong>Amazon and Amazon, from 2008 to 2018.</strong> From the sample selection <strong>composed of 40 most cited articles of both terms</strong>, a comparative analysis was performed between the author's keywords versus the keywords indicated by the database and the subject areas retrieved by the chosen terms were evaluated. In addition, Iramuteq software was used for data analysis and visualization. The study aims to contribute to a better understanding of the triad: concepts, keywords and terms regarding database information retrieval and to verify the application of the findable, accessible, interoperable and reusable principles, in the knowledge domain analysis as part of the universe of the Knowledge Organization System. In addition, there was a difficult reciprocity between authors' keywords and database keywords that may imply some semantic deviation and ambiguities in document retrieval.may imply some semantic deviation and ambiguities in document retrieval.</p> <p>Link: <a href="https://brapci.inf.br/index.php/res/v/123309">https://brapci.inf.br/index.php/res/v/123309</a></p>
FAIR Jupyter Knowledge Graph
<p><a href="https://w3id.org/fairjupyter/">FAIR Jupyter</a> is a knowledge graph representation of <a href="https://doi.org/10.5281/zenodo.8226725">Dataset of a Study of Computational reproducibility of Jupyter notebooks from biomedical publications</a>. <br>This repository contains the data, mapping, and the RDF files for each entity represented in the FAIR Jupyter KG.</p> <p>Folder structure:</p> <p>data: contains the CSV files that are exported for each entity type from the <a href="https://doi.org/10.5281/zenodo.8226725">original sqlite database</a>.</p> <p>mapping: contains the RML and YARRML mapping files for each entity type of FAIR Jupyter KG.</p> <p>kg: contains the RDF files created in N-Triples format for each entity type of FAIR Jupyter KG.</p> <p>The code for creating the FAIR Jupyter Knowledge graph is available here: https://github.com/fusion-jena/fairjupyter</p>
Evaluation notebook and files for FAIR Workbench user evaluation
<p>This archive contains the Jupyter notebook and associated (image) files used in the June 2021 evaluation of the FAIR Workbench.</p>
Atom probe tomography nomad-FAIR demonstrator dataset R76-30057-v01.epos.apth5
<p>This is the dataset of an atom probe tomography experiment which is provided open source for testing the possibility of implementing an open source encyclopedia for experimental materials science datasets, including techniques to begin with such as Scanning Transmission Electron Microscopy (STEM), Multidimensional Photo Emission Spectroscopy (MPES), and Atom Probe Tomography (APT) / Field Ion Microscopy (FIM).</p> <p><strong>This repository serves three aims:</strong></p> <p>1. The dataset is of scientific interest. Specifically, it captures the result of a cutting-edge APT experiment whose details are going to be reported in an upcoming publication by Shyam Katnagallu and coworkers.</p> <p>2. The dataset contributes to tests of an extension to "The NOMAD Laboratory" (https://nomad-coe.eu/): nomad-FAIR. Specifically, to test various aspects of an automatized metadata parsing and processing pipeline to enable the extraction of domain-specific JSON metadata files into a NOMAD-conformant JSON file, ultimately aiming for searchable and repurposable dataset documentation. This serves two purposes: on the one hand to contextualize each dataset within NOMAD. On the other hand to serve as a starting point to parse potential interesting content from the heavy data HDF5 file to reduce unnecessary file access.<br> The implementation of nomad-FAIR is coordinated by Markus Scheidgen.<br> The APT domain-specific parser is developed by Markus Kühbach.</p> <p>3. The dataset constitutes further a test of an open format specification for storing atom probe tomography data using the Hierarchical Data Format (HDF5). This is a recent initiative of the International Field Emission Society's (IFES) atom probe tomography technical committee. In this repository it is detailed an exemplar proposal of how to store acquisition-side relevant results and context of an APT experiment into a HDF5 file and complementary metadata files such as JSON. Implementation of this HDF5-based storage solution for APT data is lead by Markus Kühbach.</p> <p><strong>The organization of this repository with respect to above aims is as follows:</strong></p> <p>-The original EPOS file of the measured is contained in the compressed *.epos.tar.gz archive.</p> <p>-The *.apth5 file is a transcoded version of the EPOS file. Therein, x,y,z data columns are stripped.</p> <p>-The correspondingly named *.json file is the file which nomad-FAIR parses metadata from.</p> <p>-Other files constitute logs of the transcoding process.</p> <p><br> <strong>Funding:</strong><br> The work was partially supported by BiGmax, the Max Planck Society's Research Network on Big-Data-Driven Materials-Science.</p>
Atom probe tomography nomad-FAIR demonstrator dataset R76-31053-v01.epos.apth5
<p>This is the dataset of an atom probe tomography experiment which is provided open source for testing the possibility of implementing an open source encyclopedia for experimental materials science datasets, including techniques to begin with such as Scanning Transmission Electron Microscopy (STEM), Multidimensional Photo Emission Spectroscopy (MPES), and Atom Probe Tomography (APT) / Field Ion Microscopy (FIM).</p> <p><strong>This repository serves three aims:</strong></p> <p>1. The dataset is of scientific interest. Specifically, it captures the result of a cutting-edge APT experiment detailed in an upcoming paper by Ye Wei and coworkers.</p> <p>2. The dataset contributes to testing an extension of "The NOMAD Laboratory" (https://nomad-coe.eu/): nomad-FAIR. Specifically, to test various aspects of its automatized metadata parsing and processing pipeline to enable the extraction of domain-specific JSON metadata files into a NOMAD-conformant JSON file, ultimately aiming for searchable and repurposable dataset documentation. This serves two purposes: on the one hand to contextualize each dataset within NOMAD. On the other hand to serve as a starting point to parse potential interesting content from the heavy data HDF5 file to reduce unnecessary file access.<br> The implementation of nomad-FAIR is coordinated by Markus Scheidgen.<br> The APT domain-specific parser is developed by Markus Kühbach.</p> <p>2. The dataset constitutes further a test of an open format specification for storing atom probe tomography data using the Hierarchical Data Format (HDF5). This is a recent initiative of the International Field Emission Society's (IFES) atom probe tomography technical committee. In this repository it is detailed an exemplar proposal of how to store acquisition-side relevant results and context of an APT experiment into a HDF5 file and complementary metadata files such as JSON. Implementation of this HDF5-based storage solution for APT data is lead by Markus Kühbach.</p> <p><br> <strong>The organization of this repository with respect to above aims is as follows:</strong></p> <p>-The original EPOS file of the measured is contained in the compressed *.epos.tar.gz archive.</p> <p>-The *.apth5 file is a transcoded version of the EPOS file. Therein, x,y,z data columns are stripped.</p> <p>-The correspondingly named *.json file is the file which nomad-FAIR parses metadata from.</p> <p>-Other files constitute logs of the transcoding process.</p> <p><br> <strong>Funding:</strong><br> The work was partially supported by BiGmax, the Max Planck Society's Research Network on Big-Data-Driven Materials-Science.</p>
Datset of the paper entitled "FAIR degree assessment in agriculture datasets using the F-UJI tool".
<p>This is a dataset of our research realised recently, which contains tested results (json files) by F-UJI tool and FAIR assesment reports of tested repositories.</p>
Aerodynamic characterisation of porous fairings : pressure drop and Laser Doppler Velocimetry measurements
<p>Aviation has become a mass transportation industry, and all prospective studies foresee growth in this sector. Among the challenges, noise in the vicinity of airports has gone from a marginal annoyance to a real public health concern. To address this problem, as well as others such as fuel consumption, aircraft manufacturers are considering radically new aircraft architectures that could enter service quickly. In the meantime, however, the noise of traditional aircraft must be reduced significantly. Aircraft noise, during takeoff and landing, results primarily from a combination of (i) engine noise, which is generated by the fan and jet, and (ii) airframe noise, primarily due to the landing gear (LG) and high lift devices (HLD), the latter including slats and trailing edge flaps, which are deployed at low speeds to increase lift. During takeoff, engine noise remains dominant, while on approach and landing, engines operate at low speeds (typically 50% of N1), and airframe noise becomes a significant contributor, especially for newer aircraft equipped with latest generation turbofans. Its mitigation is therefore of primary interest.<br> However, due to the strong integration constraints imposed by other disciplines than acoustics on components such as LGs and HLDs, the development of noise reduction technologies (NRT) on these airframe components has been limited. This lack of breakthroughs is also due to the complexity of flow physics, and thus our still limited knowledge of airframe noise generation mechanisms. The noise of the landing gear, slats and flaps has been studied on a real and reduced scale, mainly on the basis of experimental means. The maturity of numerical simulations now allows to study the mechanisms of the noise sources on various complex configurations. Moreover, numerical simulation methods can be sufficiently accurate to predict the noise generated by such configurations. In order to take the next step in the maturity of numerical prediction, these NIRs must be accurately evaluated and modeled. Experimental data based on academic configurations are therefore needed to validate the new tools and numerical models. One promising NRT is the use of a fairing in front of the landing gear to reduce the noise of this system. The present study aims at collecting an experimental database (pressure drop and turbulence characteristics) of several fairing solutions in order to have validation test cases for CFD simulation and thus develop new models for such complex geometries. The fairing samples are thus tested on the "Acoustic and Aerothermal Bench" (B2A), by measuring the pressure drop of each sample and the flow field by Laser Doppler Velocimetry (LDV). The experimental methodology will be presented first. The database will then be described. Some technical validations will also be proposed on the basis of a comparison with the literature.</p>
NCAS CDAO Sky-Camera Time-Lapse Video for 2008-10-05 11:00 UTC (showing Cumulus humilis clouds, which are also known as fair weather cumulus).
<p>A time-lapse video showing Cumulus humilis clouds, which are also known as fair weather cumulus. This video has been created from images taken by the Sky-Camera at the National Centre for Atmospheric Science (NCAS) Capel Dewi Atmospheric Observatory (CDAO) near Aberystwyth, UK - formerly known as the Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar Facility. The images are freely available under a UK Open Government Licence from http://tinyurl.com/nerc-mstrf-sky-camera/ . For more details visit http://mst.nerc.ac.uk .</p>
F-UJI and FAIR Enough tool comparison dataset (European Research Data Landscape study)
<p>Dataset used to compare the assessment results on the levels of Findability, Accessability, Interoperability and Reusability of datasets in a sample of repositories, by means of the F-UJI FAIR data assessment tool and FAIR-Enough assessment tool. Assessment carried out for the European Research Data Landscape study.</p>
Is data sharing in LCA FAIR
<p>Data for Setac Abstract - </p> <p>In the light of rising awareness, and growing need of better data management across disciplines, it is pertinent to investigate how the FAIR principles are utilized in the LCA domain. The purpose of this research is to investigate the status quo of data sharing by LCA practitioners. This study will look into data shared in relation to research outputs (e.g. peer reviewed articles). The life cycle inventory (LCI) is the most common data that is re-used, hence this study investigates how the LCI is shared in peer reviewed articles. A review of the findability, accessibility, interoperability and re-usability of the LCI data of 25 peer reviewed articles was performed. This study highlights although there is growing awareness on the importance of data sharing , the lack of a clear guidelines within the LCA domain as well as limited infrastructure is a major barrier in implementing FAIR principles. Research data sharing is beyond the sole responsibility of individual researchers. The overall research and funding infrastructure must consider the diversity of practices, differences in fields, facilitate the sharing of a broad range of research outputs. Current gaps in academic data sharing can be seen as opportunities to build a common framework</p>
Video Tutorial for the FAIR SAMPLES Template
<p>This video tutorial with audio contains FAIR WISH expert demonstrations and explanations for using the <em>FAIR SAMPLES Template</em>” of the project <strong>FAIR W</strong>orkflows to establish <strong>I</strong>GSN for <strong>S</strong>amples in the <strong>H</strong>elmholtz Association (FAIR WISH) funded by the Helmholtz Metadata Collaboration (HMC). It is part of Deliverable D3 of work package 3 “<em>Domain-specific metadata for terrestrial and aquatic Geo-Bio samples (vegetation, sediment, water, rocks</em>)”.</p> <p>The ultimate goal of the video tutorial is to instruct users how to use the FAIR SAMPLES Template. The video begins with an introduction to the Helmholtz Metadata Collaboration (HMC), the FAIR WISH project, the International Generic Sample Number (IGSN) and the overall motivation for making samples uniquely identifiable and citable by IGSN assignment. The content then changes to the main part of the tutorial, focussing on the FAIR SAMPLES “Excel” Template, its content and functionalities. In this part, the speaker guides the audience on how to use the template with the different categories of metadata for a sample.</p> <p><a title="The FAIR WISH project" href="https://dataservices-cms.gfz-potsdam.de/samples/the-fair-wish-project">FAIR WISH</a> is a joint project between the Helmholtz Centres GFZ, AWI and Hereon. It was was funded 2022-2023 by the Initiative and Networking Fund of the Helmholtz Association within the <a title="https://helmholtz-metadaten.de/en/projects/hmc-projects-2020" href="https://helmholtz-metadaten.de/en/projects/hmc-projects-2020" target="_blank" rel="noopener noreferrer">HMC Project Cohorte 2020</a> of the <a title="https://helmholtz-metadaten.de/en" href="https://helmholtz-metadaten.de/en" target="_blank" rel="noopener noreferrer">Helmholtz Metadata Collaboration Platform HMC</a>.</p>
EOSC Nordic WP4 FAIR incentives interview data
<p>Interview data were collected and analysed as part of EOSC Nordic WP4 FAIR. The main goal was to have input about the challenges and incentives of FAIRification of the research data from different stakeholder groups (researchers, data stewards/research support at institutions, representatives of research administration, and funders)</p>
FAIR-IMPACT Synchronisation Force: preliminary data gathered from projects and intiatives
<p>Between the 21st and 24th of November 2022 more than 120 representatives of projects and initiatives funded and/or supported by the European Commission H2020 and Horizon Europe programmes and operating in the EOSC framework joined the FAIR-IMPACT Synchronisation Force collaborative sessions to assess the implementation of the FAIR principles across research projects and initiatives in the EOSC framework.</p> <p>The team focussed on work related to FAIR-IMPACT focus areas, namely Metrics and assessing FAIRness (session 1), Persistent Identifiers (Session 2), Trustworthy and FAIR-enabling repositories (Session 3) and Metadata, semantics and interoperability (Session 4).</p> <p>In order to ensure an interactive meeting, participants were asked to complete a preliminary survey according to the sessions that they would join and complete 4 questions. The inputs received constituted the starting point for the discussions during the Synchronisation Force Workshop and are collected here as pdf files.</p> <p> </p>
Guideline for a FAIR Cultural Studies Research Data Management
<p>Dies ist die <strong>Datenpublikation</strong> (Ausgangsdateien, Abbildungen, Materialien zur Nachnutzung) für die NFDI4Culture Handreichung „Handreichung für ein FAIRes Management kulturwissenschaftlicher Forschungsdaten“.</p> <p>Die <strong>Online-Handreichung</strong> ist verfügbar unter <a href="https://nfdi4culture.de/go/E3625">https://nfdi4culture.de/go/E3625</a>.</p> <p>Als <strong>PDF</strong> ist diese Handreichung verfügbar unter <a href="https://doi.org/10.5281/zenodo.7716941">https://doi.org/10.5281/zenodo.7716941</a>.</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.