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11 results for “FAIR Principles”
Dataset Dental research data availability and quality according to FAIR principles
<p>This dataset contains open access publications in EPMC dental journals from 2016 to 2021 and 500 non-open access dental publications. We evaluated the level of compliance with the FAIR principles. The original dataset and codebook are attached. </p>
Dissecting the FAIR Guiding Principles - Key Categories, Core Concepts, Focus Elements, and Harmonized Indicators
<p>A comprehensive workbook created to facilitate and document the process of decomposing the FAIR Guiding Principles and mapping them to key categories, requirements, core concepts, focus elements, and harmonized indicators. It also contains a complete list of the indicators.</p>
Dataset do DH2020 [The Lusophone Digital Humanities and What they (we) are doing from the South: textual corpus analysis and FAIR principles to tackle Hegemony]
<p>Planilha de dados recuperados do Google Scholar utilizado na análise e apresentação da pesquisa empírica intitulada - <strong>The Lusophone Digital Humanities and What they (we) are doing from the South: textual corpus analysis and FAIR principles to tackle Hegemony </strong>- no evento <strong>DH2020 Ottawa</strong>: <a href="https://hcommons.org/deposits/item/hc:32051/">https://hcommons.org/deposits/item/hc:32051/</a></p>
Dataset for "Reproducibility and FAIR Principles: The Case of a Segment Polarity Network Model"
<p>Results of random sampling the segment polarity network with the simulator COPASI. These results correspond to Fig. 2 and Table 2 of von Dassow et. al (2000) (doi:10.1038/35018085). The random sampling was carried out with file vonDassow2000_1x4_alt.cps with COPASI version 4.39 selecting the appropriate parameter set named (1-7) and setting the number of repeats in the parameter scan task to the desired number. Full results of sampling are in files prefixed with the row number of Table 2 of von Dassow et. al (2000) and extension .tsv. Results with scores below 0.2 are in corresponding files with the word "-hits" in the filename. Includes also results from a time course simulation of this model using four different simulators (COPASI, Tellurium, Amici, and VCell). Finally also contains a study on multistability carried out by random sampling of parameters and initial conditions (run with COPASI). Markdown file README.md contains more detailed explanation. See also https://github.com/pmendes/models/tree/main/vonDassow2000</p>
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>
Assessing the use of HL7 FHIR for implementing the FAIR guiding principles: A case study of the MIMIC-IV emergency department module
<p><strong>Objective</strong> <br>To assess the use of Health Level Seven Fast Healthcare Interoperability Resources (FHIR<sup>®</sup>) for implementing the Findable, Accessible, Interoperable, and Reusable guiding principles for scientific data (FAIR). Additionally, present a list of FAIR implementation choices for supporting future FAIR implementations that use FHIR. <br><br><strong>Material and Methods</strong> <br>A case study was conducted on the Medical Information Mart for Intensive Care-IV Emergency Department dataset (MIMIC-ED), a deidentified clinical dataset converted into FHIR. The FAIRness of this dataset was assessed using a set of common FAIR assessment indicators. <br><br><strong>Results</strong> <br>The FHIR distribution of MIMIC-ED, comprising an implementation guide and demo data, was more FAIR compared to the non-FHIR distribution. The FAIRness score increased from 60 to 82 out of 95 points, a relative improvement of 37%. The most notable improvements were observed in interoperability, with a score increase from 5 to 19 out of 19 points, and reusability, with a score increase from 8 to 14 out of 24 points. A total of 14 FAIR implementation choices were identified. <br><br><strong>Discussion</strong> <br>Our work examined how and to what extent the FHIR standard contributes to FAIR data. Challenges arose from interpreting the FAIR assessment indicators. This study stands out for providing a real-world example of a dataset that was made more FAIR using FHIR. <br><br><strong>Conclusion</strong> <br>To the best of our knowledge, this is the first study that formally assessed the conformance of a FHIR dataset to the FAIR principles. FHIR improved the accessibility, interoperability, and reusability of MIMIC-ED. Future research should focus on implementing FHIR in research data infrastructures. Keywords: FAIR Guiding Principles, HL7 FHIR, Reusable Data, MIMIC-IV</p>
Research Space and DMPTool - Streamlining the research lifecycle and enhancing FAIR principles with a series of interoperable tools
<p>A video demonstration of the integration between the Electronic Lab Notebook, RSpace, and the DMPTool. Presented at the FORCE11 annual conference on December 7, 2021.</p>
Third FAIRmat users meeting Nov2023 - FAIR Data Principles in Perovskite Solar Cell Research using NOMAD - Daniel Baumann
<p>Daniel Baumann (doctoral research project at KIT in the group of Ulrich Paetzold) highlights how NOMAD Oasis supports experimental materials researchers in the field of perovskite photovoltaics. A live demonstration of experimental planning, documentation, as well as automated data evaluation is presented. Particularly, in conjunction with a highly repeatable robotic spin-coating setup, the realization of this vast potential may be closer than anticipated. </p>
Assessing the use of HL7 FHIR for implementing the FAIR guiding principles: A case study of the MIMIC-IV emergency department module
Open the record for dataset details and reuse information.
FAIR principles images
<p>Images about the FAIR data principles</p>
The effects of fair allocation principles on energy system model designs
<p>This is the associated dataset to <a href="https://github.com/OskarVagero/highRES-Europe-WF/tree/MENOFS">https://github.com/OskarVagero/highRES-Europe-WF/tree/MENOFS </a>, which contains the data necessary to replicate the study. </p> <p>In addition to the data required to replicate the study, we also include six pre-generated model results (.db), which represent the "top performers", as well as the cost-optimal model run. </p> <ul> <li>Weather data is based on ERA5, from ECMWF (https://doi.org/10.1002/qj.3803) </li> <li>Demand data is based on the Interannual Electricity Demand Calculator (https://zenodo.org/records/10820928)</li> <li>Existing hydropower capacity is based on the JRC Hydropower database (https://zenodo.org/records/5215920)</li> <li>Historic electricity generation from hydropower is based on the U.S. Energy Information Administration (https://www.eia.gov/international/data/world/electricity/electricity-generation)</li> </ul> <p>More details on how to use the data can be found in the GitHub repository. </p>
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