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7 results for “NFDI”
Dataset: an overview of knowledge graphs in NFDI
<p>This dataset contains a list of knowledge graphs (KGs), KG software, KG publications and KG use cases in context of NFDI (German National Research Data Infrastructure). The related manuscript is submitted to a poster session at the <em>1st Conference on Research Data Infrastructure - Connecting Communities, </em>12. – 14. September 2023, Karlsruhe, Germany: 'Who is using Knowledge Graphs in NFDI? An overview by the Working Group "Knowledge Graphs"'.</p>
Knowledge graphs for interoperable NFDI: Digital editions
<p>Präsentation im Rahmen des Text+ FAIR February Meetup 2023: <em>I wie Interoperability, </em>15. Februar 2023.</p>
FAIR assessment practices: Experiences from KonsortSWD and BERD@NFDI [Dataset 2 KonsortSWD]
<p>The dataset refers to the poster, which presents FAIR assessment experiences in the context of the two NFDI consortia KonsortSWD and BERD@NFDI, employing the established Research Data Alliance's FAIR Data Maturity Model (RDA-FDMM) and the F-UJI Tool, an automated solution. RDA-FDMM, a manual technique, is more comprehensive, while the automated F-UJI tool effectively detects areas of improvement in metadata presentation that automated means can address. Our experiences highlight the need to examine both machine-readable as well as non-machine-readable elements and acknowledge automated tools' limitations, while valuing their insights. As the research ecosystem advances, metadata representation should be made increasingly machine-readable. We recommend a "FAIR by design" approach from the beginning to ensure alignment with FAIR principles in project outcomes. Continuous assessments during a project’s lifetime promote ongoing research data infrastructure improvements within the NFDI consortia context, contributing to NFDI infrastructure innovation and optimization.</p>
FAIR assessment practices: Experiences from KonsortSWD and BERD@NFDI [Dataset 1 BERD@NFDI]
<p>This dataset evidences the BERD@NFDI results of a poster, which is documented as a related work. The poster presents FAIR assessment experiences in the context of the two NFDI consortia KonsortSWD and BERD@NFDI, employing the established Research Data Alliance's FAIR Data Maturity Model (RDA-FDMM) and the F-UJI Tool, an automated solution. RDA-FDMM, a manual technique, is more comprehensive, while the automated F-UJI tool effectively detects areas of improvement in metadata presentation that automated means can address. Our experiences highlight the need to examine both machine-readable as well as non-machine-readable elements and acknowledge automated tools' limitations, while valuing their insights. As the research ecosystem advances, metadata representation should be made increasingly machine-readable. We recommend a "FAIR by design" approach from the beginning to ensure alignment with FAIR principles in project outcomes. Continuous assessments during a project's lifetime promote ongoing research data infrastructure improvements within the NFDI consortia context, contributing to NFDI infrastructure innovation and optimization.</p>
German NFDI, FAIRmat-NFDI, NOMAD, NOMAD OASIS, pynxtools, example datasets for atom probe microscopy and electron microscopy
<p>The following repository contains a collection of data and metadata files in different vendor formats which were collected in the fields of atom probe microscopy (LEAP instruments) and electron microscopy (Nion instruments). These files are meant for development and testing purposes of the nomad north-remote-tools-hub and the related nomad-nexus-parser software tools within the FAIRmat project.FAIRmat is a consortium lead by the Humboldt-Universität zu Berlin. FAIRmat is a member of the German Research Data Infrastructure (NFDI) initiative.</p> <p>A detailed description of the background and content of the individual files follows:</p> <p><strong>ger_berlin_haas_nionswift_multimodal.zip</strong><br> This is a dataset for testing how to load entire data and metadata from compressed NionSwift project files directly.<br> This is a dataset for testing the em_nion reader which handles files from Nion microscopes and NionSwift software.<br> The data were collected by Benedikt Haas from Humboldt-Universität zu Berlin. The parser was developed together<br> with Sherjeel Shabih also from Humboldt-Universität zu Berlin. Both work in the group of Prof. Christoph Koch.<br> EM.STEM.Nion.Dataset.1.zip is a dataset we used for an earlier version of this parser</p> <p><strong>APM.LEAP.Datasets.*.zip:</strong><br> This is a collection of two datasets for testing the generic nx_apm reader which handles commercial and community file formats for reconstructed ion position and ranging data from atom probe microscopy experiments. The datasets were collected by different authors.<br> <br> <strong>APM.LEAP.Datasets.1.zip:</strong><br> <em>R31_06365-v02.pos</em>, was shared by Jing Wang and Daniel Schreiber (both at PNNL). Details to the dataset are available<br> under the following DOIs:<br> https://doi.org/10.1017/S1431927618015386<br> https://doi.org/10.1017/S1431927621012241<br> <em>70_50_50.apt</em>, was a shared by Xuyang Zhou at his time with the Max-Planck-Institut für Eisenforschung GmbH as a open-source test data to the publication he lead on machine-learning-based techniques for composition profiling.<br> The dataset and publication is available via the following DOI and resources:<br> https://doi.org/10.1016/j.actamat.2022.117633<br> The dataset specifically is also available here:<br> https://github.com/RhettZhou/APT_GB/tree/main/example/Cropped_70_50_50<br> The range files <em>*.rng </em>and<em> *.rrng</em> range serve as examples to develop tools for parsing them and handle the formatting of range files. The scientific content of the range files was inspired by experiments but is not related to the above-mentioned atom probe datasets<br> and should not be used to analyze these test data for more than pure development purposes.<br> Use instead your own data and matching range files for scientific analyses.</p> <p><strong>APM.LEAP.Datasets.2.zip</strong><br> <em>R18_53222_W_18K-v01.epos</em>, was shared with Markus Kühbach by Andrew Breen<br> during their time at the Max-Planck-Institut für Eisenforschung GmbH.<br> <br> We would like to invite the community to use the nomad infrastructure and support us with<br> sharing data and dataset which we can then use to improve the file format parsing, the reading capabilities,<br> and analyses services of the nomad infrastructure so that the community can profit again from these developments.</p> <p><strong>aut_leoben_leitner.zip</strong><br> is the dataset associated to the grain boundary solute segregation case study discussed in https://arxiv.org/abs/2205.13510</p> <p><strong>usa_portland_wang.zip</strong><br> is the dataset associated with the ODS steel specimen dataset, which is a good example for testing and learning iso-surface<br> based analyses with the paraprobe-toolbox. This dataset was mentioned as one of the test cases in https://arxiv.org/abs/2205.13510</p> <p><strong>ger_erlangen_felfer_ck10.zip</strong><br> is the Ck10 for fundamentals dataset from the atom-probe-toolbox<br> https://github.com/peterfelfer/Atom-Probe-Toolbox/tree/master/test%20data/Ck%2010%20steel%20for%20fundamentals</p> <p><strong>usa_denton_smith_apav_gbco.zip</strong><br> is the GBCO-type dataset from J. Smith and M. Young discussed in their following publications:<br> https://doi.org/10.1017/S1431927621012794 and https://github.com/openjournals/joss-reviews/issues/4862<br> <br> <strong>usa_denton_smith_apav_si.zip</strong><br> is a very small dataset in POS, ePOS, APT, RNG, and RRNG for development and testing purposes.<br> The dataset is a part of APAV mentioned here<br> https://gitlab.com/jesseds/apav/-/tree/JOSS/apav/tests</p>
Infrastructure Networks within NFDI: Survey among Institutions partnering with NFDI consortia
<p>This dataset is part of Base4NFDI's proposal to acquire funding for developing NFDI-wide basic services.</p> <p>Base4NFDI rolled out a survey to quantitatively illustrate the extent of its ties to German and international infrastructures, particularly in the area of computing. The survey - Infrastructure Networks within NFDI - ran based on a Google Form. The cleaned and anonymized dataset lists these infrastructure ties for 113 unique institutions and has a total of 163 entries as some institutions are partners to multiple consortia. The dataset does not cover all 200+ member institutions of the NFDI Association.</p> <p> </p>
German NFDI, FAIRmat-NFDI, NOMAD, NOMAD Oasis, pynxtools, pynxtools-em, NeXus, example datasets for electron microscopy
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