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. A detailed description of the background and content of the individual files follows: ger_berlin_haas_nionswift_multimodal.zip This is a dataset for testing how to load entire data and metadata from compressed NionSwift project files directly. This is a dataset for testing the em_nion reader which handles files from Nion microscopes and NionSwift software. The data were collected by Benedikt Haas from Humboldt-Universität zu Berlin. The parser was developed together with Sherjeel Shabih also from Humboldt-Universität zu Berlin. Both work in the group of Prof. Christoph Koch. EM.STEM.Nion.Dataset.1.zip is a dataset we used for an earlier version of this parser APM.LEAP.Datasets.*.zip: 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. APM.LEAP.Datasets.1.zip: R31_06365-v02.pos, was shared by Jing Wang and Daniel Schreiber (both at PNNL). Details to the dataset are available under the following DOIs: https://doi.org/10.1017/S1431927618015386 https://doi.org/10.1017/S1431927621012241 70_50_50.apt, 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. The dataset and publication is available via the following DOI and resources: https://doi.org/10.1016/j.actamat.2022.117633 The dataset specifically is also available here: https://github.com/RhettZhou/APT_GB/tree/main/example/Cropped_70_50_50 The range files *.rng and *.rrng 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 and should not be used to analyze these test data for more than pure development purposes. Use instead your own data and matching range files for scientific analyses. APM.LEAP.Datasets.2.zip R18_53222_W_18K-v01.epos, was shared with Markus Kühbach by Andrew Breen during their time at the Max-Planck-Institut für Eisenforschung GmbH. We would like to invite the community to use the nomad infrastructure and support us with sharing data and dataset which we can then use to improve the file format parsing, the reading capabilities, and analyses services of the nomad infrastructure so that the community can profit again from these developments. aut_leoben_leitner.zip is the dataset associated to the grain boundary solute segregation case study discussed in https://arxiv.org/abs/2205.13510 usa_portland_wang.zip is the dataset associated with the ODS steel specimen dataset, which is a good example for testing and learning iso-surface based analyses with the paraprobe-toolbox. This dataset was mentioned as one of the test cases in https://arxiv.org/abs/2205.13510 ger_erlangen_felfer_ck10.zip is the Ck10 for fundamentals dataset from the atom-probe-toolbox https://github.com/peterfelfer/Atom-Probe-Toolbox/tree/master/test%20data/Ck%2010%20steel%20for%20fundamentals usa_denton_smith_apav_gbco.zip is the GBCO-type dataset from J. Smith and M. Young discussed in their following publications: https://doi.org/10.1017/S1431927621012794 and https://github.com/openjournals/joss-reviews/issues/4862 usa_denton_smith_apav_si.zip is a very small dataset in POS, ePOS, APT, RNG, and RRNG for development and testing purposes. The dataset is a part of APAV mentioned here https://gitlab.com/jesseds/apav/-/tree/JOSS/apav/tests