This package contains the datasets and supplementary materials used in the IPIN 2022 Competition. Contents:- IPIN2022_Track4_CallForCompetition_v1.3.pdf: Call for competition including the technical annex describing the competition - 01-Logfiles: This folder contains 2 files for each Trials (Testing, Scoring01, Scoring02) - IPIN2022_T4_xxx.txt : data file containing ACCE, ROTA, MAGN, PRES, TEMP, GSBS, GOBS, POSI frames - IPIN2022_T4_xxx_yyy_ephem.nav : for trajectory estimation. - 02-Supplementary_Materials: This folder contains the datasheet files of the different sensors, a static logfile of about 12 hours that can be used for sensors bias estimation (Allan Variance) and a logfile of about 1 minute that can be used to calibrate the magnetometer sensor (Magnetometer Calibration). - 03-Evaluation: This folder contains the scripts used to calculate the competition metric, the 75th percentile on all evaluation points. It requires Matlab Mapping Toolbox. We also provide ground truth of the 2 scoring trials as CSV files (with full rate @60Hz and with evaluation point only). It contains samples of reported estimations and the corresponding results. Just run script_Eval_IPIN2022.mat We provide additional information on the competition at: https://evaal.aaloa.org/2022/call-for-competitions Citation Policy:Please, cite the following works when using the datasets included in this package: Ortiz, M.; Zhu, N.; Ziyou L.; Renaudin, V. Datasets and Supporting Materials for the IPIN 2022 Competition Track 4 (Foot-Mounted IMU based Positioning, offsite-online), Zenodo 2022https://doi.org/10.5281/zenodo.10497364 Check the citation policy at: https://doi.org/10.5281/zenodo.10497364 Contact: For any further questions about the database and this competition track, please contact: Miguel Ortiz (miguel.ortiz@univ-eiffel.fr) at the University Gustave Eiffel, France. Ni Zhu (ni.zhu@univ-eiffel.fr) at the University Gustave Eiffel, France. Acknowledgements: We thank Frederic Le-Bourhis and Aravind Ramseh from Univ-Eiffel for their support in collecting the datasets. We extend our appreciation to the staff at the Nantes Central station for their invaluable support throughout our collection days.