This package contains the datasets and supplementary materials used in the IPIN 2023 Competition. Contents: - IPIN2023_Track4_CallForCompetition_v2.2.pdf: Call for competition including the technical annex describing the competition - 01-Logfiles: This folder contains 2 files for each Trials (Testing, Scoring01, Scoring02) - IPIN2023_T4_xxx.txt : data file containing ACCE, ROTA, MAGN, PRES, TEMP, GSBS, GOBS, POSI frames - IPIN2023_T4_xxx_gnss_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 2 MAT and KML files. It contains samples of reported estimations and the corresponding results. Just run script_Eval_IPIN2023.mat We provide additional information on the competition at: https://evaal.aaloa.org/2023/call-for-competition 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 2023 Competition Track 4 (Foot-Mounted IMU based Positioning, offsite-online), Zenodo 2023 https://doi.org/10.5281/zenodo.8399764 Check the citation policy at: https://doi.org/10.5281/zenodo.8399764 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 Maximilian Stahlke and Christopher Mutschler at Fraunhofer ISS, as well as Joaquín Torres-Sospedra from Universidade do Minho and Francesco Potortì and Antonino Crivello from ISTI-CNR Pisa, for their support in collecting the datasets. We extend our appreciation to the staff at the Museum for Industrial Culture (Museum Industriekultur) for their unwavering patience and invaluable support throughout our collection days.