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Datasets and Supporting Materials for the IPIN 2016 Competition Track 3 (Smartphone-based, off-site)

<p>This package contains the datasets and supplementary materials&nbsp;used in the IPIN 2016 Competition (Alcal&aacute;, Spain).</p> <p><strong>Contents:</strong></p> <ol> <li>Track3_LogfileDescription_and_SupplementaryMaterial.pdf:&nbsp;Description of the logfiles and supplemental materials.</li> <li>Track3_TechnicalAnnex.pdf:&nbsp;Technical annex describing the competition&nbsp;</li> <li>01-Logfiles:&nbsp;This folder contains a subfolder with the 17 training logfiles&nbsp;and a subfolder with the 9 blind evaluation logfiles as provided&nbsp;to competitors.</li> <li>02-Supplementary_Materials:&nbsp;This folder contains the Matlab/octave parser, the raster maps&nbsp;and the visualization of the training routes.</li> <li>03-Evaluation:&nbsp;This folder contains the scripts used to calculate the competition&nbsp;metric, the 75th percentile on the 578 evaluation points. The ground&nbsp;truth is also provided in MatLab format and as a&nbsp;CSV file. Since the&nbsp;results must be provided with a 2Hz freq. starting from apptimestamp 0,&nbsp;the GT includes the closest timestamp matching the timing provided&nbsp;by competitors.</li> </ol> <p><strong>Please, cite the following works when using the&nbsp;datasets included in this package:</strong></p> <ul> <li>Torres-Sospedra, J.; Jim&eacute;nez, A.; Knauth, A.; Moreira, A.; Beer, Y.; Fetzer, T.;&nbsp;Ta, V.-C.; Montoliu, R.; Seco, F.; Mendoza, G.; Belmonte, O.; Koukofikis,&nbsp;A.; Nicolau, M.J.; Costa, A.; Meneses, F.; Ebner, F.; Deinzer, F.; Vaufreydaz, D.;&nbsp;Dao, T.-K.; and Castelli, E.&nbsp;The Smartphone-based Off-Line Indoor Location&nbsp;Competition at IPIN 2016: Analysis and Future work Sensors Vol. 17(3), 2017.&nbsp;<a href="http://dx.doi.org/10.3390/s17030557">http://dx.doi.org/10.3390/s17030557</a></li> <li>Jimenez, A.R.; Mendoza-Silva, G.M.; Montoliu, R.; Seco, F.; Torres-Sospedra, J.&nbsp;Datasets and Supporting Materials for the IPIN 2016 Competition Track 3 (Smartphone-based, off-site).&nbsp;<a href="http://dx.doi.org/10.5281/zenodo.2791530">http://dx.doi.org/10.5281/zenodo.2791530</a></li> </ul> <p><strong>Additional information can be found at:</strong></p> <ul> <li><a href="http://evaal.aaloa.org/2016/competition-home">http://evaal.aaloa.org/2016/competition-home</a></li> <li><a href="http://indoorloc.uji.es/ipin2016track3/">http://indoorloc.uji.es/ipin2016track3/</a>&nbsp; &nbsp;&nbsp;</li> </ul> <p><strong>For any further questions about the database and this competition track, please contact:&nbsp;</strong></p> <ul> <li>Joaqu&iacute;n Torres (<a href="mailto:jtorres@uji.es?subject=IPIN%202016%20Competition%20Dataset%20(Zenodo)">jtorres@uji.es</a>) Institute of New Imaging Technologies, Universitat Jaume I, Spain.&nbsp;</li> <li>Antonio R. Jim&eacute;nez (<a href="mailto:antonio.jimenez@csic.es?subject=IPIN%202016%20Competition%20Dataset%20(Zenodo)">antonio.jimenez@csic.es</a>) Center of Automation and Robotics (CAR)-CSIC/UPM, Spain.&nbsp;</li> </ul> <p>&nbsp; &nbsp;&nbsp;</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

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