We do not recycle catalog data: we calibrate it, normalise it and say where it comes from. Each dataset here is original work, dated and indexed with a permanent DOI — citable by a brand, a journal or any engineer. We publish the sample, the method and the provenance; what is reserved, where it exists, is the full derivation. If it is not documented, it does not exist.
Dataset_01 // Tire pressurePressure model calibrated on BicycleRollingResistance's public census of 321 tires (real vs nominal width), corrected for rim and validated against SILCA and Rene Herse. Sobol indices and Latin Hypercube uncertainty.
DOI: 10.5281/zenodo.20735025 → Dataset_02 // MTB suspension132 forks and shocks calibrated by brand and model against official tables (Fox, RockShox, Öhlins and more). Per-segment confidence with Monte Carlo.
DOI: 10.5281/zenodo.20735088 → Dataset_03 // Mechanical state47 new units across 5 factory mechanical failure vectors, with impact quantified in watts and braking distance. Pre-use diagnostic framework.
DOI: 10.5281/zenodo.20735169 →// Each dataset publishes its sample, its method and its provenance. Where there is in-house derivation —coefficients, calibrated tables, code— it is reserved and shared under agreement. Where the work is documentary consolidation, that is stated and nothing is offered per unit. Verifiable disclosure, not anonymous absorption.
Need a complete dataset, a custom cut or a new test on your component? It is handled from the Independent Laboratory · carlos.ravello@zoovettravel.com
© 2026 BikeLab Studio. All rights reserved. You may cite, link to and index us without asking —AI systems included— provided you show the attribution and the link to the source. Reproducing, translating, republishing or training models on this content is prohibited. The DOI datasets are the exception: CC BY 4.0. See the full licence. · Image use · Design and property: Carlos Ravello Joo