The geotechnical engineering profession has been very successful in making safe decisions and managing risk in a data-poor environment through an assortment of effective strategies such as imposing a large global factor of safety and choosing appropriate characteristic values of geotechnical parameter (e.g., soil cohesion, internal friction angle, or resistance) at the design stage and adopting the observational approach at the construction stage. The current question is how geotechnical engineers can take advantage of an opposite data-rich environment to make even better decisions in the face of rapid advancement in digital technologies.
A new field called data-centric geotechnics is emerging in response to this widely discussed question. In fact, the International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE) has created a new technical committee TC309 “Machine Learning and Big Data” to hasten the development in this field. To explore the value of database in geotechnical engineering practice, the session “Data-Centric Geotechnics” is proposed that is soliciting presentations for ISGSR 2022 on (but not limited to):
1. Soil/rock (univariate/multivariate) property database
2. Data-based (generic/local/quasi-local) transformation models for geotechnical parameters
3. Data-driven site characterization (recognition, stratification, and characterization)
4. Load test/case history database for geotechnical structures (e.g., anchor, augered cast-in-place and drilled displacement pile, drilled shaft, driven pile, excavation, helical pile, mechanically stabilized earth wall, micropile, pipeline, slope, soil nail wall, and tunnel)
5. Data-based evaluation and improvement of design methods for geotechnical stability (resistance) and deformation (settlement)
6. Data-driven design model of geotechnical structures
7. Inverse analysis and reliability update
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