Data-centric geotechnics is an emerging field in civil engineering. It is by nature a crafted combination of data science and geotechnics. Beyond classical statistics, data science is regarded as Statistics 2.0 using artificial intelligence, machine learning, and other digital technologies to extract value and knowledge from big data. However, the agenda for machine learning in geotechnics should not be focused on applying or developing algorithms alone. The geotechnical context that gives rise to the data is important. Therefore, data-centric geotechnics requires development of machine learning or other digital technologies in geotechnics to be carried out with an appropriate balance of three elements: (1) data centricity, (2) fit for (and transform) practice, and (3) geotechnical context.