Given the relative dearth of, and the huge demand for, quantitative spatial soil information, it is timely to develop and implement methodologies for its provision. We suggest that digital soil mapping, which can be defined as the creation, and population of spatial soil information systems (SSINFOS) by the use of field and laboratory observational methods, coupled with spatial and non-spatial soil inference systems, is the appropriate response. Problems of large extents and soil-cover complexity and coarse resolutions and short-range variability representation carry over from conventional soil survey to digital soil mapping. Meeting users' requests and demands and the ability to deal with spatially variable and temporally evolving datasets must be the key features of any new approach. In this chapter, we present a generic framework that recognises the procedures required. Within quantitatively defined physiographic regions, SSINFOS must be populated and spatial soil inference systems (SSINFERS) must be developed. When combined this will allow users to derive the data they require. Further work is required on the development of these systems, and on the data requirements, the optimal forms of inference and the appropriate representation of the products of digital soil mapping.