This article presents an innovative workflow for the acquisition and storage of archaeological data. The system is based on open-source software to enhance method replication and media accessibility. QGIS software is used as the central platform, connected to a spatial database developed in PostgreSQL and managed with the SQL and Python programming languages. The aim is to achieve an efficient, flexible, and reproducible digital method for data collection and management that can be applied to surface archaeological surveys. During the implementation and development of the method, we have recorded over 4,600 archaeological remains in two different structures with traces of Upper Paleolithic activity in the Lower Gallery of La Garma (Cantabria, Spain). After 18 months of continuous work, the results obtained demonstrate the usefulness and versatility of this procedure, which can be adapted to each context and to the specific needs of each researcher. Our goal is not simply to systematize archaeological documentation, as traditionally proposed, but to establish a simple and robust method for data collection and preservation, accessible to any user. Its fully open-source approach aims to promote a model that is nurtured by the use and contributions of the research community.

In this article, an approach is presented for the representation and reasoning over qualitative spatial relations. A set-theoretic approach is used for representing the topology of objects and underlying space by retaining connectivity relationships between objects and space components in a structure, denoted, adjacency matrix. Spatial relations are represented by the intersection of components, and spatial reasoning is achieved by the application of general rules for the propagation of the intersection constraints between those components. The representation approach is general and can be adapted for different space resolutions and granularities of relations. The reasoning mechanism is simple and the spatial compositions are achieved in a finite definite number of steps, controlled by the complexity needed in the representation of objects and the granularity of the spatial relations required. The application of the method is presented over geometric structures that takes into account qualitative surface height information. It is also shown how directional relationships can be used in a hybrid approach for richer composition scenarios. The main advantage of this work is that it offers a unified platform for handling different relations in the qualitative space, which is a step toward developing general spatial reasoning engines for large spatial databases.