Vectorized Topographic Maps (VTMs) offer standardized and comprehensive information crucial for researchers across various disciplines, including the social and natural sciences. With VTMs, it is possible to delineate both natural and man-made features over time and space, encompassing water lines, relief areas, soil types, and soil uses. Understanding spatial environments is integral for the recognition and preservation of cultural heritage. Despite digitization, analyzing archaeological data alongside topographic maps remains labor-intensive. Knowledge Graphs represent, organize, and semantically link diverse data types, offering a solution and facilitating semantic querying for enhanced analysis. A method to integrate vector geographic features and archaeological data into a labeled property graph is proposed. This study uses CIDOC-CRM and GeoSPARQL ontologies as the backbone to enable easy querying and visualization to discern patterns related to monument localization. The approach is validated using megalithic monuments—dolmens—in Pavia-Mora (Portugal), and official VTMs from various national organizations. This study demonstrates the effective representation and querying of multiple data types, thus contributing to the discovery of patterns and the inference of knowledge about the dolmens localizations. This, in turn, could be instrumental in improving the recognition and preservation of these monuments.