A graph-based representation of knowledge for managing land administration data from distributed agencies–A case study of Colombia

Abstract

Multiple efforts have been performed worldwide around diverse aspects of land administration. However, land administration data and systems’ notorious heterogeneity remains a longstanding challenge to develop a harmonized vision. In this sense, the traditional Spatial Data Infrastructures adoption is not enough to overcome this challenge since data sources’ heterogeneity implies needs related to harmonization interoperability, sharing, and integration in land administration development. This paper proposes a graph-based representation of knowledge for integrating multiple and heterogeneous data sources (tables, shapefiles, geodatabases, and WFS services) belonging to two Colombian agencies within a decentralized land administration scenario. These knowledge graphs are developed on an ontology-based knowledge representation using national and international standards for land administration. Our approach aims to prevent data isolation, enable cross-datasets integration, accomplish machine-processable data, and facilitate the reuse and exploitation of multi-jurisdictional datasets in a single approach. A real case study demonstrates the applicability of the land administration data cycle deployed.