This study addresses the challenges of integrating heterogeneous environmental geospatial data by proposing a framework based on ontology-based data access (OBDA). Geospatial data are important for decision-making in various domains, such as environmental monitoring, disaster management, and urban development. Data integration is a common challenge within these domains due to data heterogeneity and semantic discrepancies. The proposed framework uses semantic web technologies to enhance data interoperability, accessibility, and usability. Several practical examples were demonstrated to validate its effectiveness. These examples were based in Lake Mjøsa, Norway, addressing both spatial and non-spatial scenarios to test the framework’s potential. By extending the GeoSPARQL ontology, the framework supports SPARQL queries to retrieve information based on user requirements. A web-based SPARQL Query Interface (SQI) was developed to execute queries and display the retrieved data in tabular and visual format. Utilizing free and open-source software (FOSS), the framework is easily replicable for stakeholders and researchers. Despite some limitations, the study concludes that the framework is able to enhance cross-domain data integration and semantic querying in various informed decision-making scenarios.

Integrating digital twin (DT) technologies with Geographic Information Systems (GIS) marks a transformative shift in geospatial analysis, enabling continuous synchronization for an accurate representation of the physical landscape, offering decision-makers dynamic and context-specific insights for informed decision-making. Geospatial data, crucial across various domains, has historically faced challenges in integration, visualization, and interpretation due to its vast and fragmented nature. The emergence of the DT concept has the potential to address these constraints by creating virtual replicas of real-world objects in a digital environment. The seamless integration of DT technologies with existing GIS (integrated DT-GIS) enables multiple stakeholders to make collaborative decisions through interactive processes. This review aims to investigate the state of the art of the use of integrated DT-GIS across domains such as urban planning, disaster management, and water resource and environmental management, challenges that hinder the full potential of integrated DT-GIS, and some improvements that can be made to enhance the capabilities of integrated DT-GIS for geospatial analysis to enhance the decision-making process.

Developing spatial digital twins (SDTs) for inland water bodies requires addressing challenges such as temporal variability, dynamic water surface conditions, and heterogeneous water datasets. This study presents a semantic integration framework combining Ontology-Based Data Access (OBDA) with PostgreSQL database federation to support real-time decision-making in SDT applications. The framework integrates hydrological data, sensor networks, bathymetric data, and other static datasets under a unified ontology, enabling federated SPARQL queries without centralizing data. A 3D visualization interface allows interactive analysis of results from the SPARQL queries. Demonstrated through the Mission Mjøsa use case, this approach supports inland water mapping and decision support by aligning spatial data across domains. The framework offers a scalable solution for water data processing, semantic fusion, and scenario-based simulation, contributing to the development of intelligent, semantically enriched SDTs for sustainable environment management.