# Enabling Biodiversity-Informed Architecture Through Ontology-Driven Data Integration
## 3 Related Work  
The use of Semantic Web technologies and OWL to represent ecological network specifications is explored in [30]. Ecological networks capture the structure of existing ecosystems and provide a basis for planning their expansion, conservation, and enhancement. An OWL ontology is employed to model these networks, enabling reasoning about potential improvements and identifying violations in proposed network expansions. The approach incorporates a language called GeCoLan to define ecological network specifications, which are subsequently translated into GeoSPARQL queries. This methodology enhances the planning and management of ecological networks by supporting automated reasoning and integrating diverse data sources effectively. Global Biotic Interactions (GLOBI) [9] is an open-access platform designed for researchers, aggregating diverse datasets to provide comprehensive information on species interactions, such as predator-prey, pollinator-plant, and parasite-host relationships, among others. The platform serves as a valuable resource for understanding ecological networks, predicting the effects of environmental changes, and guiding conservation strategies. It consolidates and harmonises data on species and their occurrences and interactions from a variety of publications and observational databases. GLOBI offers both an API and a SPARQL endpoint (with partial data coverage) for accessing species interaction data in CSV or RDF formats. Species data are structured using the Darwin Core vocabulary, with equivalence between species established through owl:sameAs relations. Additionally, the platform features a web-based frontend application that supports species searches via text and/or geographical boundaries. OBO Relations ([[http://obofoundry.org/ontology/ro.html](http://obofoundry.org/ontology/ro.html)]([http://obofoundry.org/ontology/ro.html](http://obofoundry.org/ontology/ro.html)), accessed on 17 March 2025) ontology can be leveraged for reasoning to infer implicit interactions based on explicitly recorded triples. The integration of ontologies and knowledge graphs in urban ecology has gained significant attention due to their ability to model complex interactions between built environments and natural ecosystems [18]. Existing research spans two major domains: Architecture, Engineering, and Construction (AEC(O)) and Urban Design, Planning, and Management, both of which are crucial for advancing sustainable urban development. Ontologies and knowledge graphs have been extensively used in AEC(O) to improve data interoperability, lifecycle management, and decision support systems. In Building Modelling, semantic models such as the Industry Foundation Classes (IFC) ontology enable structured data exchange across different software platforms [31]. In Building Construction and Renovation, ontologies assist in process optimisation, cost estimation, and resource planning by integrating heterogeneous datasets [32]. Additionally, Building Automation has benefited from ontologies like the Brick schema, which enables the semantic representation of building sensors and control systems. Ontologies also play a key role in Building Sustainability, facilitating the assessment of energy efficiency and carbon footprints [33]. Semantic models allow for the integration of green building certification standards (e.g., LEED, BREEAM) with real-time building performance data, enhancing decision-making for sustainable design and renovation [34]. Ontologies have been applied in City Modelling, enhancing urban digital twins with semantic interoperability [35]. The CityGML standard, extended with ontologies, provides a structured representation of urban elements, supporting applications in Civil Construction and infrastructure management. Urban Sustainability ontologies enable the integration of environmental indicators with urban planning tools, aiding in decision-making for reducing ecological footprints [36]. The role of Urban Green and Blue Infrastructure ontologies is particularly relevant for urban ecology.