From Geoscience to decision-making: How ThermEcoWat used a TypeDB knowledge graph for climate change adaptation planning

France’s national geological survey (BRGM) recently launched a new platform to address challenges associated with climate change in regional spa towns across parts of South-western Europe.

A TypeDB knowledge graph provides the core architecture of this platform. The project itself takes a multidisciplinary approach to address the challenges:

• Hydrogeological and Climate Modeling: Medium-term projections (up to 2070) regarding the impact of climate change (e.g. reduction in the low-flow periods of the Remontalou river, increased severity of droughts).
• Energy Demand Analysis: Simulation of thermal and mass balances (e.g. for the thermal infrastructure) aimed at optimizing waste heat recovery and evaluating solutions such as heat pumps or urban district heating networks.
• Governance and Constraint Analysis: Mapping management entities, system vulnerabilities (e.g. centralized wells, usage conflicts), and the socio-economic impacts of potential governance agreements.

From science to complex decision making: The application of knowledge graphs within ThermEcoWat

Traditional, linear models prove insufficient when representing the systemic complexity of natural resources and territorial decision-making. To address this, the project uses the ExGy© (pronounced ‘Exigency’) Knowledge Management Framework for developing the TEW KG (ThermEcoWat Knowledge Graph) for environmental and governance analysis.

This framework relies on standardized integration of heterogeneous data. ExGy enables the unification of strictly scientific parameters (hydrogeology, faults, lithology, climate data) with operational and administrative elements (infrastructure, stakeholders, legal constraints) into a single, shared semantic structure.

The system is designed to generate specific sub-graphs or “clusters” targeted to particular analytical phases or stakeholder types (e.g. Water management cluster, Geothermal cluster, Urban planning cluster).

Given that different stakeholders (scientists, public authorities, economic operators) often speak different professional languages, a clean symbolic representation helps bridge cognitive gaps by establishing common, mutually understood concepts.

Why TypeDB was a natural fit for BRGM’s data-to-decision pipeline

The engine driving the project’s “Data-to-Decision” pipeline is built on TypeDB. Our technology delivers unique capabilities as a strongly-typed graph database to underpin the use case:

• Polymorphic model and Strong Subtyping: TypeDB allows for the definition of complex, strongly typed hierarchies of entities and relations. For instance, it flexibly distinguishes and correlates different types of thermal springs, regulatory constraints, and the distinct decision-making levels of territorial actors, within a unified schema.
• TypeQL Query Language: Using declarative pattern matching, TypeQL simplifies querying indirect, deeply nested, or chained relationships. This makes it cleaner to trace how a specific climate change impact affects a particular infrastructure, and identify exactly which stakeholders are legally responsible for it.
• Native Reasoning via Functions: Instead of relying on external computation, TypeDB allows complex logic to be embedded directly into the schema using simple recursive functions. The database evaluates these functions at query time to deduce groupings and relationships that were not explicitly recorded. Consequently, it supports scenario analysis, cost-benefit evaluations, and the dynamic assessment of cascading impacts stemming from policy and economic decisions.

Project feedback from BRGM

According to the Vice-Mayor of São Pedro do Sul (Thermalism and environment), the ExGy framework successfully translates systemic complexity into a clear, structured adaptation model:

• Identify the key vulnerabilities affecting thermal resources, water systems, and infrastructure/mobility
• Link each vulnerability to realistic adaptation measures and the respective responsible actors.
• Use indicators to compare these measures transparently, prioritizing those with the highest feasibility and impact

The experience demonstrates that the ExGy Framework powered by TypeDB enables multidisciplinary researchers and stakeholders to transform raw data and administrative constraints into a functional Decision Aiding System. The full solution allows local decision-makers to visualize territorial vulnerabilities and co-design evidence-based, transparent, and shared climate adaptation plans.

From the TypeDB side, we are delighted to support the project, and see the impact across the different organizations and governments.