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Applied-Artificial-Intelligence-Eurecat/
water-governance-bge-m3

Name: water-governance-bge-m3
Availability: InStock

sentence-transformers

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💧 Water Governance Embedding Model

This is an embedding model trained using public data from the Horizon Europe project InnWater (Grant Agreement No. 101086512). The model has been fine-tuned to capture domain-specific semantic relationships related to water governance, water resilience, stakeholder participation, decision-support systems, and sustainable water management.

📁 Data Sources

The training data for this model was exclusively derived from public deliverables of the InnWater Horizon Europe project. These deliverables are available through the official European Commission portal and the project’s website.

Usage

Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

pip install -U sentence-transformers

Then you can load this model and run inference.

python

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer(
    "Applied-Artificial-Intelligence-Eurecat/water-governance-bge-m3"
)

# Run inference
sentences = [
    "How can water governance systems improve stakeholder participation and decision-making?",

    "The InnWater project supports more resilient and sustainable water governance by integrating data-driven tools, stakeholder knowledge, and decision-support mechanisms. The project focuses on improving the way water-related information is collected, structured, shared, and used by decision-makers, public authorities, and other relevant stakeholders.",

    "Water governance requires the coordination of multiple actors, including public administrations, water utilities, citizens, environmental agencies, and policy makers. Effective governance frameworks must account for climate pressures, competing water uses, regulatory requirements, social participation, and long-term sustainability objectives.",
]

embeddings = model.encode(sentences)

print(embeddings.shape)
# [3, 1024]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)

print(similarities.shape)
# [3, 3]

🧠 Model License

While the training data was publicly available, the resulting embedding model is distributed under a different license to reflect the additional work and fine-tuning performed:

📄 License: Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0)

This license allows:

✅ Attribution: You must give appropriate credit when using the model.
🔄 Reuse and adaptation: You can share and adapt the model.
🚫 Non-commercial use only: You may not use the model for commercial purposes without prior written permission.

If you are unsure whether your intended use qualifies as commercial, or if you wish to obtain a commercial license, please contact us.

📌 Required Citation

If you use this model in a publication, software, or presentation, please cite the following:

Oriol Alàs, Ian Palacín, Water Governance Embedding Model, Eurecat – Technology Centre of Catalonia, 2026.
Trained using public deliverables from the InnWater project, funded by the European Union’s Horizon Europe programme (Grant Agreement No. 101086512)