Semantic Modelling


Semantic modelling involves the formalization of knowledge, collected into a shared worldview that defines concepts and the relationships between them, and offered to users through k.IM, an intuitive English-like language that can be used to query the system and to write models.

How does Semantic modelling contribute to achieving the Sustainable Development Goals?


The AI-based approach used in ARIES, powered by semantics and machine reasoning, supports the large-scale, multi-scale and multi-domain knowledge integration needed to assess progress towards the SDGs. Web-hosted informational assets, labeled with semantics, become readable and linkable by both humans and computers. Machine-supported intelligence can thus search, organize, reuse, combine and synthesize information quickly and safely. The application of the ARIES technology by a broad community of scientists and decision makers is already supporting open synthesis and contributing to the reuse of knowledge in decision-making and research.

No poverty

Zero Hunger

Good health and well-being

Quality education

Gender equality

Clean water and sanitation

Affordable and clean energy

Decent work and economic growth

Industry, innovation and infrastructure

Reduced inequalities

Sustainable cities and communities

Responsible consumption and production

Climate action

Life below water

Life on land

Peace, justice, and strong institutions

Partnerships for the goals

The Global Goals for Sustainable Development

Get started with semantic modelling


Learn more about the innovative technology behind ARIES in this technical introduction, providing an overview of the main components of k.LAB, the open-source software stack on which ARIES is based. The overview describes the k.IM language, used to provide semantic annotations to integrate scientific data and models and the k.Actors language, used to build applications and reactive, semantically enabled digital twins.

This comprehensive document is a full description of the integrated modelling approach for a technically savvy audience, aimed to improve users’ understanding of the main principles and architecture of the semantic web platform that powers ARIES.